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Course Outline
Introduction to Oracle Data Warehousing
- Overview of data warehouse architecture and use cases.
- Comparison of OLTP and OLAP workloads.
- Core components of an Oracle DW solution.
Warehouse Schema Design
- Dimensional modeling: star and snowflake schemas.
- Structure and usage of fact and dimension tables.
- Techniques for handling slowly changing dimensions (SCD).
Data Loading and ETL Strategies
- Designing ETL processes using SQL and PL/SQL.
- Implementation of external tables and SQL*Loader.
- Strategies for incremental loads and CDC (Change Data Capture).
Partitioning and Performance
- Partitioning methods: range, list, and hash.
- Query pruning and parallel processing techniques.
- Partition-wise joins and associated best practices.
Compression and Storage Optimization
- Hybrid columnar compression.
- Data archival strategies.
- Optimizing storage configurations for performance and cost efficiency.
Advanced Query and Analytics Features
- Utilization of materialized views and query rewrite.
- Analytical SQL functions (RANK, LAG, ROLLUP).
- Time-based analysis and real-time reporting capabilities.
Monitoring and Tuning the Data Warehouse
- Monitoring query performance.
- Managing resource usage and workload management.
- Indexing strategies tailored for warehousing.
Summary and Next Steps
Requirements
- A solid understanding of SQL and Oracle database fundamentals.
- Prior experience working with Oracle 12c/19c in an administrative or development capacity.
- Foundational knowledge of data warehousing concepts.
Target Audience
- Data warehouse developers.
- Database administrators.
- Business intelligence professionals.
21 Hours
