Allgemein
Big Data
Manipulating and processing masses of digital data is never a purely technical activity. It requires an interpretative and exploratory outlook - already well known in the social sciences and the humanities - to convey intelligible results from data analysis algorithms and create new knowledge.Big Data is based on an inquiry of several years within Proxem, a software publisher specializing in big data processing. The book examines how data scientists explore, interpret and visualize our digital traces to make sense of them, and to produce new knowledge. Grounded in epistemology and science and technology studies, Big Data offers a reflection on data in general, and on how they help us to better understand reality and decide on our daily actions.ÉGLANTINE SCHMITT holds a PhD in Philosophy of Science from the University of Technology of Compiègne (Sorbonne Universités), France. After 7 years at Proxem, she has devoted her career to building bridges between humans and technology through product management and design, in a start-up environment.Introduction viiCHAPTER 1. FROM TRACE TO WEB DATA: AN ONTOLOGY OF THE DIGITAL FOOTPRINT 11.1. The epistemology of the cultural sciences 71.2. The footprint in evidential sciences 91.3. The log or activity history 141.4. The digital footprint as a web log 181.5. The intentionality of digital footprints 201.6. Data as theoretically-loaded footprints 24CHAPTER 2. TOWARD AN EPISTEMIC CONTINUITY ANCHORED IN THE CULTURAL SCIENCES 292.1. Digital technology in the cultural sciences 312.2. Field and corpus: two modes of access to reality 342.3. Virtual methods, a reconstruction of access to the field 382.4. The challenges of the technical revolution of the text 482.5. From the web as an object to the web as a corpus 592.6. Conclusion 69CHAPTER 3. THE STATUS OF COMPUTATION IN DATA SCIENCES 713.1. Making data computable 733.2. The field of computability 773.3. Computational thinking 813.4. Computation in the natural sciences 873.5. From exploratory analysis to data mining 983.6. The institutional and theoretical melting pot of data science 1073.7. The contribution of artificial intelligence 1153.8. Conclusion 122CHAPTER 4. A PRACTICAL BIG DATA USE CASE 1254.1. Presentation of the case study 1264.2. Customer experience and coding of feedback1314.3. From the representative approach to the “big data” project 1344.4. Data preparation 1374.5. Design of the coding plan 1404.6. The constitution of linguistic resources 1434.7. Constituting the coding plan 1484.8. Visibility of the language activity 1534.9. Storytelling and interpretation of the data 1554.10. Conclusion 161CHAPTER 5. FROM NARRATIVES TO SYSTEMS: HOW TO SHAPE AND SHARE DATA ANALYSIS 1655.1. Two epistemic configurations 1665.2. The genesis of systems 1725.3. Conclusion 183CHAPTER 6. THE ART OF DATA VISUALIZATION 1876.1. Graphic semiology 1876.2. Data cartography 1986.3. Representation as evidence 2036.4. The visual language of design in system configuration 2076.5. Materialization and interpretation of recommendations 214CHAPTER 7. KNOWLEDGE AND DECISION 2197.1. Big data, a pragmatic epistemology? 2207.2. Toward gradual validity of knowledge 2277.3. Deciding, knowing and measuring 233Conclusion 239References 243Index 257
Patientenorientierte Digitalisierung im Krankenhaus
Dieses Buch dient Ihnen als Leitfaden für die Digitalisierung im Krankenhaus Gesundheitsbetriebe wie Spitäler stehen in einem Spannungsfeld zwischen steigenden Qualitätsansprüchen und Kosteneffizienz. Deshalb geben Ihnen die Autoren dieses Buchs einen aktuellen Überblick zu den Herausforderungen und den Möglichkeiten der Digitalisierung im Umfeld von Krankenhäusern. Anhand eines fiktiven Beispieles verdeutlichen Ihnen die Verfasser sowohl die Möglichkeiten als auch die Schwierigkeiten dieses Prozesses. Ziel dieses Werks ist es, die Grundlagen der Digitalisierung einer Klinik verständlich für alle Beteiligten darzustellen. Dazu führen die Autoren ein Modell ein, das den Patienten ins Zentrum rückt und das IT-Architekturmanagement mit dem Weg des Patienten durch die Behandlung verknüpft. Zudem erfahren Sie in diesem Buch, wie eine optimale IT-Struktur als Entscheidungs- und Erklärungsgrundlage in einem Krankenhaus dienen kann, um so den Kulturwandel herbeizuführen, der mit einer umfassenden Digitalisierung einhergeht. So schaffen Sie die optimale Basis für zukünftige Prozesse Zu Beginn dieses Buchs erläutern die Autoren, was Digitalisierung überhaupt ist und welche Rolle sie in Krankenhäusern spielt. Markus Mangiapane und Matthias Bender klären Sie über die Fähigkeiten und Voraussetzungen auf, die Sie im Zuge einer erfolgreichen digitalen Transformation benötigen. Die anschließenden Kapitel stellen schwerpunktmäßig folgende Aspekte in den Mittelpunkt: Die vier Pfeiler der digitalen TransformationRechtliche RahmenbedingungenProzessmanagement und -sicherheitEMR Adoption Model (EMRAM)Praktische Umsetzung des Enterprise Architektur Management (EAM)Informationssicherheit und -archivierung Zusätzliche Beispiele aus dem Alltag der Krankenhausinformation schlagen Brücken von der Theorie zur praktischen Anwendung und verdeutlichen die Schwierigkeiten bei der realen Umsetzung der Digitalisierung im Krankenhaus. Mit diesem Werk als Leitfaden sind Sie in der Lage, eine gemeinsame Wissensbasis für die erfolgreiche digitale Transformation von Geschäftsprozessen zu bilden. Das Buch „Patientenorientierte Digitalisierung im Krankenhaus“ ist daher eine Leseempfehlung für: Direktoren und Entscheidungsträger aus den Bereichen CIO, IT oder dem KrankenhausmanagementMedizininformatiker, Ärzte und medizinisches PersonalStudierende der Informatik, Medizininformatik und angrenzender Fächer Einleitung.- Was ist eigentlich Digitalisierung?.- Die vier Pfeiler der digitalen Transformation.- Rechtliche Rahmenbedingungen.- EMR Adoption Model (EMRAM).- Kunden und Patienten.- Grundmodell EAM.- Schichten-Modell.- Implementierung einer Digitalisierungsstrategie mittels EAM.- Fazit.- Literatur.
Welche KI?
Künstliche Intelligenz hat das Potenzial, viele Bereiche unseres Lebens grundlegend zu verändern. Dies betrifft unter anderem Veränderungen der Arbeitswelt, autonome Fahrzeuge oder sogar Waffen, das Gesundheitssystem, demokratische Gesellschaftsstrukturen und die gesamte Lebenswelt. Daraus erwachsen große Chancen für die Gesellschaft, aber auch große Gefahren.In der Analyse solcher Szenarien zeigt sich, dass die Auswirkungen von KI in einer ethischen Detailbetrachtung nicht ausreichend erfasst werden können. Vielmehr müssen sie aus einem umfassenden gesellschaftlichen und menschlichen Zusammenhang beurteilt werden. In diesem Buch wird daher eine Perspektive auf KI gezeigt, die ethische Detailfragen zu den Anwendungen von KI aus der größeren Perspektive philosophischer Reflexion betrachtet.Diese umfasst philosophische Überlegungen zur Auswirkung der Technik und die Betrachtung von Szenarien der Technikentwicklung. Weiterhin werden Veränderungen des Menschenbildes analysiert, die mit der Entwicklung von KI verbunden sind. Damit hängt die Frage zusammen, ob KI Bewusstsein entwickeln kann und ob einer fortgeschrittenen KI ein Rechtsstatus einer elektronischen Persönlichkeit zugeordnet werden soll.Die betrachteten Entwicklungsszenarien umfassen die Veränderung der Arbeitswelt zwischen einer Hoffnung auf eine Entlastung von monotonen und gefährlichen Tätigkeiten einerseits und der Gefahr von Massenarbeitslosigkeit andererseits. Weiterhin werden neben den bekannten Problemen des autonomen Fahrens die Auswirkungen auf Szenarien der Mobilität betrachtet. In Bezug auf den Einsatz von autonomen Waffen und auf die Steuerung der Kriegsführung durch KI wird das Szenario eines neuen Wettrüstens und einer Entgrenzung der Kriegsführung vorgestellt, das eine Ächtung dieser Techniken nahelegt.Für das Gesundheitssystem und die Altenpflege wird das Szenarium einer weiteren Entmenschlichung dieser Bereiche mit einem Konzept kontrastiert, das dem menschlichen Faktor gerade durch die Entlastung von technischen Aufgaben einen neuen Stellenwert gibt. Entsprechende Szenarien werden für die Auswirkungen von KI auf die Demokratie und die Durchdringung der Lebenswelt vorgestellt. Prof. Dr. Stefan Bauberger hat Philosophie, Theologie und Physik studiert. Er hat ein Diplom in Theologie, eine Promotion in theoretischer Physik und eine Habilitation in Philosophie erworben. Er ist an der Hochschule für Philosophie in München als Professor für Naturphilosophie und Wissenschaftstheorie tätig. Seit einigen Jahren liegt sein Schwerpunkt auf der Technikphilosophie, mit besonderer Ausrichtung auf die Künstliche Intelligenz.
Einstieg in Deep Reinforcement Learning
- Grundlegende Konzepte und Terminologie- Praktischer Einsatz mit PyTorch- Projekte umsetzenDieses Buch zeigt Ihnen, wie Sie Agenten programmieren, die basierend auf direktem Feedback aus ihrer Umgebung selbstständig lernen und sich dabei verbessern. Sie werden Netzwerke mit dem beliebten PyTorch-Deep-Learning-Framework aufbauen, um bestärkende Lernalgorithmen zu erforschen. Diese reichen von Deep-Q-Networks über Methoden zur Gradientenmethode bis hin zu evolutionären Algorithmen.Im weiteren Verlauf des Buches wenden Sie Ihre Kenntnisse in praktischen Projekten wie der Steuerung simulierter Roboter, der Automatisierung von Börsengeschäften oder dem Aufbau eines Spiel-Bots an.Aus dem Inhalt:- Strukturierungsprobleme als Markov-Entscheidungsprozesse- Beliebte Algorithmen wie Deep Q-Networks, Policy Gradient-Methode und Evolutionäre Algorithmen und die Intuitionen, die sie antreiben- Anwendung von Verstärkungslernalgorithmen auf reale Probleme Alexander Zai ist Machine Learning Engineer bei Amazon AI und arbeitet an MXNet, das eine Reihe von AWS-Maschinenlernprodukten unterstützt. Er ist auch Mitbegründer von Codesmith, einem Bootcamp für Softwareentwicklung mit Niederlassungen in Los Angeles und New York.Brandon Brown ist Medizinstudent und Data Scientist an der UCLA. Er hat in den letzten drei Jahren ausführlich über maschinelles Lernen auf outlace.com gebloggt.
