Tabla de Contenidos: “….- -- Part I: Getting Started -- 1. The World of Big Data and IoT -- 2. Generating Data with Devices.- -- Part II: Data on the Move -- 3. …”

Tabla de Contenidos: “…-- Going Forward by Looking Back : the Rise of the Longue Durée -- The Short Past : or, The Retreat of the Longue Durée -- The Long and the Short : Climate Change, Governance and Inequality since the 1970s -- Big Questions, Big Data -- Conclusion: The Public Future of the Past…”

“…Manning's authors Reuven Lerner and Dane Hillard discuss the past, present, and future of the Python programming language, privacy engineering, Big Data, and ethics. Their passionate and dynamic conversation in this Code Call Session is geared toward becoming a Pythonista pro…”

“…In this Learning Apache Accumulo training course, expert author Aaron Cordova will teach you how to develop highly scalable big data applications. This course is designed for users that already have a basic understanding of Java programming. …”

“…This report reveals: The industries furthest along in adopting big data analytics and visualization technologies The most commonly analyzed sources of big data The most commonly used technologies for analyzing streaming data Which analytics skills are in most demand The most valued characteristic of big data across all industries The types of users big data analytics and visualization projects typically target If you’re a technology decision maker, a product manager looking to embed analytics, a business user relying on analytics, or a developer pursuing the most marketable skills, this report provides valuable details on today’s data analytics trends…”

“…A straightforward, full-color guide to showcasing data so your audience can see what you mean, not just read about it Big data is big news! Every company, industry, not-for-profit, and government agency wants and needs to analyze and leverage datasets that can quickly become ponderously large. …”

“…With over 60% new content, this updated guide reflects the new standards, and includes a new Big Data focus that highlights the use of C++ among popular Big Data software solutions. …”

“…Manufacturing processes, based on advanced mechanical principles, are enhanced by big data analytics on industrial sensor data. In current machine tools and systems, complex sensors gather useful data, which is captured, stored, and processed with edge, fog, or cloud computing. …”

“…Combine business sense, statistics, and computers in a new and intuitive way, thanks to Big Data Predictive analytics is a branch of data mining that helps predict probabilities and trends. …”

“…Let Hadoop For Dummies help harness the power of your data and rein in the information overload Big data has become big business, and companies and organizations of all sizes are struggling to find ways to retrieve valuable information from their massive data sets with becoming overwhelmed. …”

“…Updated for the latest developments, this third edition of Azure for Architects helps you get to grips with the core concepts of designing serverless architecture, including containers, Kubernetes deployments, and big data solutions. You'll learn how to architect solutions such as serverless functions, you'll discover deployment patterns for containers and Kubernetes, and you'll explore large-scale big data processing using Spark and Databricks. …”

“…You'll dive into the role of graphs in machine learning and big data platforms, and take an in-depth look at data source modeling, algorithm design, recommendations, and fraud detection. …”

Tabla de Contenidos: “…Acronyms and abbreviations -- Foreword and Acknowledgements -- The growing human and financial cost of dementia -- Executive summary -- Assessment and recommendations -- Towards a cure for dementia -- The role of big data in driving global co-operation and innovation in dementia research -- Improving the lives of people living with dementia…”

Tabla de Contenidos: “…Coding Native Mobile Apps for iPhones and Android DevicesIdentifying the Parts of an App; Chapter 8 Analyzing Big Data; Understanding Big Data; Defining big data; Preparing your data for analysis; Surveying techniques to analyze data; Decoding Data with R and Python; Using R for data analysis; Using Python for data analysis; Visualizing and Interacting with Data; Part III Getting Your Coding Education; Chapter 9 Coding on Your Own; Assessing Your Goal, Time, and Budget; Choosing your goal; Making time to learn how to code; Spending money to learn how to code…”

Tabla de Contenidos: “…-- A graph for every problem -- Data : collect, clean, and connect -- Stats and layout -- Visual attributes -- Explore and explain -- Point-and-click graph tools -- Lightweight programming -- Relationships -- Hierarchies -- Communities -- Flows -- Spatial networks -- Big data -- Dynamic graphs -- Design…”

