The Digital Journey of Banking and Insurance, Volume III (eBook, PDF)
Data Storage, Data Processing and Data Analysis
Redaktion: Liermann, Volker; Stegmann, Claus
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The Digital Journey of Banking and Insurance, Volume III (eBook, PDF)
Data Storage, Data Processing and Data Analysis
Redaktion: Liermann, Volker; Stegmann, Claus
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Gathers the most relevant methods used in the bank and insurance digitalization
Showcases how to deal with data and data architectures including streaming technology
Addresses data regulatory requirements like GDPR or data lineage¿
¿
- Geräte: PC
- ohne Kopierschutz
- eBook Hilfe
- Größe: 8.57MB
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Gathers the most relevant methods used in the bank and insurance digitalization
Addresses data regulatory requirements like GDPR or data lineage¿
¿
Showcases how to deal with data and data architectures including streaming technology
Addresses data regulatory requirements like GDPR or data lineage¿
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Springer International Publishing
- Seitenzahl: 256
- Erscheinungstermin: 27. Oktober 2021
- Englisch
- ISBN-13: 9783030788216
- Artikelnr.: 62836998
- Verlag: Springer International Publishing
- Seitenzahl: 256
- Erscheinungstermin: 27. Oktober 2021
- Englisch
- ISBN-13: 9783030788216
- Artikelnr.: 62836998
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Volker Liermann, Partner at ifb group, worked in the banking industry for over two decades, primarily focusing on financial risk management. Throughout his career, he has focused on developing integrated and comprehensive frameworks to help organizations correctly project risk at a strategic and tactical line of business and departmental level. He has also focused on developing frameworks to integrate stress testing and regulatory stress tests. In recent years, his focus has shifted to digitalization, machine learning and digital processes including improvements to classical financial and non-financial risk management. He has a background in economics and a degree in mathematics from the University of Bonn. Claus Stegmann has as Co-CEO of ifb group - an international consulting firm - acquired extensive know-how over the last three decades in the financial industry regarding finance transformation, risk management and regulatory compliance. He is intensively engaged with the current challenges of the financial industry, which result from strong changes to customer behavior, a changing competitive environment and new technologies due to digitalization. He has also co-authored books on Stress Tests in Banks, Basel III as well as Digitalization in the Finance Industry, and graduated from Business School at the University of Passau, Germany.
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.
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.







