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Course Outline
Introduction to Data Warehousing
- Definition of a data warehouse
- Benefits of warehousing in analytics and reporting
- Oracle Database 19c support for warehousing
Oracle Data Warehouse Architecture
- Key components: source data, ETL, staging, 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 granularity
- Basics of slowly changing dimensions (SCD)
Introduction to ETL Processes
- Overview of ETL and Oracle-supported tools
- Batch loading versus real-time loading
- Challenges in data integration and quality
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 architectural considerations
- Advantages 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 data warehouse projects
- Initiating a pilot implementation
Summary and Next Steps
Requirements
- A foundational understanding of relational databases
- Basic knowledge of SQL
- No prior experience with Oracle data warehousing is required
Audience
- Data analysts
- IT personnel intending to work with Oracle data warehousing
- Business intelligence teams
14 Hours
Testimonials (1)
good explanation on each points and provide assignment for practices.