Visualizing Health and Healthcare Data
THE ONLY DATA VISUALIZATION BOOK WRITTEN BY AND FOR HEALTH AND HEALTHCARE PROFESSIONALS.In health and healthcare, data and information are coming at organizations faster than they can consume and interpret it. Health providers, payers, public health departments, researchers, and health information technology groups know the ability to analyze and communicate this vast array of data in a clear and compelling manner is paramount to success. However, they simply cannot find experienced people with the necessary qualifications. The quickest (and often the only) route to meeting this challenge is to hire smart people and train them.Visualizing Health and Healthcare Data: Creating Clear and Compelling Visualizations to "See how You're Doing" is a one-of-a-kind book for health and healthcare professionals to learn the best practices of data visualization specific to their field. It provides a high-level summary of health and healthcare data, an overview of relevant visual intelligence research, strategies and techniques to gather requirements, and how to build strong teams with the expertise required to create dashboards and reports that people love to use. Clear and detailed explanations of data visualization best practices will help you understand the how and the why.* Learn how to build beautiful and useful data products that deliver powerful insights for the end user* Follow along with examples of data visualization best practices, including table and graph design for health and healthcare data* Learn the difference between dashboards, reports, multidimensional exploratory displays and infographics (and why it matters)* Avoid common mistakes in data visualization by learning why they do not work and better ways to display the dataWritten by a top leader in the field of health and healthcare data visualization, this book is an excellent resource for top management in healthcare, as well as entry-level to experienced data analysts in any health-related organization.KATHY ROWELL is a nationally recognized health, healthcare, and data visualization expert, lecturer, and author specializing in helping leading organizations analyze, design, and present visual displays of data to inform their decisions and stimulate effective action. She is the co-author of the Best Boring Book Ever (BBBE) of Healthcare Classification Systems and Databases, and BBBE of Tableau for Healthcare Professionals, which are used by numerous colleges and universities and professional organizations to teach and train students and professionals.Kathy is the Co-founder and Principal of HealthDataViz (HDV) where she has led innovative and ground-breaking projects and data visualization training initiatives for leading organizations such as Memorial Sloan Kettering Cancer Center, the Centers for Medicare and Medicaid Services, and the Children’s Hospital Association. A graduate of the University of NH and Dartmouth Medical School, Kathy lives in Maine and loves being on the water and cruising the coast with her family on their boat "Visualize."With seven years wholly immersed in healthcare data visualization, following ten years as a licensed marriage and family therapist, Lindsay brings a wealth of direct care experience and an unbridled passion and nationally recognized expertise for visualizing health and healthcare data. A Tableau Zen Master and member of the HealthDataViz (HDV) team, LINDSAY is an enthusiastic creator of effective, intuitive, and beautiful dashboards that people love to use and make the story and opportunities buried in the data clear. Her passion for health and healthcare data knows no bounds evidenced by her establishment of #ProjectHealthViz, a community of passionate data visualizers that create displays of health and healthcare data each month to tell our health stories.Lindsay has a B.A. from Bucknell University and an M.A. from the University of Connecticut. She currently lives in Pennsylvania with her husband and two boys.CAMBRIA BROWN has over ten years of experience analyzing and visualizing health and healthcare data, and is a Tableau Desktop Certified Professional. With a background in public health, survey design, advanced biostatistics, and quality improvement, Cambria understands the full data use cycle and is passionate about helping organizations use data to improve health.As a member of the HealthDataViz team, she has developed beautiful, user-friendly, and high impact dashboards for a variety of clients including the New York City Dept. of Health and Mental Hygiene, the Colorado Dept. of Public Health and Environment, and the Urban Indian Health Institute. Cambria holds a Master of Public Health in Epidemiology and Biostatistics from Oregon Health & Science University. She lives in Colorado where, when not data vizzing, she enjoys going on adventures with her husband and two children.Preface xiiiSECTION I ESTABLISHING A FRAMEWORK AND PROCESS 1CHAPTER 1 HEALTH AND HEALTHCARE DATA VISUALIZATIONS OF HISTORICAL IMPORTANCE 3CHAPTER 2 STOP HUNTING UNICORNS AND START BUILDING TEAMS AND KNOW THE DATA 9Search for Characteristics and Core Competencies 10Get to Know the Data 11Classifications, Intent, Purpose, and Lineage 12Two Types of Data 14Qualitative/Categorical Data 14Quantitative/Numerical Data 14Scales/Levels of Measure 15Nominal 15Ordinal 16Interval 17Ratio 18Summary 19CHAPTER 3 REQUIREMENTS-GATHERING AND DESIGN METHODS 21Design Thinking Foundational Concepts 22Design Methods 23Contextual Inquiry 23Mental Models 24Personas 26Persona Creation Guide 27Graphic Organizers 29Guided Analytics Framework 29Summary Overview Dashboard 30Supporting Focused Reports 30Details 31Multidimensional Exploratory Displays (MEDs™) 31Sketching 32Prototyping 33Testing 34Summary 36SECTION II PERCEIVING THE BEST PRACTICES OF DATA VISUALIZATION 37CHAPTER 4 THE RESEARCH 39Research Informs Data Visualization Best Practices 39Preattentive Attributes 41Preattentive Attributes at Work 43Gestalt Principles 46Color Theory 48The Power of White Space 53Where People Look 54Summary 54CHAPTER 5 TABLE DESIGN CHECKLIST 55Fundamentals of Table Design 55Organization/Categorization 55Non-Data Ink 56Fonts 56Number Alignment and Formatting 56Labels 58Summary 58CHAPTER 6 POWERFUL VISUALIZATIONS IN FOUR SHAPES 59Bars, Lines, Points, and Boxes 59Shape One: Bars 61Bar Basics 61Using Bars To: See How You’re Doing 63Distributions 63Histograms 63Population Pyramid (Paired Bars) 65Ranking 67Change over Time 68Comparing Multiple Data Points 70Proportions | Part-to-Whole 71Challenging the 100% Myth 73Deviation (Difference, Variation) 73Ranges and Comparative Values 74Displaying the Vital Few: Pareto Charts 77Bars Are Not Boring 78Shape Two: Lines 79Line Basics 79Using Lines To: See How You’re Doing 83As a Reference | Comparison 83Change over Time 84Change over Time | Sparklines 86Change over Time | Deviation Graphs 87Distributions 88Distributions | The Empirical Rule and Control Charts 88Statistical Process Control Charts (SPCs) and Geometric (G) Charts 90Relationships | Correlations 91Shape Three: Points 92Point Basics 92Using Points To: See How You’re Doing 94Distributions 94Revealing Details 95Change over Time 96Correlation 96Hierarchy Quadrant 97Location Details 98Shape Four: Boxes 98Box Basics 99Using Boxes To: See How You’re Doing 99Distribution 99Multiple Values 100Change over Time and Utilization Rates 101Hierarchical Data 101Other Shapes 102Summary 103CHAPTER 7 MAPS 105Using Maps to Gain Insights 105Geographic Maps 105Choropleth Maps 106Hex-Tile Maps 109Symbol/Dot-Density Maps 110Proportional Symbol Maps 112When Not to Use a Map 113Summary 114CHAPTER 8 GRAPHS AND CHARTS TO NEVER USE OR USE WITH CAUTION 115When “Cool Displays” Are Anything But 115Pie and Donut Charts 117Why People Use Them 117Characteristics 118Challenges 118Best Practice Alternative 119Multiples of Several-Part Stacked Bar Charts (MSPSBCs) 121Why People Use Them 121Characteristics 121Challenges 121Best Practice Alternative 124Bubble Charts 124Why People Use Them 124Characteristics 125Challenges 125Best Practice Alternative 126Treemaps 128Why People Use Them 128Characteristics 129Challenges 129Best Practice Alternative 130Marimekko (Mekko or Mosaic) Charts 132Why People Use Them 132Characteristics 132Challenges 134Best Practice Alternative 134Radial Bar and Petal Charts 134Why People Use Them 134Characteristics 135Challenges 135Best Practice Alternative 136Radar Charts 138Why People Use Them 138Characteristics 138Challenges 138Best Practice Alternative 139Sankey Diagrams 141Why People Use Them 141Characteristics 141Challenges 142Best Practice Alternative 144One More Thing: 3-D 145Summary 146CHAPTER 9 MAKING ACCESSIBLE VISUALIZATIONS 149Accessible Design is Good Design 149Accessibility in Data Visualization 150Ways to Make Accessible Data Visualizations 151Summary 158SECTION III CREATING COMPELLING DATA DISPLAYS 159CHAPTER 10 DASHBOARDS, REPORTS, AND MULTIDIMENSIONAL EXPLORATORY DISPLAYS (MEDS™) 161Definitions Matter 161Dashboards 162Dashboards Defined 162Purpose/Objective 162Data/Information 163Design 164Example Dashboards 165Dashboard Summary 169Reports 170Reports Defined 170Purpose/Objective 170Design 170Example Reports 171Report Summary 176Multidimensional Exploratory Displays (MEDs™) 176MEDs™ Defined 177Purpose/Objective 177Design 177Example MED™ 177MEDs™ Summary 184Summary 184CHAPTER 11 INFOGRAPHICS 185"No Tobacco Day" Infographic 186Measles and Vaccinations Infographic 188Infographic vs. Infoposter 191Summary 194SECTION IV CLOSING THOUGHTS AND RECOMMENDED READING AND RESOURCES 195Closing Thoughts 197Fluency and Mastery 197Bitten by the Viz Bug | Recommended Reading and Resources 199Recommended Reading 199Resources 201Accessibility Resources 202Author Bios 203References 207Index 211
Advanced ASP.NET Core 3 Security
Incorporate security best practices into ASP.NET Core. This book covers security-related features available within the framework, explains where these feature may fall short, and delves into security topics rarely covered elsewhere. Get ready to dive deep into ASP.NET Core 3.1 source code, clarifying how particular features work and addressing how to fix problems.For straightforward use cases, the ASP.NET Core framework does a good job in preventing certain types of attacks from happening. But for some types of attacks, or situations that are not straightforward, there is very little guidance available on how to safely implement solutions. And worse, there is a lot of bad advice online on how to implement functionality, be it encrypting unsafely hard-coded parameters that need to be generated at runtime, or articles which advocate for certain solutions that are vulnerable to obvious injection attacks. Even more concerning is the functions in ASP.NET Core that are not as secure as they should be by default.ADVANCED ASP.NET CORE 3 SECURITY is designed to train developers to avoid these problems. Unlike the vast majority of security books that are targeted to network administrators, system administrators, or managers, this book is targeted specifically to ASP.NET developers. Author Scott Norberg begins by teaching developers how ASP.NET Core works behind the scenes by going directly into the framework's source code. Then he talks about how various attacks are performed using the very tools that penetration testers would use to hack into an application. He shows developers how to prevent these attacks. Finally, he covers the concepts developers need to know to do some testing on their own, without the help of a security professional.WHAT YOU WILL LEARN* Discern which attacks are easy to prevent, and which are more challenging, in the framework* Dig into ASP.NET Core 3.1 source code to understand how the security services work* Establish a baseline for understanding how to design more secure software* Properly apply cryptography in software development* Take a deep dive into web security concepts* Validate input in a way that allows legitimate traffic but blocks malicious traffic * Understand parameterized queries and why they are so important to ASP.NET Core* Fix issues in a well-implemented solution * Know how the new logging system in ASP.NET Core falls short of security needs* Incorporate security into your software development processWHO THIS BOOK IS FORSoftware developers who have experience creating websites in ASP.NET and want to know how to make their websites secure from hackers and security professionals who work with a development team that uses ASP.NET Core. A basic understanding of web technologies such as HTML, JavaScript, and CSS is assumed, as is knowledge of how to create a website, and how to read and write C#. You do not need knowledge of security concepts, even those that are often covered in ASP.NET Core documentation.SCOTT NORBERG is a web security specialist with almost 15 years of experience in various technology and programming roles, focusing on developing and securing websites built with ASP.NET. As a security consultant, he specializes on blue team (defensive) techniques such as Dynamic Application Security Testing (DAST), code reviews, and manual penetration testing. He also has an interest in building plug-and-play software libraries that developers can use to secure their sites with little-to-no extra effort. As a developer, Scott has primarily built websites with C# and various versions of ASP.NET, and he has also built several tools and components using F#, VB.NET, Python, R, Java, and Pascal.Scott holds several certifications, including Microsoft Certified Technology Specialist (MCTS), certifications for ASP.NET and SQL Server, and a Certified Information Systems Security Professional (CISSP) certification. He also has an MBA from Indiana University.Scott is currently working as a contractor and consultant through his business, Norberg Consulting Group, LLC. You can see his latest ideas and projects at scottnorberg.com.CHAPTER 1 – INTRODUCING ASP.NET CORECHAPTER 2 – GENERAL SECURITY CONCEPTSCHAPTER 3 – CRYPTOGRAPHYCHAPTER 4 – WEB SECURITY CONCEPTSCHAPTER 5 – UNDERSTANDING COMMON ATTACKSCHAPTER 6 – PROCESSING USER INPUTCHAPTER 7 – AUTHENTICATION AND AUTHORIZATIONCHAPTER 8 – DATA ACCESS AND STORAGECHAPTER 9 - LOGGING AND ERROR HANDLINGCHAPTER 10 – SETUP AND CONFIGURATIONCHAPTER 11 – SECURE APPLICATION LIFECYCLE MANAGEMENT
Foundation Dynamic Web Pages with Python
