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Course Outline
Introduction to Oracle Data Warehousing
- Data warehouse architecture and applicable use cases
- Distinguishing OLTP and OLAP workloads
- Essential components of an Oracle DW solution
Warehouse Schema Design
- Dimensional modeling techniques, including star and snowflake schemas
- Designing fact and dimension tables
- Managing slowly changing dimensions (SCD)
Data Loading and ETL Strategies
- Designing ETL processes with SQL and PL/SQL
- Utilizing external tables and SQL*Loader
- Implementing incremental loads and CDC (Change Data Capture)
Partitioning and Performance
- Partitioning techniques: range, list, and hash
- Applying query pruning and parallel processing
- Best practices for partition-wise joins
Compression and Storage Optimization
- Leveraging hybrid columnar compression
- Strategies for data archival
- Optimizing storage to balance performance and cost
Advanced Query and Analytics Features
- Using materialized views and query rewrite
- Applying analytical SQL functions (RANK, LAG, ROLLUP)
- Conducting time-based analysis and real-time reporting
Monitoring and Tuning the Data Warehouse
- Monitoring query performance metrics
- Managing resource usage and workloads
- Developing indexing strategies for warehousing
Summary and Next Steps
Requirements
- A solid grasp of SQL and fundamental Oracle database concepts
- Experience with Oracle 12c/19c in an administrative or development capacity
- Foundational knowledge of data warehousing principles
Target Audience
- Data warehouse developers
- Database administrators
- Business intelligence specialists
21 Hours
Testimonials (1)
good explanation on each points and provide assignment for practices.
