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Full Description
Big Data, the Second Generation gives business professionals the basic technological understanding, analytic tools, and diagnostic checklists they need to identify and plan out the big data strategy most appropriate to their particular company. This book examines the technologies and tools that are required to work at big data scale on the semi-structured and unstructured data of text analysis, speech recognition, video analysis, machine learning, and more. We are fast entering the second generation of big data: namely, big data that is accessible to nearly all organizations, as opposed to a few big companies. This book systematically maps the MapReduce and Apache Hadoop 2 ecosystems to the second-generation array of big data business applications, provides you the guidelines to match your company's profile with suitable applications, and shows you how to boost the power of your business analytics with new technologies for the compression, visualization, and actionable analysis of big data. The authors draw their insights into the second generation of big data from deep experience in industry as well as research.
David Belanger is the co-leader of the IEEE Big Data Initiative and was previously the Chief Scientist of AT&T Labs. Rashmi Jain is her university's representative in the New Jersey Big Data Alliance and was previously an IT systems architect for Accenture. Belanger and Jain walk you through the business applications of big data techniques for mining data produced by communication networks, social networks, and communities of interest. They consider the critical governance and security issues raised when an enterprise ventures into the big data space. They forecast the business value of emergent trends such as big-data-as-a-service open platforms. Finally, they present an action plan for executives and managers in companies large and small that will deliver maximum ROI from applying big data techniques to proprietary and public databases. A strategic planning guide rather than a technical implementation manual, Big Data, the Second Generation: Planning Your Big Data Strategy equips you to chart your organization's roadmap to harnessing big data and big analytics to beat your competition in the race to higher topline sales and a fatter bottom line.
Contents
Chapter 1. The Trajectory of Big Data Technology and the Big Analytics Culture * Scaling Bigness: The Virtue of Brevity vs. the Vice of Vogue* Expanding the Playing Field: The Arc from the First to the Second Generation of Big Data* Spreading the Analytics Culture: Smart Devices, Embedded Technologies, and Better Decisions Chapter 2. The Heart of Big Data * Six Classic Application Types at the Heart of Big Data* Metasearch* Fraud Detection and Security* Customer Experience and Marketing* Speech and Call Centers* Machine Translation* Location* Sources of Big Data* The World Wide Web* The Mobile Crowd* Operations* Experiments* Transactions* Sensors and Actuators* Manufacturing Processes* Types of Big Data* Structured * Semi-Structured"li>Unstructured Chapter 3. Application Changes Driven by Big Data * Granularity* Rare Events* Relationships* Personalization* Transparency* Latency Chapter 4. Evaluating What Big Data to Capture and Mine in Different Industries * Finance* Telecom* Media and Retail* E-Commerce* Healthcare* Government Chapter 5. The Twin Engines of Big Data: Analysis and Visualization * The Large View: The Confluence of Scale, Commodity Hardware, Parallelism, and Data Scientists* The Triad of Data Mining, Analytics, and Visualization* The MapReduce Family and the Hadoop Ecosystem* Graphs and Relationships* Learning* Fundamentals of Visualization: Thinking about Pictures and Thinking with Your Eyes* Visualization at Scale Chapter 6. Managing All of That Data Data Management Today: Data Warehouses, Data Marts, RDBMS, and Ad Hoc Systems* Next-Generation Databases* Column Store* Document, Text, Speech, and Video* Integration* Data Stream Management Systems: When Time Is of the Essence Chapter 7. Architecting the Enterprise for Big Analytics * The Role of Systems Architecture for Big Data and Analytics* IT Infrastructural Readiness* IT Governance for Big Data and Business Analytics Chapter 8. The Organizational Challenges of Transitioning an Enterprise to Big Data Functionality * The Challenge of Integrating Big Data Capabilities with Legacy Systems and Business Processes* The Challenge of Ramping Up to Big Data 2.0* Big Data Professionals: The Expanding Universe of Skill Sets and Competencies Chapter 9. Governance: The Sine Qua Non of Big Data * Principles* Policy* Processes* Practices* Challenges Chapter 10. The Meta-Issues of Big Data Governance Data Integrity and Quality* Data Security* Privacy* Operations, Administration, and Management* Data Retention Chapter 11. Convergent Trends toward Meta-Integration of Canonical Application Architectures * Integrating Metasearch, Forensics, and UX* Integrating Call Centers, Machine Translation, Geolocation, and Automated Marketing Chapter 12. Big Data 3.0: Critical Conditions for the Coming Big Bang * Open Data* Data as a Service* Internet of Things* Automatic Control Proliferation Chapter 13. Preliminaries for Framing Out the Role of Big Data in Your Organization * Down to Cases: Thinking Out Your Organization's Transition to Second-Generation Big Data* Finessing Your Organization's Structure, Processes, and Culture for Smart Big Data Integration