Discover the concepts of creating dynamic web pages (HTML) with Python. This book reviews several methods available to serve up dynamic HTML including CGI, SSI, Django, and Flask.You will start by covering HTML pages and CSS in general and then move on to creating pages via CGI. It is easy to use and can serve as a foundation for the more advanced services available for launching dynamic web pages. Next you'll explore the SSI (Server Side Interface) method. This is a slightly more advanced interface included in mots web servers that adds functionality to modify static HTML pages to add such things as the current date or time, include additional HTML, and other features to a static web page before it is delivered to the user.The book also covers some of the key the Django module features, which must be added to the web server. These features include creating dynamic web pages and calling a database to provide additional information to the web page. Lastly you will explore the Flask module. While it has limited functionality on its own, it provides a very flexible environment to create a self designed system for delivery of dynamic web pages.By the time you finish this book, you will be able to choose the appropriate methodology for delivering dynamic information using fast HTML creation services.WHAT YOU'LL LEARN* Use HTML pages and CSS together to control the style of your web site.* Install and configure SSI, Django, and Flask for Apache.* Create dynamic web pages using CGI and creating a library of partial HTML pages to use in this task.* Build dynamic web pages using SSI and auxiliary Python programs to enhance the SSI functionality.* Develop dynamic web pages using Django.WHO THIS BOOK IS FORSoftware Developers with basic Python programming skills interested in learning Web DevelopmentW. David Ashley is a technical writer for SkillSoft where he specializes in open source, particularly Linux. As a member of the Linux Fedora documentation team he recently led the Libvert project documentation, and wrote the Python programs included with it. He has developed in 20 different programming languages during his 30 years as a software developer and IT consultant, including more than 18 years at IBM and 12 years with American Airlines. Chapter 1: Introduction to Web ServersChapter Goal: An introduction to web servers – specifically the Apache web server.No. of Pages: 5Sub-Topics:Glossary of termsIntroduction to the Apache web serverIntroduction to other web serversConfiguring your web serverOrganizing your web serverChapter 2: HTML Pages and CSSChapter Goal: Describes the main principles of web pages and style sheetsNo. of Pages: 20Sub-Topics:HTML tagsOrganizing HTML sectionsLinking HTML pages to a style sheetCreating a library of partial HTML pagesEnsuring coordination between the HTML page, the CSS stylesheet, and you libraryChapter 3: Using CGI and PythonChapter Goal: Using Python to create an HTML pageNo. of Pages: 25Sub-Topics:Configure CGI for use by PythonCreate a dummy page just for creating the layout of the page major elementsHTML sectionsUsing Python to create a dynamic HTML pageWhere to split a web page into multiple partsTechniques for managing the web page for use by PythonThe good and the bad of using CGIChapter 4: Using SSI and PythonChapter Goal: Configure Apache for use by SSI and PythonNo. of Pages: 45Sub-Topics:Configure SSI for use by PythonCreate a dummy page just for creating the layout of the page major elementsHTML sectionsUsing SSI and Python to create a dynamic HTML pageWhere to split a web page into multiple partsTechniques for managing the web page for use by SSI and PythonThe good and the bad of using SSIChapter 5: Using Django and PythonChapter Goal: Using Django and Python to create an HTML pageNo. of Pages: 40Sub-Topics:Configure Apache for use by Django and PythonCreate a dummy page just for creating the layout of the page major elementsHTML sectionsUsing Django and Python to create a dynamic HTML pageWhere to split a web page into multiple partsTechniques for managing the web page for use by Django and PythonThe good and the bad of using DjangoChapter 6: Using Flask and JinjaChapter Goal: Using Flask and Python to create an HTML pageNo. of Pages: 40Sub-Topics:Configure Apache for use by Flask and PythonCreate a dummy page just for creating the layout of the page major elementsHTML sectionsUsing Flask and Python to create a dynamic HTML pageWhere to split a web page into multiple partsTechniques for managing the web page for use by Flask and PythonThe good and the bad of using FlaskChapter 7: Comparing CGI, SSI, Django, and Flask Chapter Goal: Choosing the correct dynamic page creation systemNo. of Pages: 50Sub-Topics:List the advantages of each systemList the disadvantages of each systemChapter 8: Usage Options - CGI, SSI, Django, and FlaskChapter Goal: Choosing the correct dynamic page creation systemNo. of Pages: 50Sub-Topics:Discuss options for using multiple systemsSome things to remember
Cybersecurity in Humanities and Social Sciences
The humanities and social sciences are interested in the cybersecurity object since its emergence in the security debates, at the beginning of the 2000s. This scientific production is thus still relatively young, but diversified, mobilizing at the same time political science, international relations, sociology , law, information science, security studies, surveillance studies, strategic studies, polemology. There is, however, no actual cybersecurity studies. After two decades of scientific production on this subject, we thought it essential to take stock of the research methods that could be mobilized, imagined and invented by the researchers. The research methodology on the subject "cybersecurity" has, paradoxically, been the subject of relatively few publications to date. This dimension is essential. It is the initial phase by which any researcher, seasoned or young doctoral student, must pass, to define his subject of study, delimit the contours, ask the research questions, and choose the methods of treatment. It is this methodological dimension that our book proposes to treat. The questions the authors were asked to answer were: how can cybersecurity be defined? What disciplines in the humanities and social sciences are studying, and how, cybersecurity? What is the place of pluralism or interdisciplinarity? How are the research topics chosen, the questions defined? How, concretely, to study cybersecurity: tools, methods, theories, organization of research, research fields, data ...? How are discipline-specific theories useful for understanding and studying cybersecurity? Has cybersecurity had an impact on scientific theories? Hartmut Aden, Prof. University of Berlin Hugo Loiseau, Prof. University of Sherbrooke Daniel Ventre, CNRS, researcher at CESDIPIntroduction ixDaniel VENTRE, Hugo LOISEAU and Hartmut ADENCHAPTER 1 THE “SCIENCE” OF CYBERSECURITY IN THE HUMAN AND SOCIAL SCIENCES: ISSUES AND REFLECTIONS 1Hugo LOISEAU1.1 Introduction 11.2 A method? 41.3 Data? 111.4 One or more definition(s)? 161.5 Conclusion 201.6 References 21CHAPTER 2 DEFINITIONS, TYPOLOGIES, TAXONOMIES AND ONTOLOGIES OF CYBERSECURITY 25Daniel VENTRE2.1 Introduction 252.2 Definition 272.2.1 What is a definition? 272.2.2 Usefulness of definitions 292.2.3 Rules for constructing definitions 292.2.4 Definitions of cybersecurity 322.3 Typology 432.3.1 What is a typology? 442.3.2 Usefulness of typologies 442.3.3 Rules for the construction of typologies 452.3.4 Cybersecurity typologies 462.4 Taxonomy 482.4.1 What is a taxonomy? 482.4.2 Usefulness of taxonomy 492.4.3 Rules for the construction of taxonomies 492.4.4 Taxonomies of cybersecurity 502.5 Ontologies 512.5.1 What is ontology? 522.5.2 Usefulness of ontologies 532.5.3 Rules for construction of ontologies 532.5.4 Cybersecurity ontologies 542.6 Conclusion 562.7 References 57CHAPTER 3 CYBERSECURITY AND DATA PROTECTION – RESEARCH STRATEGIES AND LIMITATIONS IN A LEGAL AND PUBLIC POLICY PERSPECTIVE 67Hartmut ADEN3.1 Introduction 673.2 Studying the complex relationship between cybersecurity and data protection: endangering privacy by combating cybercrime? 683.2.1 Potential tensions between cybersecurity and data protection 693.2.2 Potential synergies between cybersecurity and data protection 723.3 Methodological approaches and challenges for the study of cybersecurity – legal and public policy perspectives 743.3.1 Legal interpretation and comparison as methodological approaches to the study of cybersecurity 743.3.2 Public policy approaches to the study of cybersecurity 773.3.3 Transdisciplinary synergies between legal and public policy perspectives 783.4 Conclusion and outlook 803.5 References 81CHAPTER 4 RESEARCHING STATE-SPONSORED CYBER-ESPIONAGE 85Joseph FITSANAKIS4.1 Defining cybersecurity and cyber-espionage 854.2 Taxonomies of cyber-threats 874.3 The structure of this chapter 884.4 The significance of state-sponsored cyber-espionage 904.5 Research themes in state-sponsored cyber-espionage 944.6 Theorizing state-sponsored cyber-espionage in the social sciences 984.7 Research methodologies into state-sponsored cyber-espionage 1044.8 Intellectual precision and objectivity in state-sponsored cyber-espionage research 1064.9 Detecting state actors in cyber-espionage research 1104.10 Identifying specific state actors in cyber-espionage research 1124.11 Conclusion: researching a transformational subject 1164.12 References 118CHAPTER 5 MOVING FROM UNCERTAINTY TO RISK: THE CASE OF CYBER RISK 123Michel DACOROGNA and Marie KRATZ5.1 Introduction 1235.2 The scientific approach to move from uncertainty to risk 1245.3 Learning about the data: the exploratory phase 1265.4 Data cleansing 1285.5 Statistical exploration on the various variables of the dataset 1305.6 Univariate modeling for the relevant variables 1345.7 Multivariate and dynamic modeling 1395.7.1 A fast-changing environment: time dependency 1405.7.2 Causal relations 1435.7.3 Models for prediction 1475.8 Conclusion 1495.9 Acknowledgments 1515.10 References 151CHAPTER 6 QUALITATIVE DOCUMENT ANALYSIS FOR CYBERSECURITY AND INFORMATION WARFARE RESEARCH 153Brett VAN NIEKERK and Trishana RAMLUCKAN6.1 Introduction 1536.1.1 Previous research 1546.2 Information warfare and cybersecurity 1546.3 Researching information warfare and cybersecurity 1566.4 Qualitative research methodologies for information warfare and cybersecurity 1576.4.1 Clustering of documents 1596.4.2 Clustering of words 1596.4.3 Word frequencies and word clouds 1596.4.4 Text search and word trees 1596.4.5 Example use cases of qualitative document analysis 1606.5 An analysis of national cybersecurity strategies 1616.5.1 Selection process for the documents 1616.5.2 Analysis 1626.5.3 Discussion 1676.6 An analysis of the alignment of South Africa’s Cybercrimes Bill to international legislation 1696.6.1 Background to the documents 1696.6.2 Analysis 1706.6.3 Discussion 1746.7 An analysis of the influence of classical military philosophy on seminal information warfare texts 1766.8 Reflections on qualitative document analysis for information warfare and cybersecurity research 1776.9 Conclusion 1796.10 References 180CHAPTER 7 ANTI-FEMINIST CYBER-VIOLENCE AS A RISK FACTOR: ANALYSIS OF CYBERSECURITY ISSUES FOR FEMINIST ACTIVISTS IN FRANCE 185Elena WALDISPUEHL7.1 Introduction 1857.2 Localization of an online field 1877.2.1 Online ethnographic work and empathy 1927.2.2 Cybersecurity issues of an online field 1937.3 Online–offline continuum 1947.4 Continuum between security and insecurity 1997.5 Conclusion 2047.6 References 205List of Authors 211Index 213
Data Lake Analytics on Microsoft Azure
Get a 360-degree view of how the journey of data analytics solutions has evolved from monolithic data stores and enterprise data warehouses to data lakes and modern data warehouses. You willThis book includes comprehensive coverage of how:* To architect data lake analytics solutions by choosing suitable technologies available on Microsoft Azure* The advent of microservices applications covering ecommerce or modern solutions built on IoT and how real-time streaming data has completely disrupted this ecosystem* These data analytics solutions have been transformed from solely understanding the trends from historical data to building predictions by infusing machine learning technologies into the solutionsData platform professionals who have been working on relational data stores, non-relational data stores, and big data technologies will find the content in this book useful. The book also can help you start your journey into the data engineer world as it provides an overview of advanced data analytics and touches on data science concepts and various artificial intelligence and machine learning technologies available on Microsoft Azure.WHAT WILL YOU LEARNYou will understand the:* Concepts of data lake analytics, the modern data warehouse, and advanced data analytics* Architecture patterns of the modern data warehouse and advanced data analytics solutions* Phases—such as Data Ingestion, Store, Prep and Train, and Model and Serve—of data analytics solutions and technology choices available on Azure under each phase* In-depth coverage of real-time and batch mode data analytics solutions architecture* Various managed services available on Azure such as Synapse analytics, event hubs, Stream analytics, CosmosDB, and managed Hadoop services such as Databricks and HDInsightWHO THIS BOOK IS FORData platform professionals, database architects, engineers, and solution architectsHARSH CHAWLA has been working on data platform technologies for last 14 years. He has been in various roles in the Microsoft world for last 12 years, going from CSS to services to technology strategy. He currently works as an Azure specialist with data and AI technologies and helps large IT enterprises build modern data warehouses, advanced analytics, and AI solutions on Microsoft Azure. He has been a community speaker and blogger on data platform technologies.PANKAJ KHATTAR is a seasoned Software Architect with over 14 years of experience in design and development of Big Data, Machine Learning and AI based products. He currently works with Microsoft on the Azure platform as a Sr. Cloud Solution Architect for Data & AI technologies. He also possesses extensive industry experience in the field of building scalable multi-tier distributed applications and client/server based development.You can connect with him on LinkedIn at https://www.linkedin.com/in/pankaj-khattar/CHAPTER 1: INTRODUCTION AND THE NEED OF DATA LAKECHAPTER GOAL: The chapter introduces the readers to the concept & need of a data lake in this big data environment.The chapter also covers how to create a data lake & architecture patterns to be followed for data lake analytics.NO OF PAGES 15SUB -TOPICS1. Relational and non-relation data stores2. Base for data: relational and non-relational databases3. Warehouses of data: data warehouses4. Markets for data: data marts5. Introduction to data lake6. Need to create a data lakeCHAPTER 2: DATA JUST GOT BIGGERCHAPTER GOAL: Today, enterprises have mix of relational and non-relational stores. However, when it comes to analyzing all this data – there must be a neutral platform which can understand these types of data. This introduces us to modern world concepts of distributed data storage & processing. It also talks about data sciences & machine learning concepts & how they are revolutionizing the data analysis world.NO OF PAGES : 20Sub - Topics:1. Massively parallel processing, distributed data and spark the Hadoop2. Distributed systems vs massively parallel processing systems (MPP)3. Respective use cases for distributed and MPP systems4. Science for data5. Learning of machines6. Overview of data analytics and advanced data analyticsCHAPTER 3: EMERGENCE OF CLOUD LAKESCHAPTER GOAL: The chapter enlighten the users with multiple cloud-based technologies available which are scalable, agile and performance in terms of computation, storage & analytics options. It goes into details about the suggested architecture on Microsoft Azure to solve Modern data warehouse, analytics use cases.NO OF PAGES: 20SUB - TOPICS:1. Data travels to Cloud with added benefits2. Overview of phases of data analytics architecture3. Available products under each phase on Microsoft AzureCHAPTER 4: PHASES IN MANAGING DATA ANALYTICS PIPELINECHAPTER GOAL: This chapter covers in-depth context of this book. After we understand the