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Duration 14 hours
Course Outline
Data Warehousing Fundamentals
- Defining the concept of a data warehouse
- The advantages of warehousing for analytics and reporting
- The role of Oracle Database 19c in supporting warehousing initiatives
Oracle Data Warehouse Architecture
- Essential components: source data, ETL, staging, and presentation layers
- Comparing star and snowflake schema designs
- Oracle utilities for managing DW environments
Data Modelling Principles
- Fact and dimension tables
- The use of surrogate keys and defining granularity
- An introduction to Slowly Changing Dimensions (SCD)
Overview of ETL Processes
- ETL concepts and the range of Oracle-supported tools
- Distinguishing between batch and real-time data loading
- Addressing challenges in data integration and quality assurance
Query and Reporting Strategies
- Understanding the differences between OLAP and OLTP workloads
- How Oracle optimises queries for data warehouse performance
- An introduction to materialised views and aggregate structures
Planning and Scaling Oracle Warehouses
- Considering hardware and architectural requirements
- The benefits of partitioning and data compression
- An overview of Oracle licensing and relevant features
Applications and Best Practices
- Case studies in warehouse design
- Best practices for planning Oracle DW projects
- Initiating a pilot implementation
Conclusion and Future Directions
Requirements
- A working comprehension of relational databases
- Foundational knowledge of SQL
- No previous experience with Oracle data warehousing is necessary
Target Audience
- Data analysts
- IT personnel intending to engage with Oracle data warehousing
- Business intelligence teams
Testimonials (1)
good explanation on each points and provide assignment for practices.
