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Course Outline
Fundamentals of Data Warehousing
- Defining the role of a data warehouse.
- Advantages of warehousing for analytical and reporting purposes.
- Support capabilities of Oracle Database 19c for warehousing.
Structure of Oracle Data Warehouses
- Core elements: source data, ETL, staging, and presentation layers.
- Comparing star and snowflake schema designs.
- Oracle utilities for administering DW environments.
Principles of Data Modeling
- The function of fact and dimension tables.
- Understanding surrogate keys and data granularity.
- Introduction to slowly changing dimensions (SCD).
Overview of ETL Workflows
- ETL overview and tools supported by Oracle.
- Differences between batch and real-time loading methods.
- Common obstacles in data integration and quality management.
Querying and Reporting Principles
- Distinguishing between OLAP and OLTP workloads.
- Oracle’s approach to optimizing queries for data warehouses.
- Introduction to materialized views and aggregate functions.
Designing and Scaling Oracle Warehouses
- Considerations for hardware and system architecture.
- Benefits of partitioning and data compression.
- Summary of Oracle licensing and available features.
Practical Applications and Industry Standards
- Examination of real-world warehouse design scenarios.
- Recommended practices for planning Oracle DW projects.
- Initiating a pilot implementation phase.
Conclusion and Future Directions
Requirements
- Familiarity with relational database systems
- Foundational proficiency in SQL
- No existing expertise in Oracle data warehousing is necessary
Intended Learners
- Data analysts
- IT personnel preparing to engage with Oracle data warehousing solutions
- Business intelligence teams
14 Hours
Testimonials (1)
good explanation on each points and provide assignment for practices.