background, this chapter will provide understanding of what are the phases of building entire data analytics pipeline. All the phases discussed in this book are critical to understand and any analytics solution will adhere to this common principle some way or the other. In each phase, there are different solutions to cater respective issues.It covers the data life cycle from upstream to downstream applications.NO OF PAGES: 20SUB - TOPICS:1. Real time and batch mode data processing2. Phases in data Management· Ingest· Store· Analytics· Visualization3. Cloud data lake architecture patternsCHAPTER 5: DATA INGESTION IN THE LAKEChapter Goal: The chapter talks about the limitations about the traditional storage & how the big data technologies has emerged as the champion in solving the limitations & changing the concepts of Extract, Transform & Load (ETL) to Extract, Load & Transform(ELT).NO OF PAGES: 20SUB - TOPICS:1. Traditional limitations, can big data help?2. ETL now becomes ELT3. Tools in cloud for data ingestion· Azure Data Factory on Microsoft Azure· SQL server integration services on-premise4. Overview of partner solutions for ETL/ELT – Informatica PowerEdgeCHAPTER 6: DATA STORAGE & FARMINGCHAPTER GOAL: The chapter shares with readers that how once the data is available in storage layers, how it can be grown & real time data storage & analysis needs can be catered, it also talks about batch & real time data processing & storage.No of pages: 20SUB - TOPICS:1. Grow the data2. Role of Azure data lake store, Blob, relational and non-relational stores3. Architecting the Lambda & Kappa4. Manage storage for real time and batch processingCHAPTER 7: ANALYZING THE BIGGER DATA IN REAL TIMECHAPTER GOAL: Analysis of data is crucial for enterprises to get the business insights from the historic, present & future data to make descriptive, streaming & predictive analytics. In this chapter, we will specifically talk about real time analytics. Components required to perform real time analytics and how to optimize the cost using Azure PaaS solutions.NO OF PAGES: 30SUB - TOPICS:1. Need of real time analytics2. Approach to build data analytics on data lake for real time processing3. Leverage event hubs/IOT hubs as a queuing solution on Azure4. Why Edge computing and digital twins are gaining limelight5. Choice between PaaS vs IaaS solution for streaming data processing6. PaaS – stream analytics or spark streaming7. Infuse R and Python on real-time data analytics pipelines8. Use cases for real time analyticsCHAPTER 8: ANALYZING THE BIGGER DATA IN BATCH MODECHAPTER GOAL: Analysis of data is crucial for enterprises to get the business insights from the historic, present & future data to make descriptive, streaming & predictive analytics. Analytics can help companies identify new business opportunities and revenue streams which results in an increase in profits, new customers, and improved customer service.No of pages: 30SUB - TOPICS:9. Role of big data and massively parallel processing systems10. Approach to build data analytics on data lake for batch processing11. Approach to build data analytics solution for real time analytics12. When to leverage HDInsight and Spark clusters13. Infuse R and Python in data analytics pipelines14. How it's different from conventional data warehousing and massively parallel processing solutions15. Use cases for batch mode processingCHAPTER 9: VISUALIZATION AND OTHER DOWNSTREAM CHOICESChapter Goal: Visualization of data is crucial for reporting& also to perform exploratory data analytics. The chapter talks about the visual elements like charts, graphs, and maps, data visualization tools which provide an accessible way to see and understand trends, outliers, and patterns in dataNO OF PAGES: 10SUB - TOPICS:1. Visualizations tools – Power BI2. Downstream applications – LOB applications, notification applications3. Choice of data stores for downstream applications – Cosmos DB, Azure SQL DatabaseCHAPTER 10: SUMMARY OF DATA LAKE COMPONENTS IN AZURECHAPTER GOAL: The chapter takes a dig at multiple azure components which makes its easy to create an enterprise data lake in cloud & talks about in details the usage of eachNo of pages: 20SUB - TOPICS:1. Azure data factory2. Azure data lake storage3. Azure HDInsight4. Azure databricks5. Azure data warehouse6. Azure PowerBICHAPTER 11: CONCLUSIONCHAPTER GOAL: The concluding chapter summarizes the information shared around the data lake in the bookNo of pages: 5
Pro Microsoft Power Platform
Become a self-sufficient citizen developer by learning the tools within the Microsoft Power Platform and how they can be used together to drive change and multiply your productivity. Learn about PowerApps for building applications, Power Automate for automating business processes across those applications, and Power BI for analyzing results and communicating business intelligence through compelling visuals. By understanding the purpose and capabilities of these tools, you will be able to enhance your organization’s visibility into key areas and make informed business decisions in a timely matter.This book is divided into four parts and begins in Part I by showing you how to build applications through PowerApps. You will learn about screens and controls, application sharing and administration, and how to make your applications accessible from mobile devices such as phones and tablets. Part II is about creating workflows using Power Automate that implement business logic across your applications. Part III brings in dashboards and data analysis, showing you how to connect to a data source, cleanse the data from that source, and drive decision making through interactive reports and storytelling. Part IV brings together all the pieces by showing the integrations that are possible when all three tools are combined into a single solution.WHAT YOU WILL LEARN* Understand the need for the citizen developer in today’s business environment* Organize and plan the building of line-of-business applications with PowerApps solutions * Replace wasteful paper processes with automated applications built in PowerApps* Automate workflows across processes with Power Automate* Communicate analytical results through visualizations and storytelling* Integrate PowerApps, Power Automate, and Power BI into solutions that multiply productivityWHO THIS BOOK IS FORPower users and analysts with strong Excel skills who need a more comprehensive set of tools that can better help them accomplish their vision on projects, those familiar with one of the Power Platform tools who wish to learn how all three can fit together, and those who are seen as as “rogue IT” problem solvers who get things done when others have tried but failedMITCHELL PEARSON is a business intelligence consultant and the training content manager for Pragmatic Works. He has authored books on SQL Server and Power BI, and spends his time at Pragmatic Works developing new courses on business intelligence and Microsoft Azure. He has experience developing enterprise-level BI solutions using the full suite of products offered by Microsoft (SSRS, SSIS, SSAS, Power BI, and Azure). He is active in the community, running the local Power BI user group, presenting at SQL Saturday events and at PASS virtual chapters, and in giving free webinars for Pragmatic Works.BRIAN KNIGHT is a Power Apps MVP, founder of Pragmatic Works, and co-founder of SQLServerCentral.com and JumpstartTV.com. He won the CEO of the year award given by the Jacksonville Business Journal, and Pragmatic Works has ranked up on the top growing companies in the country for many years in a row. He runs the local SQL Server user group in Jacksonville (JSSUG), is a contributing columnist for SQL Server Standard, maintains a regular column for the database website SQLServerCentral.com, and does regular webcasts at Jumpstart TV. He has co-authored and authored more than nine SQL Server books. He has spoken at conferences such as PASS, SQL Connections, and TechEd, and at many Code Camps.DEVIN KNIGHT is a Microsoft Data Platform MVP and Vice President of Training at Pragmatic Works. He is an author of eight SQL Server, Power Platform, and BI books. You can find him speaking at conferences such as the Microsoft Business Application Summit, PASS Summit, SQL Saturdays, and Code Camps. He is also a contributing member to several virtual user group chapters. Making his home in Jacksonville, FL, He contributes locally at the Jacksonville Power BI User Group.MANUEL QUINTANA is a training content manager at a Pragmatic Works. Previously, he was a senior manager working in the hotel industry. He joined the Pragmatic Works team in 2014 with no knowledge in the business intelligence space, but now speaks at SQL Saturdays and SQL Server user groups locally and virtually. He also teaches various BI technologies to many Fortune 500 companies on behalf of Pragmatic Works. Since 2014, he has called Jacksonville, Florida home, and before that Orlando, but he was born on the island of Puerto Rico and loves to go back and visit his family. When he is not working on creating new content for Pragmatic Works, you can probably find him playing board games or watching competitive soccer matches.IntroductionPART I. BUILDING LINE OF BUSINESS APPLICATIONS WITH POWERAPPS1. Introduction to PowerApps2. Building Your First PowerApp3. Exploring PowerApps Screens and Controls4. Working with PowerApps Expressions5. Leveraging Variables and Collections6. Securing and Sharing Apps7. Managing Power Apps8. Common Data Services and Model-Driven AppsPART II. TASK AUTOMATION WITH MICROSOFT FLOW9. Introduction to Power Automate10. Building Your First Flow11. Exploring Different Trigger Types12. Working with Flow Expressions13. Building Conditional Flows14. Designing Approval Flows15. Administering Power AutomatePART III. DASHBOARDS, REPORTING, AND ANALYTICS WITH POWER BI16. Introduction to Power BI17. Connecting to Data18. Defining Data Cleansing Business Rules with the Power Query Editor19. Data Model Design20. Extending Your Data Model with DAX Calculations21. Report Writing Basics22. Designing Interactive Reports23. Data Storytelling with Power BI24. Sharing Power BI Solutions25. Administering Power BIPART IV. INTEGRATING THE POWER PLATFORM TOOLS TOGETHER26. Power Platform Integration in PowerApps27. Power Platform Integration in Microsoft Flow28. Power Platform Integration in Power BI29. Designing a Fully Integrated Power Platform Solution
Supervised Learning with Python
Gain a thorough understanding of supervised learning algorithms by developing use cases with Python. You will study supervised learning concepts, Python code, datasets, best practices, resolution of common issues and pitfalls, and practical knowledge of implementing algorithms for structured as well as text and images datasets.You’ll start with an introduction to machine learning, highlighting the differences between supervised, semi-supervised and unsupervised learning. In the following chapters you’ll study regression and classification problems, mathematics behind them, algorithms like Linear Regression, Logistic Regression, Decision Tree, KNN, Naïve Bayes, and advanced algorithms like Random Forest, SVM, Gradient Boosting and Neural Networks. Python implementation is provided for all the algorithms. You’ll conclude with an end-to-end model development process including deployment and maintenance of the model.After reading Supervised Learning with Python you’ll have a broad understanding of supervised learning and its practical implementation, and be able to run the code and extend it in an innovative manner.WHAT YOU'LL LEARN* Review the fundamental building blocks and concepts of supervised learning using Python* Develop supervised learning solutions for structured data as well as text and images * Solve issues around overfitting, feature engineering, data cleansing, and cross-validation for building best fit models* Understand the end-to-end model cycle from business problem definition to model deployment and model maintenance * Avoid the common pitfalls and adhere to best practices while creating a supervised learning model using PythonWHO THIS BOOK IS FORData scientists or data analysts interested in best practices and standards for supervised learning, and using classification algorithms and regression techniques to develop predictive models.VAIBHAV VERDHAN has 12+ years of experience in Data Science, Machine Learning and Artificial Intelligence. An MBA with engineering background, he is a hands-on technical expert with acumen to assimilate and analyse data. He has led multiple engagements in ML and AI across geographies and across retail, telecom, manufacturing, energy and utilities domains. Currently he resides in Ireland with his family and is working as a Principal Data Scientist. Chapter 1: Introduction to Supervised LearningChapter Goal: Start the journey of the readers on supervised learningNo of pages: 30-40Sub -Topics1. Machine learning and how is it different from software engineering?2. Discuss reasons for machine learning being popular3. Compare between supervised, semi-supervised and unsupervised algorithms4. Statistical methods to get significant variables5. The use cases of machine learning and respective use cases for each of supervised, semi-supervised and unsupervised algorithmsChapter 2: Supervised Learning for Regression AnalysisChapter Goal: Embrace the core concepts of supervised learning to predict continuous variablesNo of pages: 40-50Sub - Topics1. Supervised learning algorithms for predicting continuous variables2. Explain mathematics behind the algorithms3. Develop Python solution using linear regression, decision tree, random forest, SVM and neural network4. Measure the performance of the algorithms using r square, RMSE etc.5. Compare and contrast the performance of all the algorithms6. Discuss the best practices and the common issues faced like data cleaning, null values etc.Chapter 3: Supervised Learning for Classification ProblemsChapter Goal: Discuss the concepts of supervised learning for solving classification problemsNo of pages : 30-40Sub - Topics:1. Discuss classification problems for supervised learning2. Examine logistic regression, decision tree, random forest, knn and naïve Bayes. Understand the statistics and mathematics behind each3. Discuss ROC curve, akike value, confusion matrix, precision/recall etc4. Compare the performance of all the algorithms5. Discuss the tips and tricks, best practices and common pitfalls like a bias-variance tradeoff, data imbalance etc.Chapter 4: Supervised Learning for Classification Problems-AdvancedChapter Goal: cover advanced classification algorithms for supervised learning algorithmsNo of pages:30-40Sub - Topics:1. Refresh classification problems for supervised learning2. Examine gradient boosting and extreme gradient boosting, support vector machine and neural network3. Compare the performance of all the algorithms4. Discuss the best practices and common pitfalls, tips and tricksChapter 5: End-to-End Model DeploymentChapter Goal: guide the reader on the end-to-end process of deploying a supervised learning model in productionNo of pages:25-301. Meaning of model deployment2. Various steps in the model deployment process3. Preparations to be made like settings, environment etc.4. Various use cases in the deployment5. Practical tips in model deployment
