Dieses Buch behandelt auf 91 Seiten diverse Big Data Use Cases, stellt Überlegungen zur richtigen Daten-Architektur an, behandelt extensiv wachsende Bereiche wie Social Media oder GIS, und deckt einige der heiklen Themen rund um Datenschutz auf. [...]
This book covers a number of Big Data use cases, architecture considerations, and the rise of emerging observation spaces (social, geospatial, etc.) and covers some of the thorny issues around data privacy. An organization’s available obser- vation space (data they can get their hands on within law and policy) is growing faster than their ability to make sense of it. As organizations struggle to keep up, they are being forced to reconsider what kind of infrastructure will be required to harness Big Data.
Going forward, organizations must be able to sense and respond to trans- actions happening now and must be able to deeply reflect over what has been observed—this deep reflection is a necessary activity to discover relevant weak signal and emerging patterns. Following fairly recent experiments involving how humans piece jigsaw puzzles together, I have witnessed the criticality of tightly coupling discovery from deep reflection right back into the real-time sense and respond analytics. In fact, as the feedback loop gets faster and tighter, it signifi- cantly enhances the discovery.
The organizations that figure out how to make sense of what they learn fast enough to do something about it while it is happening will be more competitive.
Contents:
- Chapter 1: Introduction
- Chapter 2: Drivers for Big Data?
- Chapter 3: Big Data Analytics Applications
- Chapter 4: Architecture Components
- Chapter 5: Advanced Analytics Platform
- Chapter 6: Implementation of Big Data Analytics
- Chapter 7: Closing Thoughts
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