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Course Outline
Introduction to Data Warehousing
- Defining a data warehouse
- Advantages of warehousing for analytics and reporting
- Oracle Database 19c capabilities for warehousing
Oracle Data Warehouse Architecture
- Core components: source data, ETL, staging areas, and presentation layers
- Comparing star and snowflake schemas
- Oracle tools for managing data warehouse environments
Data Modeling Concepts
- Fact and dimension tables
- Surrogate keys and levels of granularity
- Introduction to slowly changing dimensions (SCD)
Introduction to ETL Processes
- Overview of ETL and Oracle-supported tools
- Batch versus real-time data loading
- Challenges associated with data integration and quality
Query and Reporting Concepts
- Fundamentals of OLAP versus OLTP workloads
- Methods Oracle uses to optimize queries for data warehouses
- 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
Use Cases and Best Practices
- Case studies on warehouse design
- Best practices for planning Oracle DW projects
- Initiating a pilot implementation
Summary and Next Steps
Requirements
- Understanding of relational databases
- Fundamental knowledge of SQL
- No prior experience with Oracle data warehousing is required
Target Audience
- Data analysts
- IT personnel planning to engage with Oracle data warehousing
- Business intelligence teams
14 Hours
Testimonials (1)
good explanation on each points and provide assignment for practices.
