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Duration 14 hours
Course Outline
Fundamentals of Data Warehousing
- Defining the concept of a data warehouse
- The value of warehousing in analytics and reporting
- How Oracle Database 19c supports warehouse operations
Architecture of the Oracle Data Warehouse
- Essential elements: source data, ETL, staging, and presentation layers
- Comparison of star and snowflake schemas
- Oracle utilities for managing DW environments
Principles of Data Modeling
- Fact and dimension tables
- The role of surrogate keys and granularity
- Basics of slowly changing dimensions (SCD)
Overview of ETL Processes
- Introduction to ETL and Oracle-integrated tools
- Contrast between batch and real-time loading
- Common hurdles in data integration and quality assurance
Concepts in Querying and Reporting
- Distinguishing between OLAP and OLTP workloads
- Mechanisms Oracle uses to optimize warehouse queries
- Introduction to materialized views and aggregate data
Strategy and Scaling for Oracle Warehouses
- Considerations regarding hardware and architectural design
- Advantages of partitioning and data compression
- Overview of Oracle licensing and feature sets
Real-World Applications and Best Practices
- Case studies on warehouse design
- Recommended practices for initiating Oracle DW projects
- Steps for launching a pilot implementation
Recap and Future Directions
Requirements
- Familiarity with relational database systems
- Fundamental proficiency in SQL
- No previous hands-on experience with Oracle data warehousing is necessary
Target Audience
- Data analysts
- IT personnel preparing to engage with Oracle warehouse environments
- Business intelligence teams
Testimonials (1)
good explanation on each points and provide assignment for practices.