Modern Arm Assembly Language Programming
Gain the fundamentals of Armv8-A 32-bit and 64-bit assembly language programming. This book emphasizes Armv8-A assembly language topics that are relevant to modern software development. It is designed to help you quickly understand Armv8-A assembly language programming and the computational resources of Arm’s SIMD platform. It also contains an abundance of source code that is structured to accelerate learning and comprehension of essential Armv8-A assembly language constructs and SIMD programming concepts. After reading this book, you will be able to code performance-optimized functions and algorithms using Armv8- A 32-bit and 64-bit assembly language.Modern Arm Assembly Language Programming accentuates the coding of Armv8-A 32-bit and 64-bit assembly language functions that are callable from C++. Multiple chapters are also devoted to Armv8-A SIMD assembly language programming. These chapters discuss how to code functions that are used in computationally intense applications such as machine learning, image processing, audio and video encoding, and computer graphics.The source code examples were developed using the GNU toolchain (g++, gas, and make) and tested on a Raspberry Pi 4 Model B running Raspbian (32-bit) and Ubuntu Server (64-bit). It is important to note that this is a book about Armv8-A assembly language programming and not the Raspberry Pi.What You Will Learn* See essential details about the Armv8-A 32-bit and 64-bit architectures including data types, general purpose registers, floating-point and SIMD registers, and addressing modesUse the Armv8-A 32-bit and 64-bit instruction sets to create performance-enhancing functions that are callable from C++ * Employ Armv8-A assembly language to efficiently manipulate common data types and programming constructs including integers, arrays, matrices, and user-defined structures* Create assembly language functions that perform scalar floating-point arithmetic using the Armv8-A 32-bit and 64-bit instruction sets* Harness the Armv8-A SIMD instruction sets to significantly accelerate the performance of computationally intense algorithms in applications such as machine learning, image processing, computer graphics, mathematics, and statistics.* Apply leading-edge coding strategies and techniques to optimally exploit the Armv8-A 32-bit and 64-bit instruction sets for maximum possible performance WHO THIS BOOK IS FORSoftware developers who are creating programs for Armv8-A platforms and want to learn how to code performance-enhancing algorithms and functions using the Armv8-A 32-bit and 64-bit instruction sets. Readers should have previous high-level language programming experience and a basic understanding of C++.Daniel Kusswurm has over 35 years of professional experience as a software developer and computer scientist. During his career, he has developed innovative software for medical devices, scientific instruments, and image processing applications. On many of these projects, he successfully employed assembly language to significantly improve the performance of computationally intense algorithms or solve unique programming challenges. His educational background includes a BS in electrical engineering technology from Northern Illinois University along with an MS and PhD in computer science from DePaul University. Daniel Kusswurm is also the author of Modern X86 Assembly Language Programming (ISBN-13: 978-1484200650) and Modern X86 Assembly Language Programming, Second Edition (ISBN-13: 978-1484240625), both published by Apress.Modern Arm Assembly Language ProgrammingF:\ModArmAsm\Chapters\Outline\ModernArmAsm_Outline (V2).docx Page 1 of 6Daniel KusswurmIntroductionBook overviewTarget audienceContent overviewSource codeTerminology and conventionsAdditional resourcesChapter 1 – Armv8-32 ArchitectureArmv8-32 OverviewData typesFundamental data typesNumerical data typesSIMD data typesInternal architectureGeneral-purpose register fileApplication Program Status Register (APSR)Instruction set overviewInstruction operandsMemory addressing modesChapter 2 – Armv8-32 Core Programming – Part 1Integer arithmeticAddition and subtraction (Ch02_01)Multiplication (Ch02_02)Division (Ch02_03)Integer operationsLoad instructions (Ch02_04)Move instructions (Ch02_05, Ch02_06)Logical operations (Ch02_07)Chapter 3 – Armv8-32 Core Programming – Part 2Basic stack argumentsStack arguments (Ch03_01)Stack arguments using mixed data types (Ch03_02)Advanced stack useModern Arm Assembly Language ProgrammingF:\ModArmAsm\Chapters\Outline\ModernArmAsm_Outline (V2).docx Page 2 of 6Daniel KusswurmStack use with local storage (Ch03_03)Stack use with frame pointer (Ch03_04)Using the APSR condition flagsCompare instructions (Ch03_05)Looping (Ch03_06)Chapter 4 – Armv8-32 Core Programming – Part 3Integer arraysArray arithmetic (Ch04_01)Array arithmetic using mixed-type integers (Ch04_02)Integer matricesMatrix example #1 (Ch04_03)Matrix example #2 (Ch04_04)Advanced programmingAdvanced array operations (Ch04_05)Structures (Ch04_06)Chapter 5 – Armv8-32 Floating-Point ArchitectureFloating-point programming conceptsBinary encodingsNaNsDenormalsFlush to zeroFloating-point registersSingle-precision registersDouble-precision registersFPSCR (floating-point status and control register)Rounding modesExceptionsChapter 6 – Armv8-32 Floating-Point ProgrammingFloating-point arithmeticFP arithmetic example #1 (Ch06_01)FP arithmetic example #2 (Ch06_02)FP arithmetic example #3 (Ch06_03)Floating-point compares and conversionsFP compares (Ch06_04)FP conversions (Ch06_05)Floating-point arrays and matricesModern Arm Assembly Language ProgrammingF:\ModArmAsm\Chapters\Outline\ModernArmAsm_Outline (V2).docx Page 3 of 6Daniel KusswurmFP arrays (Ch06_06)FP matrices (Ch06_07)Advanced floating-point programmingUsing C++ floating-point library functions (Ch06_08)Chapter 7 – Armv8-32 SIMD ArchitectureArmv8-32 SIMD Architecture OverviewSIMD programming conceptsWraparound and saturated arithmeticSIMD architectureRegister setsData typesSIMD arithmetic operationsPacked integer arithmeticPacked floating-point arithmeticChapter 8 – Armv8-32 SIMD Integer ProgrammingPacked integer arithmeticAddition and subtraction (Ch08_01)Multiplication (Ch08_02)Shift and logical operations (Ch08_03)Packed integer image processingPixel minimum and maximum (Ch08_04)Mean intensity (Ch08_05)Image thresholding (Ch08_06)Chapter 9 – Armv8-32 SIMD Floating-Point ProgrammingPacked floating-point arithmeticAddition, subtraction, multiplication, division (Ch09_01)Compares (Ch09_02)Conversions (Ch09_03)Packed floating-point arraysMinimum and maximum (Ch09_04)Least squares (Ch09_05)Packed floating-point matrices4x4 matrix transposition (Ch09_06)4x4 matrix multiplication (Ch09_07)Modern Arm Assembly Language ProgrammingF:\ModArmAsm\Chapters\Outline\ModernArmAsm_Outline (V2).docx Page 4 of 6Daniel KusswurmChapter 10 – Armv8-64 ArchitectureArmv8-64 OverviewData typesNumerical data typesSIMD data typesInternal architectureGeneral-purpose register fileFloating-point and SIMD registersStatus flags and condition codesInstruction set overviewOperandsMemory addressing modesChapter 11 – Armv8-64 Core Programming – Part 1Integer arithmeticAddition & subtraction (Ch11_01)Multiplication (Ch11_02)Division (Ch11_03)Integer operationsLoad and store instructions (Ch11_04)Move instructions (Ch11_05)Logical instructions (Ch11_06)Shift instructions (Ch11_07)Chapter 12 – Armv8-64 Core Programming – Part2Stack arguments and local storageStack arguments using mixed data types (Ch12_01)Stack arguments with local storage (Ch12_02)Using condition codesCompare instructions (Ch12_03)Looping (Ch12_04)Integer arrays and matricesArray programming example (Ch12_05)Matrix programming example (Ch12_06)Chapter 13 – Armv8-64 Floating-Point ProgrammingFloating-point arithmeticSingle-precision arithmetic (Ch13_01)Modern Arm Assembly Language ProgrammingF:\ModArmAsm\Chapters\Outline\ModernArmAsm_Outline (V2).docx Page 5 of 6Daniel KusswurmDouble-precision arithmetic example #1 (Ch13_02)Double-precision arithmetic example #2 (Ch13_03)Floating-point compares and conversionsCompare instructions (Ch13_04)Conversion instructions (Ch13_05)Floating-point arrays and matricesArray programming example (Ch13_06)Matrix programming example (Ch13_07)Advanced floating-point programmingUsing C++ floating-point library functions (Ch13_08)Chapter 14 – Armv8-64 SIMD Integer ProgrammingPacked integer arithmeticAddition and subtraction (Ch14_01)Shift operations (Ch14_02)Multiplication (Ch14_03)Packed integer image processingPixel min/max (Ch14_04)Gray-scale pixel clipping (Ch14_05)Image statistics (Ch14_06)Chapter 15 – Armv8-64 SIMD Floating-Point ProgrammingPacked floating-point arithmeticAddition subtraction, multiplication, division (Ch15_01)Compares (Ch15_02)Conversions (Ch15_03)Packed floating-point arraysCorrelation coefficient (Ch15_04)Image conversion – RGB to grayscale (Ch15_05)Packed floating-point matrices4x4 matrix multiplication (Ch15_06)4x4 matrix-vector multiplication (Ch15_07)Chapter 16 – Armv8-64 Advanced SIMD ProgrammingArmv8 microarchitecture overviewOptimization guidelinesSignal processingFMA convolution (Ch16_01)Modern Arm Assembly Language ProgrammingF:\ModArmAsm\Chapters\Outline\ModernArmAsm_Outline (V2).docx Page 6 of 6Daniel KusswurmVector and matrix operationsVector cross products (Ch16_02)Matrix-vector products (Ch16_03)Matrix inversion (Ch16_04)Appendix A – Source Code and Software Development ToolsSource codeHardware platformHost operating systemsSetup and configurationSoftware toolsg++gasmakeBuilding and executing the source code projectsAppendix B – References and Additional ResourcesArmv8 programming referencesAlgorithm referencesSoftware development resourcesAdditional resources
Modern CSS
Come on a tour of “modern” CSS in 2020. This example-driven book demonstrates the concepts by showing code examples, screenshots, and diagrams to help clearly communicate the information.You'll start with the very basics of CSS: box model, colors, selectors and combinators, and specificity. Then gradually move through more intermediate topics - styling text, positioning, Z-index and stacking contexts, gradients, borders, and then to more advanced topics such as transforms, transitions, animations, flexbox, and CSS grid. Some features are only available in modern browsers (Chrome, Edge, Safari, and Firefox), but information about IE11 compatibility is included where possible.There is a lot of discussion about how hard CSS is, and how intimidated some people are by it, but it doesn’t have to be this way. Modern CSS uses a logical and understandable approach to break down and clearly explain the ins and outs of CSS.WHAT YOU'LL LEARN* Work with the syntax of CSS selectors and calculate specificity* Use styling techniques, fonts and text styling* Review custom properties (variables)* Explore the different ways an element can be transformed* Use animating elements with CSS transitions * Position elements using Flexbox layout* Understand the basics of responsive designWHO THIS BOOK IS FORAnyone who has some experience with HTML, and some CSS, but might not be familiar with some of the newer concepts like flexbox or grid. Also, those looking for a refresher in those areas.JOE ATTARDI is a software engineer specializing in front-end development. He has over 15 years’ experience working with JavaScript, HTML, and CSS, and has worked extensively with front-end technologies such as Angular and React. He currently works at Salesforce, and has worked in the past with companies such as Dell and Nortel. He is also the author of Using Gatsby and Netlify CMS (Apress, 2020). He lives in the Boston area with his wife and son. You can find him on Twitter at @JoeAttardi.1. Introduction to CSS2. CSS Selectors3. Basic CSS Concepts4. Basic Styling5. Backgrounds and Gradients6. Text Styling7. Layout and Positioning8. Transforms9. Transitions and Animations10. Flexbox11. Responsive Design12. CSS Grid13. Wrap-up
Using Gatsby and Netlify CMS
Leverage the powerful new combination of Gatsby and Netlify CMS, a free open source content management solution, to build blazing fast apps. This book shows you how to create a React-powered website using the Gatsby framework for the frontend, and Netlify CMS as the content backend.Through the course of the book you'll gradually build a website for a coffee shop that includes a blog and a bakery/coffee menu that is customizable through Netlify CMS. The project starts with a bare-bones Gatsby site to which you'll add functionality such as setting up/configuring the CMS, creating different types of content, and writing some Gatsby glue code to consume the Markdown data via plugins. When done, you'll be well-equipped to build on your existing JavaScript and React knowledge to effectively use Gatsby and Netlify CMS for yourself or your clients.Using Gatsby and Netlify CMS is an ideal guide for anyone looking to build their own sites and manage their own content without having to deal with creating Markdown files or Git repositories.WHAT YOU'LL LEARN* Clone repositories, install dependencies and deploy on Netlify* Configure Netlify Identity and Git Gateway* Use Netlify CMS Content Manager* Source blog data using Gatsby plugin* Manage dynamic page reactions using Gatsby Node APIs* Work with pagination, content and menus* Customize Netlify CMSWHO THIS BOOK IS FORExperienced JavaScript developers with a good handle on React who want to learn how to build a maintainable Gatsby powered site. Basic familiarity with Gatsby is assumed but not required.JOE ATTARDI is a software engineer specializing in front-end development. He has over 15 years’ experience working with JavaScript, HTML, and CSS, and has worked extensively with front-end technologies such as Angular and React. He currently works at Salesforce, and has worked in the past with companies such as Dell and Nortel. He is also the author of Modern CSS (Apress, 2020). He lives in the Boston area with his wife and son. You can find him on Twitter at @JoeAttardi.1. Introduction to Netlify CMS2. Gatsby Crash Course3. Setting Up the Example Project4. Setting Up Netlify CMS5. The Netlify CMS Application6. Sourcing Blog Data7. Dynamic Page Creation8. Blog Pagination9. Adding More Content10. Creating the Coffee Menu11. Working with Images12. Customizing the CMS13. The Editorial Workflow14. Wrap Up
Serverless Security
