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Course Outline
Introduction to Oracle Data Warehousing
- Data warehouse architecture and common use cases
- Differences between OLTP and OLAP workloads
- Core components of an Oracle Data Warehouse solution
Warehouse Schema Design
- Dimensional modeling: star and snowflake schemas
- 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
- Incremental loads and Change Data Capture (CDC)
Partitioning and Performance
- Partitioning methods: range, list, and hash
- Query pruning and parallel processing
- Partition-wise joins and best practices
Compression and Storage Optimization
- Hybrid columnar compression
- Data archival strategies
- Optimizing storage for both performance and cost efficiency
Advanced Query and Analytics Features
- Materialized views and query rewrite capabilities
- 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 specifically for data warehousing
Summary and Next Steps
Requirements
- A solid understanding of SQL and fundamental Oracle database concepts
- Experience working with Oracle 12c/19c in administrative or development roles
- Basic knowledge of data warehousing principles
Target Audience
- Data warehouse developers
- Database administrators
- Business intelligence professionals
21 Hours
Testimonials (2)
good explanation on each points and provide assignment for practices.
Piseth Ben - ACLEDA Bank Plc.
Course - Oracle Database 19c: SQL Tuning Workshop
Learning about a new tool, the practices help a lot in understanding the topics, and that was what I liked the most.
David Vargas Alpizar - BANCO BAC SAN JOSE S.A
Course - Oracle Database 19c: Administration
Machine Translated