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Duration 14 hours
Course Outline
Fundamentals of Data Warehousing
- Defining the data warehouse
- Advantages of warehousing for analytics and reporting
- Oracle Database 19c capabilities for warehousing support
Architecture of Oracle Data Warehouses
- Core components: source data, ETL, staging, and presentation layers
- Comparing star and snowflake schemas
- Oracle tools for managing data warehouse environments
Principles of Data Modeling
- Utilizing fact and dimension tables
- The role of surrogate keys and data granularity
- Basic concepts of Slowly Changing Dimensions (SCD)
Overview of ETL Workflows
- Introduction to ETL and supported Oracle tools
- Comparing batch loading with real-time loading
- Addressing challenges in data integration and quality assurance
Querying and Reporting Essentials
- Distinguishing OLAP and OLTP workloads
- Oracle’s approach to query optimization for data warehouses
- Introduction to materialized views and aggregate tables
Planning and Scaling Oracle Warehouses
- Considerations regarding hardware and system architecture
- Benefits of partitioning and data compression
- Overview of Oracle licensing and feature sets
Practical Applications and Best Practices
- Case studies on warehouse design
- Best practices for orchestrating Oracle DW projects
- Initiating a pilot implementation
Recap and Future Directions
Requirements
- Familiarity with relational database systems
- Fundamental proficiency in SQL
- No previous experience with Oracle data warehousing is necessary
Target Audience
- Data analysts
- IT personnel preparing to engage with Oracle data warehousing solutions
- Business intelligence teams
Testimonials (1)
good explanation on each points and provide assignment for practices.
