Materias:

Tabla de Contenidos: “…Commercial OfferingsStaying Ahead of the Adversary; Summary; Chapter 6: Data Visualization; Synopsis; Introduction; Common Methods; Big Data Analytics; Interactive Visualization; Not Just For the Boardroom; Summary; Chapter 7: Data Simulation; Synopsis; Introduction; Traffic Simulation vs Emulation; Environmental; Flow; Data Sandboxes; Analytic Engines; Quantum Computing; Summary; Chapter 8: Kill Chain Modeling; Synopsis; Introduction; Key Components of Kill Chain Modeling; Leveraging Big Data; Tools Available; Maltego; Splunk; OpenGraphiti; Creation of Data Files; STIX; Kill Chains in STIX…”

Materias:

Tabla de Contenidos: “…Chapter 4: Managing Change in Data Science -- Understanding Change Management in Data Science -- Approaching Change in Data Science -- Recognizing what to avoid when driving change in data science -- Using Data Science Techniques to Drive Successful Change -- Using digital engagement tools -- Applying social media analytics to identify stakeholder sentiment -- Capturing reference data in change projects -- Using data to select people for change roles -- Automating change metrics -- Getting Started -- Part 2: Making Strategic Choices for Your Data -- Chapter 5: Understanding the Past, Present, and Future of Data -- Sorting Out the Basics of Data -- Explaining traditional data versus big data -- Knowing the value of data -- Exploring Current Trends in Data -- Data monetization -- Responsible AI -- Cloud-based data architectures -- Computation and intelligence in the edge -- Digital twins -- Blockchain -- Conversational platforms -- Elaborating on Some Future Scenarios -- Standardization for data science productivity -- From data monetization scenarios to a data economy -- An explosion of human/machine hybrid systems -- Quantum computing will solve the unsolvable problems -- Chapter 6: Knowing Your Data -- Selecting Your Data -- Describing Data -- Exploring Data -- Assessing Data Quality -- Improving Data Quality -- Chapter 7: Considering the Ethical Aspects of Data Science -- Explaining AI Ethics -- Addressing trustworthy artificial intelligence -- Introducing Ethics by Design -- Chapter 8: Becoming Data-driven -- Understanding Why Data-Driven Is a Must -- Transitioning to a Data-Driven Model -- Securing management buy-in and assigning a chief data officer (CDO) -- Identifying the key business value aligned with the business maturity -- Developing a Data Strategy -- Caring for your data -- Democratizing the data -- Driving data standardization…”

Tabla de Contenidos: “…Front Cover; Contents; Preface; About the Editor; Contributors; Chapter 1: The Value of Business Analytics; Chapter 2: Producing Insights from Information through Analytics; Chapter 3: Executive/Performance Dashboards; Chapter 4: Data Mining: Helping to Make Sense of Big Data; Chapter 5: Big Data Analytics for Business Intelligence; Chapter 6: Text Mining Fundamentals; Chapter 7: Neural Network Fundamentals; Chapter 8: Measuring Success in Social Media: An Information Strategy in a Data Obese World; Chapter 9: The Legal and Privacy Implications of Data Mining…”

Tabla de Contenidos: “…Detrick -- Ch8 Big Learning Data Risks: Privacy, Transparency, Culture, and Silly Data, Elliott Masie -- SECTION III Approaches to Big Learning Data -- Ch9 Case Study: It's Bigger Than Big Data- Metrics and Measurement Without a Strategy Is Just Data, Nickole Hansen, Peggy Parskey, Jennifer O'Brien -- Ch10 Case Study: Big Data, Big Difference in Training and Development, Jeff Losey -- Ch11 Case Study: Points for the Training Scoreboard, Ben Morrison -- Ch12 Case Study: Big Learning Data Sources and Analytics, Doug Armstrong -- Ch13 A Perspective From K-12: A View From the U.S. …”

Materias: “…Big data…”

Materias: “…Big data…”

Materias: “…Big data…”

Tabla de Contenidos: “…Creating a Data Explorer pool using the Azure CLI -- Summary -- Chapter 3: Exploring Azure Synapse Studio -- Technical requirements -- Exploring the user interface of Azure Synapse Studio -- Running your first query -- Creating a database -- Loading the data -- Verifying whether your data has loaded successfully -- Working with data in Azure Synapse notebooks -- Saving your work and configuring source control -- Managing and monitoring Data Explorer pools -- Scaling Data Explorer pools -- Pausing and resuming pools -- Monitoring Data Explorer pools -- Summary -- Chapter 4: Real-World Usage Scenarios -- Technical requirements -- Building a multi-purpose end-to-end analytics environment -- Sources -- Ingest -- Store -- Process -- Enrich -- Serve -- User -- Summary -- Managing IoT data -- Processing and analyzing geospatial data -- Enabling real-time analytics with big data -- Performing time series analytics -- Summary -- Part 2: Working with Data -- Chapter 5: Ingesting Data into Data Explorer Pools -- Technical requirements -- Understanding the data loading process -- Defining a retention policy -- Choosing a data load strategy -- Streaming ingestion -- Batching ingestion -- Performing data ingestion -- Using KQL control commands -- Building an Azure Synapse pipeline -- Implementing continuous ingestion -- Using other data ingestion mechanisms -- Summary -- Chapter 6: Data Analysis and Exploration with KQL and Python -- Technical requirements -- Analyzing data with KQL -- Selecting data -- Working with calculated columns -- Plotting charts -- Obtaining percentiles -- Creating a time series -- Detecting outliers -- Using linear regression -- Exploring Data Explorer pool data with Python -- Creating an Apache Spark pool -- Working with Azure Synapse notebooks -- Reading data from Data Explorer pools -- Plotting charts…”

Materias: “…Big data…”

Materias: “…Big data…”

Materias:

Tabla de Contenidos: “…Intro -- Inhaltsverzeichnis -- Vorwort -- Inhaltsübersicht -- Inhaltsverzeichnis -- 1 Big Data und Data Science -- 1.1 Einführung in Big Data -- 1.1.1 Volumen -- Abb. 1-1 Wachstum des Datenvolumens im Internetverkehr -- 1.1.2 Velocity/Geschwindigkeit -- 1.1.3 Variety/Vielfalt -- Abb. 1-2 Datenpyramide -- 1.1.4 Innovative Informationsverarbeitungsmethoden -- 1.1.5 Wissen generieren, Entscheidungen treffen, Prozesse automatisieren -- 1.1.6 Noch mehr Vs -- 1.2 Einführung in Data Science -- 1.2.1 Was gehört zu Data Science? …”

Materias:

Materias:

Tabla de Contenidos: “…Cover; Title Page; Copyright; Dedication; Contents; Preface; About the authors; 1.1 - Corporate data; The Totality of Data Across the Corporation; Dividing Unstructured Data; Business Relevancy; Big Data; The Great Divide; The Continental Divide; The Complete Picture; 1.2 - The data infrastructure; Two Types of Repetitive Data; Repetitive Structured Data; Repetitive Big Data; The Two Infrastructures; What's being Optimized?…”

Materias: “…Big data…”

Materias: “…Big data Social aspects…”

Tabla de Contenidos: “…More data ; "More data" Big data! ; Cutting through the hype ; Preparing for big data ; Putting big data in context ; Wrap up ; Notes ; Chapter 3. …”