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Course Outline
Introduction to Oracle Data Warehousing
- Data warehouse architecture and applicable use cases
- Comparison of OLTP and OLAP workloads
- Core components of an Oracle DW solution
Warehouse Schema Design
- Dimensional modeling: star and snowflake schemas
- Fact and dimension tables
- Managing slowly changing dimensions (SCD)
Data Loading and ETL Strategies
- ETL process design utilizing SQL and PL/SQL
- Leveraging external tables and SQL*Loader
- Incremental loads and CDC (Change Data Capture)
Partitioning and Performance
- Partitioning methods: range, list, hash
- Query pruning and parallel processing
- Partition-wise joins and best practices
Compression and Storage Optimization
- Hybrid columnar compression
- Data archival strategies
- Optimizing storage for both performance and cost
Advanced Query and Analytics Features
- Materialized views and query rewrite
- Analytical SQL functions (RANK, LAG, ROLLUP)
- Time-based analysis and real-time reporting
Monitoring and Tuning the Data Warehouse
- Monitoring query performance
- Resource usage and workload management
- Indexing strategies for warehousing
Summary and Next Steps
Requirements
- A solid understanding of SQL and Oracle database fundamentals
- Practical experience 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
Testimonials (1)
good explanation on each points and provide assignment for practices.
