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Duration 21 hours
Course Outline
Introduction to Oracle Data Warehousing
- Data warehouse architecture and applicable use cases
- Distinguishing between OLTP and OLAP workloads
- Essential components of an Oracle DW solution
Warehouse Schema Design
- Dimensional modeling through 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
- Utilizing external tables and SQL*Loader
- Implementing incremental loads and Change Data Capture (CDC)
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 techniques
- Strategies for data archival
- Optimizing storage to balance performance and cost
Advanced Query and Analytics Features
- Materialized views and query rewrite capabilities
- Analytical SQL functions such as RANK, LAG, and ROLLUP
- Time-based analysis and real-time reporting mechanisms
Monitoring and Tuning the Data Warehouse
- Monitoring query performance metrics
- Managing resource usage and workload distribution
- Indexing strategies tailored for warehousing environments
Summary and Next Steps
Requirements
- A solid understanding of SQL and fundamental Oracle database concepts
- Experience working with Oracle 12c/19c in either an administrative or development capacity
- Foundational knowledge of data warehousing principles
Target Audience
- Data warehouse developers
- Database administrators
- Business intelligence professionals
Testimonials (1)
good explanation on each points and provide assignment for practices.
