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Duration 21 hours
Course Outline
Foundations of 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 through star and snowflake schemas
- Structure and usage of fact and dimension tables
- Managing slowly changing dimensions (SCD)
Data Loading and ETL Methodologies
- Designing ETL processes using SQL and PL/SQL
- Implementing external tables and SQL*Loader
- Executing incremental loads and Change Data Capture (CDC)
Partitioning and Performance Enhancement
- Partitioning strategies: range, list, and hash
- Applying query pruning and parallel processing
- Utilizing partition-wise joins and adhering to best practices
Compression and Storage Optimization
- Implementing hybrid columnar compression
- Developing data archival strategies
- Balancing storage optimization for performance and cost efficiency
Advanced Query and Analytics Capabilities
- Leveraging materialized views and query rewrite features
- Utilizing 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 workloads
- Defining indexing strategies specific to warehousing
Recap and Future Directions
Requirements
- A solid grasp of SQL and fundamental Oracle database concepts
- Practical experience with Oracle 12c/19c in either administrative or development capacities
- Foundational knowledge of data warehousing principles
Target Audience
- Data warehouse developers
- Database administrators
- Business intelligence specialists
Testimonials (1)
good explanation on each points and provide assignment for practices.
