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Course Outline
Foundamentals of Data Warehousing
- Defining the concept of a data warehouse
- The advantages of warehousing for analytics and reporting
- How Oracle Database 19c supports warehousing operations
Oracle Data Warehouse Architecture
- Essential components: source data, ETL, staging, and presentation layers
- Comparing star and snowflake schema designs
- Oracle tools utilized for managing data warehouse environments
Data Modeling Principles
- The role 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 supported Oracle tools
- Distinguishing between batch and real-time data loading
- Addressing challenges in data integration and quality assurance
Querying and Reporting Strategies
- Differentiating OLAP and OLTP workloads
- Methods Oracle employs to optimize warehouse queries
- Introduction to materialized views and aggregate functions
Planning and Scaling Oracle Warehouses
- Considerations for hardware and architectural design
- Benefits of partitioning and data compression
- Overview of Oracle licensing and feature sets
Real-world Applications and Best Practices
- Case studies on warehouse design
- Best practices for planning Oracle DW projects
- Initiating a pilot implementation
Recap and Future Pathways
Requirements
- Familiarity with relational database structures
- Foundational proficiency in SQL
- No prior hands-on experience with Oracle data warehousing is necessary
Target Audience
- 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.
