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.

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.