Apply the basics of security in serverless computing to new or existing projects. This hands-on guide provides practical examples and fundamentals. You will apply these fundamentals in all aspects of serverless computing: improving the code, securing the application, and protecting the infrastructure. You will come away having security knowledge that enables you to secure a project you are supporting and have technical conversations with cybersecurity personnel.At a time when there are many news stories on cybersecurity breaches, it is crucial to think about security in your applications. It is tempting to believe that having a third-party host the entire computing platform will increase security. This book shows you why cybersecurity is the responsibility of everyone working on the project.WHAT YOU WILL LEARN* Gain a deeper understanding of cybersecurity in serverless computing* Know how to use free and open source tools (such as the Node Package Manager, ESLint, and VSCode) to reduce vulnerabilities in your application code* Assess potential threats from event triggers in your serverless functions* Understand security best practices in serverless computing* Develop an agnostic security architecture while reducing risk from vendor-specific infrastructureWHO THIS BOOK IS FORDevelopers or security engineers looking to expand their current knowledge of traditional cybersecurity into serverless computing projects. Individuals just beginning in serverless computing and cybersecurity can apply the concepts in this book in their projects.MIGUEL CALLES is a freelance cybersecurity content writer. He has an information assurance certification, and works as an engineer on a serverless project. He started in cybersecurity in 2016 for a US government contract, and has been doing technical writing since 2007, and has worked in various engineering roles since 2004. Miguel started his interest in cybersecurity when he was in middle school and was trying to backward engineer websites.INTRODUCTIONPART I: THE NEED FOR SECURITYCHAPTER 1: DETERMINING SCOPEUnderstanding the ApplicationScopingCHAPTER 2: PERFORMING A RISK ASSESSMENTUnderstanding the Threat LandscapeThreat ModelingPreparing the Risk AssessmentPart II: Securing the ApplicationCHAPTER 3: SECURING THE CODEAssessing DependenciesUsing Static Code Analysis ToolsWriting Unit TestsCHAPTER 4: SECURING THE INTERFACESIdentifying the InterfacesDetermining the Interface InputsReducing the Attack SurfaceCHAPTER 5: SECURING THE CODE REPOSITORYUsing a Code RepositoryLimiting Saved ContentPART III: SECURING THE INFRASTRUCTURECHAPTER 5: RESTRICTING PERMISSIONSUnderstanding PermissionsIdentifying the ServicesUpdating the PermissionsCHAPTER 6: ACCOUNT MANAGEMENTUnderstanding Account AccessRestricting Account AccessImplementing Multi-Factor AuthenticationUsing SecretsPART IV: MONITORING AND ALERTINGCHAPTER 7: MONITORING LOGSUnderstanding Logging MethodsReviewing LogsCHAPTER 8: MONITORING METRICSUnderstanding MetricsReviewing MetricsCHAPTER 9: MONITORING BILLINGUnderstanding BillingReviewing BillingCHAPTER 10: MONITORING SECURITY EVENTSUnderstanding Security EventsReviewing Security EventCHAPTER 10: ALERTINGUnderstanding AlertingImplementing AlertingCHAPTER 11: AUDITINGUnderstanding AuditingImplementing AuditingPART V: SECURITY ASSESSMENT AND REPORTCHAPTER 12: FINALIZING THE RISK ASSESSMENTScoring the Identified RisksDefining the Mitigation StepsAssessing the Business ImpactDetermining the Overall Security Risk Level
Learn PHP 8
Write solid, secure, object-oriented code in the new PHP 8. In this book you will create a complete three-tier application using a natural process of building and testing modules within each tier. This practical approach teaches you about app development and introduces PHP features when they are actually needed rather than providing you with abstract theory and contrived examples.In Learn PHP 8, programming examples take advantage of the newest PHP features; you’ll follow a learn-by-doing approach, which provides you with complete coding examples. “Do It” exercises in each chapter provide the opportunity to make adjustments to the example code. The end-of-chapter programming exercises allow you to develop your own applications using the algorithms demonstrated in the chapter.Each tier is logically and physically separated using object-oriented and dependency injection techniques, thus allowing independent tiers that can be updated with little or no effect on the other tiers. In addition to teaching good programming practices through OOP, there is a strong emphasis on creating secure code.As each chapter is completed, you’ll have the opportunity to design and create an application reinforcing the concepts learned.WHAT YOU WILL LEARN* Program PHP 8 web applications* Use interfaces, containers, and platforms* Apply modular programming * Manage data objects and use MySQL and other databasesWork with multi-functional and secure user interfaces * Handle logging exceptions and moreWHO THIS BOOK IS FORThose new to web development, specifically PHP programming. Also, this book can be useful to those who have some PHP/web development experience who are new to PHP 8.Steve Prettyman is a college instructor on PHP programming, web development, and related technologies. He is and has been a practicing web developer and is a book author.1. Introduction to PHP 82. Interfaces, Platforms, Containers: Three-Tiers Programming3. Modular Programming4. Secure User Interfaces5. Handling and Logging Exceptions6. Data Objects7. Authentication8. Multi-functional Interfaces
Beginning C++20
Begin your programming journey with C++ , starting with the basics and progressing through step-by-step examples that will help you become a proficient C++ programmer. This book includes new features from the C++20 standard such as modules, concepts, ranges, and the spaceship operator. All you need are Beginning C++20 and any recent C++ compiler and you'll soon be writing real C++ programs. There is no assumption of prior programming knowledge.All language concepts that are explained in the book are illustrated with working program examples, and all chapters include exercises for you to test and practice your knowledge. Free source code downloads are provided for all examples from the text and solutions to the exercises.This latest edition has been fully updated to the latest version of the language, C++20, and to all conventions and best practices of modern C++. Beginning C++20 also introduces the elements of the C++ Standard Library that provide essential support for the C++20 language.WHAT YOU WILL LEARN* Begin programming with the C++20 standard* Carry out modular programming in C++* Work with arrays and loops, pointers and references, strings, and more* Write your own functions, types, and operators* Discover the essentials of object-oriented programming* Use overloading, inheritance, virtual functions, and polymorphism* Write generic function and class templates, and make them safer using concepts * Learn the ins and outs of containers, algorithms, and ranges* Use auto type declarations, exceptions, move semantics, lambda expressions, and much moreWHO THIS BOOK IS FORProgrammers new to C++ and those who may be looking for a refresh primer on C++ in general.IVOR HORTON is self-employed in consultancy and writes programming tutorials. He is the author of many programming books. Ivor worked for IBM for many years and holds a bachelor's degree, with honors, in mathematics. Horton's experience at IBM includes programming in most languages (including assembler and high-level languages on a variety of machines), real-time programming, and designing and implementing real-time closed loop industrial control systems. He has extensive experience teaching programming to engineers and scientists (Fortran, PL/1, APL, etc.). Horton is an expert in mechanical, process, and electronic CAD systems; mechanical CAM systems; and DNC/CNC systems.PETER VAN WEERT works for Danaher in its R&D unit for digital dentistry software, developing software for the dental practice of tomorrow. In his spare time, he has co-authored two books on C++ and two award-winning Windows 8 apps and is a regular expert speaker at, and board member of, the Belgian C++ Users Group. He is a software engineer whose main interests and expertise are application software development, programming languages, algorithms, and data structures.He received his master of science degree in computer science summa cum laude with congratulations of the Board of Examiners from the University of Leuven. In 2010, he completed his PhD thesis there on the design and efficient compilation of rule-based programming languages at the research group for declarative programming languages and artificial intelligence. During his doctoral studies, he was a teaching assistant for object-oriented programming (Java), software analysis and design, and declarative programming. After graduating, Peter worked at Nikon Metrology for more than six years on large-scale, industrial application software in the area of 3D laser scanning and point cloud inspection. He learned to master C++ and refactoring and debugging of very large code bases, and he gained further proficiency in all aspects of the software development process, including the analysis of functional and technical requirements, and agile and scrum-based project and team management.1. Basic Ideas2. Introducing Fundamental Types of Data3. Working Fundamental Types4. Making Decisions5. Arrays and Loops6. Pointers and References7. Working with Strings8. Defining Functions9. Vocabulary Types10. Function Templates11. Modules and Namespaces12. Defining your own Data Types13. Operator Overloading14. Inheritance15. Polymorphism16. Runtime Errors and Exceptions17. Class Templates18. Move Semantics19. First-Class Functions20. Containers and Algorithms21. Constrained Templates and ConceptsAppendix A (online only; to be offered as part of source code download)
Creating Good Data
Create good data from the start, rather than fixing it after it is collected. By following the guidelines in this book, you will be able to conduct more effective analyses and produce timely presentations of research data.Data analysts are often presented with datasets for exploration and study that are poorly designed, leading to difficulties in interpretation and to delays in producing meaningful results. Much data analytics training focuses on how to clean and transform datasets before serious analyses can even be started. Inappropriate or confusing representations, unit of measurement choices, coding errors, missing values, outliers, etc., can be avoided by using good dataset design and by understanding how data types determine the kinds of analyses which can be performed.This book discusses the principles and best practices of dataset creation, and covers basic data types and their related appropriate statistics and visualizations. A key focus of the book is why certain data types are chosen for representing concepts and measurements, in contrast to the typical discussions of how to analyze a specific data type once it has been selected.WHAT YOU WILL LEARN* Be aware of the principles of creating and collecting data* Know the basic data types and representations* Select data types, anticipating analysis goals* Understand dataset structures and practices for analyzing and sharing* Be guided by examples and use cases (good and bad)* Use cleaning tools and methods to create good dataWHO THIS BOOK IS FORResearchers who design studies and collect data and subsequently conduct and report the results of their analyses can use the best practices in this book to produce better descriptions and interpretations of their work. In addition, data analysts who explore and explain data of other researchers will be able to create better datasets.HARRY J. FOXWELL is a professor. He teaches graduate data analytics courses at George Mason University in the department of Information Sciences and Technology and he designed the data analytics curricula for his university courses. He draws on his decades of experience as Principal System Engineer for Oracle and for other major IT companies to help his students understand the concepts, tools, and practices of big data projects. He is co-author of several books on operating systems administration. He is a US Army combat veteran, having served in Vietnam as a Platoon Sergeant in the First Infantry Division. He lives in Fairfax, Virginia with his wife Eileen and two bothersome cats.INTRODUCTIONGoal: The problem of dataset cleaning and why better design is neededWho this book is forCHAPTER 1: BASIC DATA TYPESGoal: understanding data typesNominal, ordinal, interval, ratio, otherHow/why to choose specific representationsCHAPTER 2: PLANNING YOUR DATA COLLECTIONGoal: preventive action, avoiding data creation errorsAnticipating your required analysisThe goals of descriptive statistics and visualizationsThe goals of relationship statistics and visualizationsIndependent and dependent variablesCHAPTER 3: DATASET STRUCTURESGoal: Understanding how to structure/store dataTypes of datasets.csv, SQL, Excel, Web, JSON,Sharing data (open formats)Managing datasetsCHAPTER 4: DATA COLLECTION ISSUESGoal: Understanding how to collect dataUnderstand and avoid BiasSamplingCHAPTER 5: EXAMPLES AND USE CASESGoal: Illustrate good & not so good datasetsCHAPTER 6: TOOLS FOR DATASET CLEANINGGoal: still need some data cleanup? here’s some helpData cleaning using R, Python, commercial tools (e.g., Tableau)ANNOTATED REFERENCESGoal: include helpful data design and cleaning references
Learn Data Science Using SAS Studio
Do you want to create data analysis reports without writing a line of code? This book introduces SAS Studio, a free data science web browser-based product for educational and non-commercial purposes. The power of SAS Studio comes from its visual point-and-click user interface that generates SAS code. It is easier to learn SAS Studio than to learn R and Python to accomplish data cleaning, statistics, and visualization tasks.The book includes a case study about analyzing the data required for predicting the results of presidential elections in the state of Maine for 2016 and 2020. In addition to the presidential elections, the book provides real-life examples including analyzing stocks, oil and gold prices, crime, marketing, and healthcare. You will see data science in action and how easy it is to perform complicated tasks and visualizations in SAS Studio.You will learn, step-by-step, how to do visualizations, including maps. In most cases, you will not need a line of code as you work with the SAS Studio graphical user interface. The book includes explanations of the code that SAS Studio generates automatically. You will learn how to edit this code to perform more complicated advanced tasks. The book introduces you to multiple SAS products such as SAS Viya, SAS Analytics, and SAS Visual Statistics.WHAT YOU WILL LEARN* Become familiar with SAS Studio IDE* Understand essential visualizations* Know the fundamental statistical analysis required in most data science and analytics reports* Clean the most common data set problems* Use linear progression for data prediction* Write programs in SAS* Get introduced to SAS-Viya, which is more potent than SAS studioWHO THIS BOOK IS FORA general audience of people who are new to data science, students, and data analysts and scientists who are experienced but new to SAS. No programming or in-depth statistics knowledge is needed.ENGY FOUDA is an author, freelance engineer, and journalist. She also is a freelance instructor and teaches SAS, Docker Fundamentals, Docker for Enterprise Developers, Docker for Enterprise Operations, and Kubernetes. Engy holds two master's degrees, one in journalism from Harvard University, Extension School, and another in computer engineering from Cairo University, Egypt. She earned the Data Science Professional Graduate Certificate from Harvard University, Extension School. She volunteers as the Team Lead for Momken Group (Engineering for the Blind), Egypt Scholars Inc. The team designs and manufactures devices and develops Arabic applications for visually impaired people in the MENA region. Engy volunteers as a Member-at-Large and as newsletter editor of the IEEE Mid-Hudson section. And she published several books that made Amazon's best-selling charts for Arabic books.