Tabla de Contenidos: “…Future Trends in Master Data Management Using DaaS 194 -- Comparing Master Data Services Approach (Virtual) with Master Data Management Approach Involving Physical Consolidation 196 -- Case Study: Master Data Services for a Premier Investment Bank 197 -- Detailed Scope and Benefits 198 -- Proposed Solution Architecture for Master Data Services 199 -- Enterprise and Canonical Model for Master Data Management Implementation 202 -- Summary 208 -- 11. Big Data and Analytical Services 210 -- Topics Covered in this Chapter 210 -- Big Data 212 -- Big Data Analytics 213 -- Relationship Between DaaS and Big Data Analytics 217 -- Future Impact of DaaS on Big Data Analytics 220 -- Extending DaaS Reference Architecture for Big Data and Cloud Services 221 -- Fostering an Enterprise Data Mindset 228 -- Case Study: Big DaaS in the Automotive Industry 231 -- Summary 233 -- Part Four Ensuring Organizational Success -- 12. …”

Tabla de Contenidos: “…The age of the data product -- An operating system for big data -- A framework for Python and Hadoop streaming -- In-memory computing with Spark -- Distributed analysis and patterns -- Data mining and warehousing -- Data ingestion -- Analytics with higher-level APIs -- Machine learning -- Summary : doing distributed data science…”

“…Building on our 2015 study Big Data and Transport: Understanding and Assessing Options, this report presents the findings of an extensive exploration of these two broad themes at a workshop on "21st Century Public Interest Data Sharing" in Paris in November 2015, which involved a wide range of experts and stakeholders brought together under the auspices of the International Transport Forum’s Corporate Partnership Board…”

Tabla de Contenidos: “…4.2.4.9 The Need For Prescriptive Analytics in Maintenance: A Case Study -- 4.3 Big Data Analytics Methods -- 4.3.1 Defining Big Data Analytics -- 4.3.2 Defining Big Data Via the Three Vs -- 4.3.2.1 Data Volume as a Defining Attribute of Big Data -- 4.3.2.2 Data Type Variety as a Defining Attribute of Big Data -- 4.3.2.3 Data Feed Velocity as a Defining Attribute of Big Data -- 4.3.3 Text Analytics -- 4.3.4 Audio Analytics -- 4.3.5 Video Analytics -- 4.3.6 Social Media Analytics -- 4.4 Maintenance Strategies with Big Data Analytics -- 4.5 Data-Driven and Model-Driven Approaches -- 4.5.1 Data Mining and Knowledge Discovery -- 4.6 Maintenance Descriptive Analytics -- 4.7 Maintenance Diagnostic Analytics -- 4.8 Maintenance Predictive Analytics -- 4.9 Maintenance Prescriptive Analytics -- 4.10 Big Data Analytics Methods -- 4.10.1 Text Analytics -- 4.10.2 Audio Analytics -- 4.10.3 Video Analytics -- 4.10.4 Social Media Analytics -- 4.11 Big Data Management and Governance -- 4.12 Big Data Access and Analysis -- 4.13 Big Data Visualisation -- 4.14 Big Data Ingestion -- 4.15 Big Data Cluster Management -- 4.16 Big Data Distributions -- 4.17 Data Governance -- 4.18 Data Access -- 4.19 Data Analysis -- 4.20 Bid Data File System -- 4.20.1 Quantcast File System -- 4.20.2 Hadoop Distributed File System -- 4.20.3 Cassandra File System (CFS) -- 4.20.4 GlusterFS -- 4.20.5 Lustre -- 4.20.6 Parallel Virtual File System -- 4.20.7 Orange File System (OrangeFS) -- 4.20.8 BeeGFS -- 4.20.9 MapR-FS -- 4.20.9.1 Kudu -- References -- Chapter 5 Data-Driven Decision-Making -- 5.1 Data for Decision-Making -- 5.1.1 Data-Driven Decision-Making -- 5.1.2 The Process of Data-Driven Decision-Making -- 5.1.3 The Context of Data-Driven Decision-Making -- 5.1.4 The Importance of Data-Driven Decision-Making -- 5.1.5 Common Challenges of Data-Driven Decision-Making…”