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Duration 14 hours
Course Outline
Introduction to Data Warehousing
- Definition of a data warehouse
- Advantages of warehousing for analytics and reporting
- Support for warehousing via Oracle Database 19c
Oracle Data Warehouse Structure
- Core elements: source data, ETL, staging, presentation
- Comparison of star and snowflake schemas
- Oracle tools for managing DW environments
Data Modeling Principles
- Fact and dimension tables
- Surrogate keys and granularity
- Fundamentals of slowly changing dimensions (SCD)
Introduction to ETL Workflows
- Overview of ETL and tools supported by Oracle
- Batch vs. real-time loading
- Challenges in data integration and quality
Query and Reporting Principles
- Basics of OLAP vs. OLTP workloads
- How Oracle optimizes queries for data warehouses
- Introduction to materialized views and aggregates
Planning and Scaling Oracle Warehouses
- Hardware and architectural considerations
- Benefits 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 DW projects
- Initiation of a pilot implementation
Summary and Next Steps
Requirements
- Familiarity with relational databases
- Foundational knowledge of SQL
- No prior experience with Oracle data warehousing is necessary
Target Audience
- Data analysts
- IT personnel planning to engage with Oracle data warehousing
- Business intelligence teams
Testimonials (1)
good explanation on each points and provide assignment for practices.