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Course Outline
Introduction to Data Warehousing
- What constitutes a data warehouse?
- Benefits of warehousing for analytics and reporting
- Oracle Database 19c support for warehousing
Oracle Data Warehouse Architecture
- Key components: source data, ETL processes, staging areas, and presentation layers
- Star schema versus snowflake schema
- Oracle tools for managing data warehouse environments
Data Modeling Concepts
- Fact and dimension tables
- Surrogate keys and levels of granularity
- Fundamentals of slowly changing dimensions (SCD)
Introduction to ETL Processes
- Overview of ETL and tools supported by Oracle
- Batch loading versus real-time loading
- Challenges in data integration and quality assurance
Query and Reporting Concepts
- Fundamentals of OLAP versus OLTP workloads
- How Oracle optimizes queries for data warehouses
- Introduction to materialized views and aggregates
Planning and Scaling Oracle Warehouses
- Hardware and architecture considerations
- Advantages of partitioning and compression
- Overview of Oracle licensing and features
Use Cases and Best Practices
- Case studies in warehouse design
- Best practices for planning Oracle data warehouse projects
- Steps for initiating a pilot implementation
Summary and Next Steps
Requirements
- A solid understanding of relational databases
- Basic proficiency in SQL
- No prior experience with Oracle data warehousing is necessary
Target Audience
- Data analysts
- IT professionals planning to work with Oracle data warehousing
- Business intelligence teams
14 Hours
Testimonials (1)
good explanation on each points and provide assignment for practices.
