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Duration 14 hours
Course Outline
Fundamentals of Data Warehousing
- Defining the data warehouse concept
- Advantages of warehousing for analytics and reporting
- Warehousing capabilities in Oracle Database 19c
Oracle Data Warehouse Architecture
- Core elements: source data, ETL, staging, and presentation layers
- Comparison of star and snowflake schema designs
- Oracle tools for administering DW environments
Data Modeling Principles
- Understanding fact and dimension tables
- Surrogate keys and data granularity
- Basics of Slowly Changing Dimensions (SCD)
Overview of ETL Workflows
- Introduction to ETL and compatible Oracle tools
- Batch loading versus real-time data ingestion
- Common challenges in data integration and quality assurance
Querying and Reporting Principles
- Distinguishing between OLAP and OLTP workloads
- Methods Oracle uses to optimize warehouse queries
- Introduction to materialized views and data aggregation
Planning and Scaling Oracle Warehouses
- Hardware and architectural considerations
- Advantages of partitioning and data compression
- Overview of Oracle licensing and available features
Use Cases and Best Practices
- Analytical case studies on warehouse design
- Best practices for planning Oracle DW initiatives
- Initiation of a pilot implementation strategy
Recap and Future Directions
Requirements
- Familiarity with relational database structures
- Foundational proficiency in SQL
- No previous experience with Oracle data warehousing is necessary
Target Audience
- Data analysts
- IT personnel intending to engage with Oracle warehousing solutions
- Business intelligence teams
Testimonials (1)
good explanation on each points and provide assignment for practices.
