Description
Book SynopsisThis 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.
Table of ContentsPart 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.
