Data Storage, Data Processing and Data Analysis
Buch, Englisch, 256 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 441 g
ISBN: 978-3-030-78823-0
Verlag: Springer International Publishing
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.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Bankwirtschaft
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Wirtschaftsinformatik
- Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Versicherungswirtschaft
- Mathematik | Informatik EDV | Informatik Digital Lifestyle Online Banking & Finance
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
- Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsinformatik, SAP, IT-Management
Weitere Infos & Material
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.