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Course Outline
Introduction to Oracle Data Warehousing
- Data warehouse architecture and applicable use cases
- Distinctions between OLTP and OLAP workloads
- Essential components of an Oracle DW solution
Designing Warehouse Schemas
- Dimensional modeling: star and snowflake schema structures
- Management of fact and dimension tables
- Strategies for handling slowly changing dimensions (SCD)
Data Loading and ETL Strategies
- Designing ETL processes using SQL and PL/SQL
- Utilizing external tables and SQL*Loader
- Implementing incremental loads and CDC (Change Data Capture)
Partitioning and Performance Optimization
- Various partitioning methods: range, list, and hash
- Techniques for query pruning and parallel processing
- Partition-wise joins and associated best practices
Compression and Storage Efficiency
- Hybrid columnar compression techniques
- Strategies for data archival
- Balancing storage optimization for performance and cost
Advanced Query and Analytics Capabilities
- Materialized views and query rewrite mechanisms
- Analytical SQL functions (RANK, LAG, ROLLUP)
- Time-based analysis and real-time reporting
Monitoring and Tuning the Data Warehouse
- Tracking and assessing query performance
- Managing resource usage and workloads
- Indexing strategies tailored for warehousing
Summary and Recommended Next Steps
Requirements
- A solid grasp of SQL and core Oracle database principles
- Practical experience with Oracle 12c/19c in administrative or development capacities
- Foundational knowledge of data warehousing concepts
Target Audience
- Data warehouse developers
- Database administrators
- Business intelligence specialists
21 Hours
Testimonials (1)
good explanation on each points and provide assignment for practices.
