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Course Outline
Introduction to Data Warehousing
- Defining a data warehouse.
- Benefits of warehousing in analytics and reporting.
- Oracle Database 19c support for warehousing.
Oracle Data Warehouse Architecture
- Core components: source data, ETL, staging, presentation.
- Star schema versus snowflake schema.
- Oracle tools for managing DW environments.
Data Modeling 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 loading versus real-time loading.
- Challenges in data integration and quality.
Query and Reporting Concepts
- Fundamentals of OLAP versus OLTP workloads.
- How Oracle optimizes queries for data warehouses.
- Introduction to materialized 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
- Warehouse design case studies.
- Best practices for planning Oracle DW projects.
- Initiating a pilot implementation.
Summary and Next Steps
Requirements
- Familiarity with relational databases
- Fundamental knowledge of SQL
- No prior experience with Oracle data warehousing is required
Target Audience
- Data analysts
- IT staff planning to engage with Oracle data warehousing
- Business intelligence teams
14 Hours
Testimonials (1)
good explanation on each points and provide assignment for practices.