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Duration 14 hours
Course Outline
Fundamentals of Data Warehousing
- Definition and scope of a data warehouse
- Advantages of warehousing in analytical and reporting contexts
- How Oracle Database 19c facilitates warehousing capabilities
Oracle Data Warehouse Structural Design
- Core elements: source data, ETL, staging, and presentation layers
- Comparing star and snowflake schema structures
- Oracle utilities for managing data warehouse environments
Data Modeling Principles
- The role of fact and dimension tables
- Understanding surrogate keys and data granularity
- Basics of slowly changing dimensions (SCD)
Overview of ETL Processes
- Introduction to ETL and Oracle-validated tools
- Distinctions between batch and real-time data loading
- Addressing challenges in data integration and quality assurance
Querying and Reporting Principles
- Differentiating OLAP and OLTP workloads
- Methods Oracle uses to optimize data warehouse queries
- Introduction to materialized views and data aggregation
Strategic Planning and Scaling Oracle Warehouses
- Considerations regarding hardware and architectural design
- Benefits of partitioning and data compression
- Overview of Oracle licensing and available features
Practical Applications and Best Practices
- Review of warehouse design case studies
- Recommended approaches for planning Oracle DW initiatives
- Initiating a pilot implementation project
Recap and Future Directions
Requirements
- A fundamental understanding of relational databases
- Foundational knowledge of SQL
- Prior experience with Oracle data warehousing is not mandatory
Target Audience
- Data analysts
- IT professionals planning to engage with Oracle data warehousing solutions
- Business intelligence teams
Testimonials (1)
good explanation on each points and provide assignment for practices.