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Course Outline
Introduction to Data Warehousing
- What is a data warehouse?
- Benefits of warehousing in analytics and reporting
- Oracle Database 19c support for warehousing
Oracle Data Warehouse Architecture
- Key components: source data, ETL, staging, presentation
- Star vs snowflake schemas
- Oracle tools for managing data warehouse environments
Data Modelling Concepts
- Fact and dimension tables
- Surrogate keys and granularity
- Basics of slowly changing dimensions (SCD)
Introduction to ETL Processes
- Overview of ETL and Oracle-supported tools
- Batch vs real-time loading
- Challenges in data integration and data quality
Query and Reporting Concepts
- Basics of OLAP vs OLTP workloads
- How Oracle optimises queries for data warehouses
- Introduction to materialised views and aggregates
Planning and Scaling Oracle Warehouses
- Hardware and architecture 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 data warehouse projects
- Getting started with a pilot implementation
Summary and Next Steps
Requirements
- An understanding of relational databases
- Basic knowledge of SQL
- No prior experience with Oracle data warehousing required
Audience
- Data analysts
- IT staff planning to work with Oracle data warehousing
- Business intelligence teams
14 Hours
Testimonials (1)
good explanation on each points and provide assignment for practices.