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Duration 14 hours
Course Outline
Introduction to Data Warehousing
- Defining the data warehouse concept
- Advantages of warehousing for analytics and reporting
- Warehousing capabilities in Oracle Database 19c
Oracle Data Warehouse Architecture
- Essential components: source data, ETL, staging, and presentation layers
- Comparison of star and snowflake schemas
- Oracle tools for managing data warehouse environments
Data Modelling Concepts
- Structure of fact and dimension tables
- Understanding surrogate keys and data granularity
- Basics of slowly changing dimensions (SCD)
Overview of ETL Processes
- Introduction to ETL and Oracle-supported tooling
- Batch loading versus real-time data ingestion
- Addressing challenges in data integration and quality
Querying and Reporting Principles
- Distinguishing between OLAP and OLTP workloads
- Methods Oracle uses to optimize warehouse queries
- Introduction to materialized views and aggregated data
Planning and Scaling Oracle Warehouses
- Hardware and architectural requirements
- Advantages of partitioning and data compression
- Overview of Oracle licensing and feature sets
Applications and Best Practices
- Real-world warehouse design case studies
- Best practices for structuring Oracle data warehouse projects
- Initiating a pilot implementation
Wrap-up and Future Directions
Requirements
- Familiarity with relational database systems
- Foundational understanding of SQL
- No prior experience with Oracle data warehousing is necessary
Target Audience
- Data analysts
- IT professionals intending to engage with Oracle data warehousing solutions
- Business intelligence teams
Testimonials (1)
good explanation on each points and provide assignment for practices.
