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Course Outline
Data Warehousing Fundamentals
- Defining the concept of a data warehouse
- Advantages of warehousing for analytics and reporting tasks
- How Oracle Database 19c facilitates warehousing
Structure of Oracle Data Warehouses
- Essential elements: source data, ETL, staging, and presentation layers
- Comparing star and snowflake schema designs
- Oracle utilities for managing DW environments
Data Modeling Principles
- Fact and dimension tables
- Concepts of surrogate keys and data granularity
- Introduction to Slowly Changing Dimensions (SCD)
Overview of ETL Workflows
- Introduction to ETL and tools supported by Oracle
- Batch processing versus real-time data loading
- Common challenges in data integration and quality management
Querying and Reporting Principles
- Differences between OLAP and OLTP workloads
- Oracle’s methods for optimizing warehouse queries
- Introductory concepts of materialized views and aggregates
Planning and Expanding Oracle Warehouses
- Considerations for hardware and architecture
- The benefits of partitioning and compression
- Overview of Oracle licensing and key features
Application Examples and Recommended Practices
- Case studies on warehouse design
- Best practices for planning Oracle DW projects
- Steps for initiating a pilot implementation
Recap and Future Directions
Requirements
- A grasp of relational database concepts
- Fundamental proficiency in SQL
- No previous exposure to Oracle data warehousing is necessary
Intended Learners
- Data analysts
- IT personnel intending to engage with Oracle data warehousing solutions
- Business intelligence teams
14 Hours
Testimonials (1)
good explanation on each points and provide assignment for practices.