BigQuery for Data Warehousing
Create a data warehouse, complete with reporting and dashboards using Google’s BigQuery technology. This book takes you from the basic concepts of data warehousing through the design, build, load, and maintenance phases. You will build capabilities to capture data from the operational environment, and then mine and analyze that data for insight into making your business more successful. You will gain practical knowledge about how to use BigQuery to solve data challenges in your organization.BigQuery is a managed cloud platform from Google that provides enterprise data warehousing and reporting capabilities. Part I of this book shows you how to design and provision a data warehouse in the BigQuery platform. Part II teaches you how to load and stream your operational data into the warehouse to make it ready for analysis and reporting. Parts III and IV cover querying and maintaining, helping you keep your information relevant with other Google Cloud Platform services and advanced BigQuery. Part V takes reporting to the next level by showing you how to create dashboards to provide at-a-glance visual representations of your business situation. Part VI provides an introduction to data science with BigQuery, covering machine learning and Jupyter notebooks.WHAT YOU WILL LEARN* Design a data warehouse for your project or organization* Load data from a variety of external and internal sources* Integrate other Google Cloud Platform services for more complex workflows* Maintain and scale your data warehouse as your organization grows* Analyze, report, and create dashboards on the information in the warehouse* Become familiar with machine learning techniques using BigQuery MLWHO THIS BOOK IS FORDevelopers who want to provide business users with fast, reliable, and insightful analysis from operational data, and data analysts interested in a cloud-based solution that avoids the pain of provisioning their own servers.MARK MUCCHETTI is an industry technology leader in healthcare and ecommerce. He has been working with computers and writing software for over 30 years, starting with BASIC and Turbo C on an Intel 8088 and now using Node.js in the cloud. He has been building and managing technology groups for much of that time, combining his deep love of technical topics with his management skills to create world-class platforms. Mark has also worked in databases, release engineering, front- and back-end coding, and project management. He believes that the best decisions are made with the best data available, and that BigQuery is a great technology to increase the value and accessibility of data for business leaders on a day-to-day basis. He has seen the transformation that accurate, timely data has on an organization’s ability to succeed, and wants to bring that knowledge to the world in a people-first way. PART I. BUILDING A WAREHOUSE1. Settling into BigQuery2. Starting Your Warehouse Project3. All My Data4. Managing BigQuery CostsPART II. FILLING THE WAREHOUSE5. Loading Data Into the Warehouse6. Streaming Data Into the Warehouse7. DataflowPART III. USING THE WAREHOUSE8. Care and Feeding of Your Warehouse9. Querying the Warehouse10. Scheduling Jobs11. Serverless Functions with GCP12. Cloud LoggingPART IV. MAINTAINING THE WAREHOUSE13. Advanced BigQuery14. Data Governance15. Adapting to Long-Term ChangePART V. REPORTING ON AND VISUALIZING YOUR DATA16. Reporting17. Dashboards and Visualization18. Google Data StudioPART VI. ENHANCING YOUR DATA'S POTENTIAL19. BigQuery ML20. Jupyter Notebooks and Public Datasets21. Conclusion22. Appendix A: Cloud Shell and Cloud SDK23. Appendix B: Sample Project Charter
Entwicklung eines Customization Frameworks für cloudbasierte Shopfloor Management Systeme. Wie digitale Produkte für Kunden individualisierbar bleiben
Durch die voranschreitende Digitalisierung und die damit verbundene digitale Verfügbarkeit von Produktionsprozessdaten in Echtzeit ergeben sich auf Shopfloor-Ebene neue Möglichkeiten. Besonderes Potenzial bieten die rechnergestützte Auswertung und die Interaktion mit den Mitarbeitern vor Ort, aber auch mit dem Management. Doch die Datenintegration in Produktionsprozesse bringt auch Herausforderungen. Digitale Produkte sollen kundenspezifisch individualisierbar sein, bei der Einbindung in Unternehmen sind daher meist funktionale und technische Anpassungen notwendig. Dadurch wird für den Kunden die angestrebte Digitalisierung langwierig und kostenintensiv, für den Anbieter herrscht Planungsunsicherheit. Jan Heimer leitet ein Customization Framework für ein digitales Shopfloor Management System her. Mit diesem sollen Skalierbarkeit, Standardisierung und Flexibilität auch bei einer cloudbasierten Systemarchitektur erreicht werden, sodass Kunden neue Systeme flexibel nach ihren Wünschen anpassen können. Aus dem Inhalt: - Hybrid-Cloud; - Industrie 4.0; - Lean Management; - Digitale Transformation; - Nutzenkontext
Projekt Unicorn
Mit Spannung erwarteter Folgeband zum Bestseller "Projekt Phoenix" - Roman, der "Projekt Phoenix" um die Perspektive der Entwickler ergänzt - Wall Street Journal-Bestseller in den USA - fesselnde Story über die Herausforderungen moderner Softwareentwicklung in Zeiten der digitalen Transformation Parts Unlimited – ein milliardenschweres Unternehmen der Automobilbranche – steht kurz davor, aus dem Markt verdrängt zu werden. Nach einer folgenschweren Panne bei der Lohn- und Gehaltsabrechnung wird Maxine, eine leitende Softwareentwicklerin, unverschuldet in das berüchtigte Projekt Phoenix strafversetzt. Dort verzweifelt sie fast an einem bürokratischen Monsterapparat mit endlosen Meetings und hochkomplizierten Regeln – bis sie von firmeninternen Rebellen angeworben wird, die die bestehende Ordnung umstürzen wollen: Damit Entwicklerinnen und Entwickler wieder echte Freude an ihrer Arbeit haben. Die kluge und kämpferische Maxine und ihre rebellischen Kolleginnen und Kollegen rufen Projekt Unicorn ins Leben und setzen dabei auf die "Fünf Ideale". Damit verändern sie grundlegend, wie die Business- und Technologiebereiche des Unternehmens zusammenarbeiten – und geraten in das Fadenkreuz einflussreicher und gefährlicher Gegner. Gelingt es ihnen, das Überleben von Parts Unlimited in einem Wettrennen gegen die Zeit zu sichern? Packend beschreibt Gene Kim, Autor des Bestsellers "Projekt Phoenix", die Herausforderungen, denen sich Unternehmen – und alle, die in ihnen arbeiten – im Zeitalter von Digital Disruption stellen müssen: in der Softwareentwicklung und als lernende Organisation. Sie werden sich in diesem Roman wiederfinden – und die fesselnde Story wird Sie unterhalten und Ihnen viele Denkanstöße geben.
