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Duration 21 hours
Course Outline
Introduction to Oracle Data Warehousing
- Data warehouse architecture and practical applications
- Comparing OLTP and OLAP workloads
- Key components of an Oracle DW solution
Warehouse Schema Design
- Dimensional modelling: star and snowflake schemas
- Fact and dimension table structures
- Managing slowly changing dimensions (SCD)
Data Loading and ETL Strategies
- Designing ETL processes using SQL and PL/SQL
- Utilising external tables and SQL*Loader
- Implementing incremental loads and CDC (Change Data Capture)
Partitioning and Performance
- Partitioning approaches: range, list, and hash
- Query pruning and parallel processing techniques
- Partition-wise joins and industry best practices
Compression and Storage Optimisation
- Hybrid columnar compression methods
- Data archival strategies
- Optimising storage for improved performance and cost efficiency
Advanced Query and Analytics Features
- Materialised views and query rewriting
- Analytical SQL functions (RANK, LAG, ROLLUP)
- Time-based analysis and real-time reporting capabilities
Monitoring and Tuning the Data Warehouse
- Tracking and analysing query performance
- Resource allocation and workload management
- Indexing strategies specific to data warehousing
Summary and Next Steps
Requirements
- Solid grasp of SQL and core Oracle database principles
- Practical experience with Oracle 12c/19c in either administrative or development capacities
- Foundational understanding of data warehousing concepts
Target Audience
- Data warehouse developers
- Database administrators
- Business intelligence specialists
Testimonials (1)
good explanation on each points and provide assignment for practices.
