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Course Outline
Foundations of Data Warehousing
- Defining the concept of a data warehouse
- The role of warehousing in enhancing analytics and reporting
- Warehousing capabilities provided by Oracle Database 19c
Oracle Data Warehouse Structural Design
- Core elements: source data, ETL, staging, and presentation layers
- Comparing star and snowflake schema structures
- Oracle utilities for administering DW environments
Principles of Data Modeling
- The function of fact and dimension tables
- Understanding surrogate keys and data granularity
- Introductory concepts of Slowly Changing Dimensions (SCD)
Overview of ETL Workflows
- Introduction to ETL and supported Oracle tools
- Differentiating batch processing from real-time loading
- Addressing challenges in data integration and quality control
Querying and Reporting Mechanisms
- Distinguishing between OLAP and OLTP workloads
- Methods Oracle uses to optimize warehouse queries
- Basic introduction to materialized views and aggregates
Strategy and Scalability for Oracle Warehouses
- Considerations for hardware and system architecture
- Advantages of partitioning and data compression
- Summary of Oracle licensing and feature set
Practical Applications and Best Practices
- Case studies on warehouse design
- Recommendations for planning Oracle DW initiatives
- Initiating a pilot implementation phase
Conclusion and Future Pathways
Requirements
- Familiarity with relational database systems
- Foundational proficiency in SQL
- No previous hands-on experience with Oracle data warehousing is necessary
Target Audience
- Data analysts
- IT professionals intending to engage with Oracle data warehousing
- Business intelligence teams
14 Hours
Testimonials (1)
good explanation on each points and provide assignment for practices.
