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Duration 14 hours
Course Outline
Introduction to Data Warehousing
- Defining the data warehouse
- Advantages of warehousing in analytics and reporting
- Warehousing capabilities within Oracle Database 19c
Oracle Data Warehouse Architecture
- Essential components: source data, ETL, staging, and presentation layers
- Comparison of star and snowflake schemas
- Oracle tools for administering data warehouse environments
Data Modeling Concepts
- Fact and dimension tables
- Surrogate keys and data granularity
- Introduction to slowly changing dimensions (SCD)
Overview of ETL Processes
- Overview of ETL and Oracle-integrated tools
- Distinction between batch and real-time data loading
- Addressing data integration and quality challenges
Query and Reporting Concepts
- Understanding OLAP versus OLTP workloads
- How Oracle optimizes queries for data warehousing
- Introduction to materialized views and aggregates
Planning and Scaling Oracle Warehouses
- Considerations for hardware and architecture
- Benefits of partitioning and compression
- Overview of Oracle licensing and features
Case Studies and Best Practices
- Analysis of warehouse design case studies
- Best practices for planning Oracle data warehouse projects
- Initiating a pilot implementation
Summary and Future Directions
Requirements
- Familiarity with relational database systems
- Fundamental understanding of SQL
- Previous experience with Oracle data warehousing is not necessary
Target Audience
- Data analysts
- IT personnel involved in Oracle data warehousing initiatives
- Business intelligence teams
Testimonials (1)
good explanation on each points and provide assignment for practices.