PMP Project Management Professional Exam Study Guide
PREPARE FOR PMP CERTIFICATION EXAM SUCCESS WITH THIS FULLY UPDATED AND COMPREHENSIVE STUDY GUIDEThis study guide serves as a comprehensive resource for those who plan on taking the Project Management Professional (PMP) certification exam administered by PMI. The book helps you prepare for the exam, and it will continue to serve project managers as an on-the-job reference book.The PMP Project Management Professional Exam Study Guide, Tenth Edition is fully updated to include recent changes to the exam. New content covers the integral role that Agile and other iterative practices have in project management. Updates also address the pivotal responsibilities of the project manager and the skill sets required for this position. The study guide was written to reflect the Project Management Process and Procedures found in the revised A Guide to the Project Management Body of Knowledge -- PMBOK® Guide, 6th Edition.Well-known author and expert Kim Heldman, PMP, helps to prepare you for the exam with in-depth coverage of topics, concepts, and key terms. Learn more about the three main domain areas of people, process, and business environment, plus the predictive, agile, and hybrid approaches to project management.This guide is an effective learning aid that will take your understanding to the next level.* Provides comprehensive material, covering the complete exam outline* Lists chapter objectives and offers detailed discussions of these objectives* Reflects differences in project management environments and approaches* Effectively presents real world scenarios, project application sidebars, and chapter review questionsYou’ll also connect to a beneficial, on-the-go resource: an interactive online learning environment and test bank. This environment includes an assessment test, chapter tests, practice exams, electronic flashcards, and a glossary of key terms. A thorough review is the best prep for a challenging certification exam. So, get ready with this essential PMP study guide.ABOUT THE AUTHORKIM HELDMAN, PMP®, is Senior Manager, IT/Chief Information Officer for the Regional Transportation District in Denver, Colorado, where she oversees an IT portfolio of projects that range from those small in scope and budget to multimillion-dollar, multiyear projects. Kim has more than 25 years of experience in IT project management, resource planning, budgeting, project prioritization, and strategic and tactical planning. Most of the real-world scenarios in this Study Guide are based on her actual experiences on the job. Visit her website at www.kimheldman.com. Introduction xixAssessment Test xxixAnswers to Assessment Test xlixCHAPTER 1 BUILDING THE FOUNDATION 1Establishing the Foundation 3Projects vs. Operations 4Project Characteristics 6What Is Project Management? 7Programs 8Portfolios 8Organizational Project Management 11Project Management Offices 11Understanding How Projects Come About 13Needs and Demands and Other Factors That Lead to Project Creation 14Skills Every Good Project Manager Needs 17Technical Project Management Skills 18Business Management and Strategic Skills 18Communication Skills 19Organizational and Planning Skills 19Conflict Management Skills 20Negotiation and Influencing Skills 20Leadership Skills 21Team-Building and Motivating Skills 21Role of a Project Manager 22Understanding Project Management Process Groups 22Determining a Project Methodology or Approach 28Life Cycle Categories 29Predictive Life Cycle Methodology 30Agile Methodologies 33Hybrid 38Project Life Cycles 38Understanding How This Applies to Your Next Project 39Summary 40Exam Essentials 41Review Questions 43CHAPTER 2 ASSESSING PROJECT NEEDS 49Exploring the Project Management Knowledge Areas 51Project Integration Management 53Project Scope Management 56Project Schedule Management 57Project Cost Management 58Project Quality Management 59Project Resource Management 59Project Communications Management 60Project Risk Management 62Project Procurement Management 62Project Stakeholder Management 63Assessing Project Viability 64Using Project Selection Methods 65Assessing Project Needs and Creating the Project Charter 73Enterprise Environmental Factors 78Organizational Process Assets 78Tools and Techniques 81Formalizing and Publishing the Project Charter 82Pulling the Project Charter Together 83Key Stakeholders 84Project Charter Sign-Off 87Maintaining Project Artifacts 88Introducing the Kitchen Heaven Project Case Study 89Understanding How This Applies to Your Next Project 93Summary 94Exam Essentials 96Review Questions 98CHAPTER 3 DELIVERING BUSINESS VALUE 103Understanding Organizational Structures 106Functional Organizations 108Project-Oriented Organizations 112Matrix Organizations 114Other Organizational Structures 118Pmo 118PMO in an Agile Environment 119Project-Based Organizations 121Influences of Organizational Structure on Agile Methodologies 122Identifying Stakeholders 123Discovering Stakeholders 124Stakeholder Analysis 126Categorizing Stakeholders 127Stakeholder Register 134Stakeholders on an Agile Project 135Six Sigma Adaptive Methodology 137Delivering Business Value 140Business Value Network 142Assessing Business Value 143Delivering Business Value Incrementally 145Examining Business Value 147Subdividing Project Tasks 148Understanding How This Applies to Your Next Project 151Summary 152Exam Essentials 153Review Questions 155CHAPTER 4 DEVELOPING THE PROJECT SCOPE 161Developing the Project Management Plan 164Project Complexity 168Data Gathering and Interpersonal Skills 168Documenting the Project Management Plan 169Documenting the Project Management Plan Using a Predictive Methodology 172Plan Scope Management 173Alternatives Analysis 175Documenting the Scope Management Plan 177Documenting the Requirements Management Plan 178Collecting Requirements 178Gathering Documents for the Collect Requirements Process 180Gathering and Documenting Requirements 185Finalizing Requirements 189Defining Scope 192Writing the Project Scope Statement 194Managing the Product Backlog 199Creating the Work Breakdown Structure 201Decomposing the Deliverables 202Constructing the WBS 203Backlog 211Finalizing the WBS 212Understanding How This Applies to Your Next Project 216Summary 218Exam Essentials 219Review Questions 221CHAPTER 5 CREATING THE PROJECT SCHEDULE 229Creating the Schedule Management Plan 232Defining Activities 233Creating the Activity List 234Breaking Down User Stories 235Understanding the Sequence Activities Process 237Precedence Diagramming and Leads and Lags 238Project Management Information System 243Project Schedule Network Diagrams 243Estimating Activity Resources 244How to Estimate Activity Resources 245Documenting Resource Requirements 246Estimating Resources in an Adaptive Methodology 247Estimating Activity Durations 247Project Calendars and Other Considerations 248Estimating Techniques 249Duration Estimates 253Estimating Activity Durations Using Adaptive Methodologies 255Developing the Project Schedule 257Gather Documents to Assist in Developing the Schedule 257Developing the Project Schedule 258Project Schedule and the Schedule Baseline 272Using a Kanban Board and Scrum Board 277Scrum Board 279Combining Techniques 280Agile Release Planning 281Applying Process Groups in an Agile Approach 281Understanding How This Applies to Your Next Project 286Summary 287Exam Essentials 289Review Questions 291CHAPTER 6 DEVELOPING THE PROJECT BUDGET AND ENGAGING STAKEHOLDERS 297Creating the Cost Management Plan 300Performing Plan Cost Management 301Creating the Cost Management Plan 302Estimating Costs 303Estimating Techniques 307Estimating Costs for an Agile Project 308Creating the Cost Estimates 309Establishing the Cost Baseline 311Techniques for Developing the Project Budget 313Developing the Cost Baseline 314Understanding Stakeholders 318Analyzing Stakeholders 319Stakeholder Engagement Plan 320Mentoring Stakeholders 321Engaging Stakeholders in an Adaptive Methodology 322Communicating the Plan 323Planning Communications 324Determining Communication Needs 325Documenting the Communications Management Plan 331Communicating on an Agile Team 333A Closer Look at Adaptive Methodologies 335Other Methodologies 340Combining Methodologies 345Understanding How This Applies to Your Next Project 348Summary 349Exam Essentials 351Review Questions 353CHAPTER 7 IDENTIFYING PROJECT RISKS 359Understanding Risk 361Creating the Risk Management Plan 362Risk Attitude 363Conducting Risk Meetings 364Documenting the Risk Management Plan 366Identifying Potential Risks 372Data Gathering and Data Analysis Techniques for Identifying Risks 374Documenting the Risk Register 378Identifying Risks Using an Agile Approach 380Analyzing Risks Using Qualitative Techniques 381Performing Qualitative Risk Analysis 382Ranking Risks in the Risk Register 390Quantifying Risk 391Performing Quantitative Risk Analysis 392Updating the Risk Report 397Developing a Risk Response Plan 398Strategies for Creating Risk Responses 399Documenting the Risk Responses Plan 404Assessing Risks Using an Agile Approach 407Planning for Project Compliance 409Understanding How This Applies to Your Next Project 413Summary 414Exam Essentials 415Review Questions 417CHAPTER 8 PLANNING AND PROCURING RESOURCES 423Procurement Planning 425Gathering Documents for the Procurement Management Plan 427Source Selection Criteria 433Procurement Management Plan 435Procurements in an Agile Environment 442Developing the Resource Management Plan 445Understanding Enterprise Environmental Factors 446Using Data Representation Techniques for Plan Resource Management 448Documenting the Resource Management Plan 451Resources on an Agile Project 455Quality Planning 456Preparing for Quality 457Developing the Quality Management Plan 458Documenting the Quality Management Plan 466Quality Planning for Agile Projects 468Project Planning Using Agile Methodologies 469Bringing It All Together 470Choosing a Life Cycle Methodology 473Understanding How This Applies to Your Next Project 480Summary 481Exam Essentials 482Review Questions 485CHAPTER 9 DEVELOPING THE PROJECT TEAM 491Directing and Managing Project Work 494Direct and Manage Project Work Inputs 496Project Management Information System 499Deliverables and Work Performance Data 499Directing Project Work on Agile Projects 504Executing Practices for Delivering Project Work 508Acquiring the Project Team and Project Resources 510The Resource Management Plan 510Techniques for Acquiring Resources 511Project Team Assignments 515Developing the Project Team 517Generational Diversity 518Tools and Techniques to Develop the Team 520Developing Agile Teams 536Team Performance Assessments 539Managing Project Teams 543Emotional Intelligence and Other Tools for Managing Teams 543Lessons Learned Managing Teams 545Understanding How This Applies to Your Next Project 547Summary 548Exam Essentials 550Review Questions 552CHAPTER 10 SHARING INFORMATION 559Implementing Risk Responses 563Conducting Procurements 563Evaluating Proposals 564Creating Procurement Agreements 571Conducting Procurements on Agile Projects 573Laying Out Quality Assurance Procedures 574Managing Quality with Data and Audits 575Quality Reports and Test and Evaluation Documents 580Conducting Quality Assessments on an Agile Project 581Managing Project Knowledge 582Knowledge Management 583Information Management 583Managing Project Artifacts 583Managing Project Information 584Communication and Conflict Resolution Skills 585Project Communications and Elements of Communicating 594Communicating on Agile Projects 596Managing Stakeholder Engagement 597Observing and Conversing 598Agile Frameworks 599Agile Methodologies or Frameworks 600Scaling Frameworks 601Understanding How This Applies to Your Next Project 606Summary 607Exam Essentials 608Review Questions 611CHAPTER 11 MEASURING AND CONTROLLING PROJECT PERFORMANCE 619Monitoring and Controlling Project Work 624Forecasting Methods 625Work Performance Reports 626Controlling Procurements 627Procurement Documents and Approved Change Requests 629Monitoring Vendor Performance 631Closing Out Procurements 632Monitoring Communications 636Documents to Help Monitor Communications 637Monitoring Communications with Meetings 637Work Performance Information 639Performing Integrated Change Control 642How Change Occurs 643Change Control Concerns 644Configuration Control 645Change Control System 646Approved Change Requests 650Changes in the Business Environment 651Monitoring Stakeholder Engagement 654Controlling Resources 654Utilizing Control Quality Techniques 655Control Quality Tools and Techniques 656Verifying Deliverables 664Monitoring and Controlling Risk 664Monitor Risks Analysis and Meetings 666Monitor Risks Updates 667Monitoring Project Management Integrations 668Understanding How This Applies to Your Next Project 671Summary 672Exam Essentials 674Review Questions 676CHAPTER 12 CONTROLLING WORK RESULTS AND CLOSING OUT THE PROJECT 683Controlling Cost Changes 686Earned Value Analysis 687Variance Analysis 689Trend Analysis 692To-Complete Performance Index 697Earned Value Measures on Agile Projects 700Monitoring and Controlling Schedule Changes 702Burndown and Burnup Charts 703Performance Reviews 705Changes to the Schedule 706Validating Project Scope 707Controlling Scope 708Measuring Work Results on Agile Projects 710Formulating Project Closeout 713Characteristics of Closing 713Project Endings 714Closing Out the Project 717Administrative Closure Procedures 718Regression Analysis 719Close Project or Phase Final Report 719Closing Out the Procurements 723Closing Out an Agile Project 724Celebrate! 725Releasing Project Team Members 725Balancing Stakeholders’ Interests at Project Close 725Competing Needs 726Dealing with Issues and Problems 727Balancing Constraints 727Professional Responsibility 727Responsibility 728Respect 731Fairness 734Honesty 737Role Delineation Study 739Applying Professional Knowledge 739Project Management Knowledge 740Education Providers 740Industry Knowledge 740Understanding How This Applies to Your Next Project 746Summary 748Exam Essentials 750Review Questions 752APPENDICES 757APPENDIX A ANSWERS TO REVIEW QUESTIONS 759Chapter 1: Building the Foundation 760Chapter 2: Assessing Project Needs 761Chapter 3: Delivering Business Value 763Chapter 4: Developing the Project Scope 765Chapter 5: Creating the Project Schedule 767Chapter 6: Developing the Project Budget and Engaging Stakeholders 768Chapter 7: Identifying Project Risks 770Chapter 8: Planning and Procuring Resources 771Chapter 9: Developing the Project Team 773Chapter 10: Sharing Information 775Chapter 11: Measuring and Controlling Project Performance 776Chapter 12: Controlling Work Results and Closing Out the Project 778APPENDIX B PROCESS INPUTS AND OUTPUTS 781Initiating Processes 782Planning Processes 784Executing Processes 807Monitoring and Controlling Processes 821Closing Processes 836Index 839
PMP Project Management Professional Practice Tests
THE BEST PRACTICE TEST PREPARATION FOR THE PMP EXAM!Boost your confidence through preparation before you take the new Project Management Professional (PMP) exam. The PMP Project Management Professional Practice Tests is the hands-on way to prepare for the exam and achieve your certification.* Access three practice tests* Study questions that cover the three PMP performance domains* Test your knowledge with three additional bonus exams* Practice with a total of 1,000 unique test questions.The Project Management Professional (PMP) certification was developed by the Project Management Institute (PMI). The certification requires extensive project management experience, instructional hours, and successful completion of the certification exam. Well-known PMP authors and experts, Kim Heldman and Vanina Mangano, have written practice questions that will help you get ready for testing as you work toward certification. The test questions provide you with coverage within each of the performance domains: people, process, and business environments.Project managers play a critical role in today’s organizations. When you pass the exam and earn certification, you will gain additional recognition for your skill set and expertise. This confidence-building guide also connects you to an interactive online learning environment and test bank including all the practice exam questions. Get help reaching your professional goals with the right PMP tools!ABOUT THE AUTHORSKIM HELDMAN, MBA, PMP, is the Chief Information Officer for the Regional Transportation District in Denver, Colorado. She has over 25 years of experience in project management and more than 18 years of experience in senior management positions. VANINA MANGANO, PMP, is a project portfolio management leader within Microsoft Corporation and leads a security PMO within the Cloud and AI division. She devotes time to furthering the project management profession through her volunteer work at the Project Management Institute. Introduction xvChapter 1 People (Domain 1.0) 1Chapter 2 Process (Domain 2.0) 37Chapter 3 Business Environment (Domain 3.0) 75Chapter 4 Full-Length Practice Exam 1 99Chapter 5 Full-Length Practice Exam 2 145Chapter 6 Full-Length Practice Exam 3 191Appendix Answers and Explanations 237Chapter 1: People (Domain 1.0) 238Chapter 2: Process (Domain 2.0) 250Chapter 3: Business Environment (Domain 3.0) 264Chapter 4: Full-Length Practice Exam 1 273Chapter 5: Full-Length Practice Exam 2 290Chapter 6: Full-Length Practice Exam 3 307Index 329