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Course Outline
Introduction to Oracle Data Warehousing
- Overview of data warehouse architecture and use cases
- Distinctions between OLTP and OLAP workloads
- Key components of an Oracle DW solution
Warehouse Schema Design
- Dimensional modeling: star and snowflake schemas
- Understanding fact and dimension tables
- Managing slowly changing dimensions (SCD)
Data Loading and ETL Strategies
- Designing ETL processes using SQL and PL/SQL
- Leveraging external tables and SQL*Loader
- Implementing incremental loads and CDC (Change Data Capture)
Partitioning and Performance
- Exploring partitioning methods: range, list, and hash
- Techniques for query pruning and parallel processing
- Best practices for partition-wise joins
Compression and Storage Optimization
- Implementing hybrid columnar compression
- Developing data archival strategies
- Optimizing storage for enhanced performance and cost-efficiency
Advanced Query and Analytics Features
- Utilizing materialized views and query rewrite capabilities
- Applying analytical SQL functions (RANK, LAG, ROLLUP)
- Conducting time-based analysis and real-time reporting
Monitoring and Tuning the Data Warehouse
- Tracking and analyzing query performance
- Managing resource usage and workload distribution
- Establishing effective indexing strategies for warehousing
Summary and Next Steps
Requirements
- Proficiency in SQL and a solid understanding of Oracle database fundamentals
- Prior experience working with Oracle 12c/19c in administrative or development capacities
- 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.
