From Big Data to Intelligent Data: An Applied Perspective

✍ Scribed by Fady A. Harfoush

Publisher: Springer
Year: 2021
Tongue: English
Leaves: 121
Series: Management for Professionals
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This book addresses many of the gaps in how industry and academia are currently tackling problems associated with big data. It introduces novel concepts, describes the end-to-end process, and connects the various pieces of the puzzle to offer a holistic view. In addition, it explains important concepts for a wide audience, using accessible language, diagrams, examples and analogies to do so. The book is intended for readers working in industry who want to expand their knowledge or pursue a related degree, and employs an industry-centered perspective.

✦ Table of Contents

Preface
Acknowledgments
Contents
About the Author
1: Introduction
1.1 The Business Value Proposition
1.2 The Enhanced Value
1.3 The Age of Big Data
1.4 From Business Intelligence to Business Analytics
1.5 Dynamic Process Flow
1.6 A Paradigm Shift
1.7 Evolving Technologies
1.8 Data Modeling: Structured or Unstructured
1.9 Much Information Little Intelligence
1.10 Measuring Information: Bits and Bytes
1.11 The Competing Vs of Big Data
1.12 The Competitive Edge
2: High Fidelity Data
2.1 The Telephone Game: Data Sourcing and Transmission
2.2 From Audiophile to Dataphile
2.3 Interference and Data Contamination (Signal-to-Noise)
2.4 Monitoring, Detecting, Resolving, and Reporting
Monitoring
Detecting
Resolving
Reporting
3: Connecting the Dots
3.1 The Internet of Things (IoT)
3.2 Data Aggregation
3.3 The Golden Copy
4: Real-Time Analytics
4.1 Faster Processing
4.2 Analytics on the Run
4.3 Streaming Data
5: Predicting the Future
5.1 A Crystal Ball
5.2 Machine Learning and Artificial Intelligence
5.3 Smart Reporting and Actionable Insights
Data Context
Units, Scales, Legends, Labels, Titles, and References
Data Presentation
5.4 Codeless Coding and Visual Modeling
6: The New Company
6.1 The Mythical Profile
6.2 Organizational Structure
6.3 Software and Technology
7: Data Ethics: Facts and Fiction
7.1 Virtual or Fake Reality
7.2 Privacy Matters
7.3 Data Governance and Audit
7.4 Who Owns the Data
7.5 The Coming of COVID-19
8: Role of Academia, Industry, and Research
8.1 Revamping Academia
8.2 Bridging the Gap
8.3 STEAM for All
8.4 A Capstone Template

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