This book, the third one of three volumes, focuses on data and the actions around data, like storage and processing. The angle shifts over the volumes from a business-driven approach in "Disruption and DNA" to a strong technical focus in "Data Storage, Processing and Analysis", leaving "Digitalization and Machine Learning Applications" with the business and technical aspects in-between. In the last volume of the series, "Data Storage, Processing and Analysis", the shifts in the way we deal with data are addressed.

<p>Part I. Big Data and Special Databases

Chapter 1. Data Lineage
Chapter 2. Digitization and MongoDB - The Art of Possible
Chapter 3. Graph Databases
Chapter 4. Data Tiering Options with SAP HANA and Usage in a Hadoop Scenario
Part II. Streaming
Chapter 5. Kafka - Real-Time Streaming for the Finance Industry
Chapter 6. Architecture Patterns - Batch & Real-Time Capabilities
Chapter 7. Kafka - A Practical Implementation of Intraday Liquidity Risk Management
Part III. Data: A View on Meta Aspects
Chapter 8. Data Sustainability - A Thorough Consideration
Chapter 9. Special Data for Insurance Companies
Chapter 10. Data Protection - Putting the Brakes on Digitalization Processes? - Part IV. Distributed Ledger
Chapter 11. Digital Identity Management - for Humans Only? - Part V. Machine Learning and Deep Learning
Chapter 12. Overview Machine Learning and Deep Learning Frameworks
Chapter 13. Methods of Machine Learning
Part VI. Summary.</p>