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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 modelling: star and snowflake schemas
- Structuring fact and dimension tables
- Managing slowly changing dimensions (SCD)
Data Loading and ETL Strategies
- ETL process design leveraging SQL and PL/SQL
- Utilising external tables and SQL*Loader
- Implementing incremental loads and CDC (Change Data Capture)
Partitioning and Performance
- Partitioning methodologies: range, list, and hash
- Query pruning and parallel processing
- Partition-wise joins and industry best practices
Compression and Storage Optimisation
- Hybrid columnar compression
- Data archival strategies
- Optimising storage for enhanced performance and cost efficiency
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 specific to warehousing
Summary and Next Steps
Requirements
- A solid grasp of SQL and fundamental Oracle database concepts
- Hands-on experience working with Oracle 12c/19c in an administrative or development capacity
- Foundational knowledge of data warehousing principles
Audience
- Data warehouse developers
- Database administrators
- Business intelligence specialists
Testimonials (1)
good explanation on each points and provide assignment for practices.
