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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 techniques: star and snowflake schemas
- Structure and role of fact and dimension tables
- Managing slowly changing dimensions (SCD)
Data Loading and ETL Strategies
- Designing ETL processes utilizing SQL and PL/SQL
- Employing external tables and SQL*Loader for data ingestion
- Implementing incremental loads and Change Data Capture (CDC)
Partitioning and Performance
- Partitioning approaches: range, list, and hash
- Leveraging query pruning and parallel processing
- Best practices for partition-wise joins
Compression and Storage Optimization
- Hybrid columnar compression methods
- Strategies for data archival
- Balancing storage optimization for performance and cost efficiency
Advanced Query and Analytics Features
- Utilizing materialized views and automatic query rewrite
- Applying analytical SQL functions such as RANK, LAG, and 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
- Developing indexing strategies specific to warehousing
Summary and Next Steps
Requirements
- A solid grasp of SQL and fundamental Oracle database concepts
- Practical experience 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 specialists
21 Hours
Testimonials (1)
good explanation on each points and provide assignment for practices.