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Duration 14 hours (2 days)
Course Outline
Foundations of Data Warehousing
- Defining a data warehouse
- Advantages of warehousing for analytics and reporting
- Support for warehousing within Oracle Database 19c
Oracle Data Warehouse Architecture
- Core components: source data, ETL, staging areas, and presentation layers
- Comparison of star and snowflake schemas
- Oracle utilities for managing DW environments
Data Modeling Principles
- Fact and dimension tables
- Surrogate keys and data granularity
- Fundamentals of Slowly Changing Dimensions (SCD)
Overview of ETL Processes
- ETL overview and Oracle-supported tools
- Batch versus real-time loading strategies
- Obstacles in data integration and quality assurance
Querying and Reporting Fundamentals
- Distinguishing between OLAP and OLTP workloads
- How Oracle optimizes queries for data warehouse scenarios
- Introduction to materialized views and aggregation
Planning and Scaling Oracle Warehouses
- Considerations for hardware and architecture
- Benefits of partitioning and compression
- Overview of Oracle licensing and features
Real-World Applications and Best Practices
- Case studies on warehouse design
- Best practices for planning Oracle DW projects
- Initiating a pilot implementation
Recap and Recommended Next Steps
Requirements
- Familiarity with relational databases
- Foundational knowledge of SQL
- No previous experience with Oracle data warehousing is necessary
Target Audience
- Data analysts
- IT personnel intending to engage with Oracle data warehousing
- Business intelligence teams
Testimonials (1)
good explanation on each points and provide assignment for practices.