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Duration 14 hours
Course Outline
Foundations of Data Warehousing
- Defining the concept of a data warehouse
- Advantages of warehousing for analytics and reporting purposes
- Support features provided by Oracle Database 19c for warehousing
Structure of Oracle Data Warehouses
- Essential elements: source data, ETL, staging, and presentation layers
- Comparison between star and snowflake schema designs
- Utilization of Oracle tools for managing DW environments
Principles of Data Modeling
- Structure of fact and dimension tables
- Concepts of surrogate keys and data granularity
- Fundamentals of Slowly Changing Dimensions (SCD)
Overview of ETL Workflows
- General view of ETL and tools supported by Oracle
- Distinction between batch and real-time data loading
- Obstacles related to data integration and data quality
Querying and Reporting Principles
- Distinguishing OLAP from OLTP workloads
- Methods Oracle uses to optimize queries for data warehouses
- Overview of materialized views and aggregation techniques
Strategy and Expansion of Oracle Warehouses
- Considerations regarding hardware and architectural design
- Advantages derived from partitioning and compression
- Summary of Oracle licensing and available features
Practical Applications and Recommended Approaches
- Review of warehouse design case studies
- Best practices for planning Oracle DW initiatives
- Initiating a pilot implementation project
Recap and Future Directions
Requirements
- Familiarity with relational database systems
- Foundational grasp of SQL
- No previous hands-on experience with Oracle data warehousing is necessary
Target Participants
- Data analysts
- IT professionals preparing to engage with Oracle data warehousing
- Business intelligence teams
Testimonials (1)
good explanation on each points and provide assignment for practices.
