Modern Data Warehousing in Banking

Overview

Explore modern data warehousing in banking, covering evolution, components, compliance, design, implementation frameworks, and future trends for effective financial reporting and analytics.

Syllabus

• Introduction to Data Warehousing in Banking
Overview of data warehousing concepts
Importance in the banking sector
Key objectives and benefits
• Evolution of Data Warehousing in Banking
Historical developments
Transition from traditional to modern data warehousing
Impact of big data and cloud technologies
• Key Components of Modern Data Warehouses
Data sources and data integration
Data storage solutions
Data processing and ETL (Extract, Transform, Load)
Data governance and quality
• Compliance and Regulatory Requirements
Overview of financial regulations
Role of data warehousing in compliance
Case studies of compliance failures and successes
• Design Principles of Data Warehouses
Data modeling techniques
Security and privacy considerations
Scalability and performance optimization
• Implementation Frameworks
Best practices for deployment
Tools and technologies for implementation (e.g., SQL, NoSQL, cloud platforms)
Migration strategies for legacy systems
• Data Warehousing for Financial Reporting
Integration with BI (Business Intelligence) tools
Dashboards and visualization techniques
Real-time vs. batch processing for reporting
• Analytics and Decision Making
Role of data warehousing in predictive analytics
Use cases of advanced analytics in banking
Machine learning integration
• Future Trends in Data Warehousing
Emerging technologies in data storage and processing
The role of AI and machine learning
Impact of blockchain and distributed ledger technologies
• Course Conclusion
Summary of key learning points
Future opportunities and career paths in data warehousing
Course feedback and next steps

Subjects

Business