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Course Outline
Introduction to Data Warehousing
- What constitutes a data warehouse?
- Benefits of warehousing in analytics and reporting.
- Oracle Database 19c support for warehousing.
Oracle Data Warehouse Architecture
- Key components: source data, ETL, staging, and presentation layers.
- Star versus snowflake schemas.
- 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 versus real-time loading.
- Challenges in data integration and quality.
Query and Reporting Concepts
- Basics of OLAP versus OLTP workloads.
- How Oracle optimises queries for data warehouses.
- Introduction to materialised views and aggregates.
Planning and Scaling Oracle Warehouses
- Hardware and architecture considerations.
- Benefits of partitioning and compression.
- Oracle licensing and feature overview.
Use Cases and Best Practices
- Warehouse design case studies.
- Best practices for planning Oracle DW projects.
- Getting started with a pilot implementation.
Summary and Next Steps
Requirements
- A foundational understanding of relational databases.
- Basic knowledge of SQL.
- No prior experience with Oracle data warehousing is required.
Audience
- Data analysts.
- IT staff planning to work with Oracle data warehousing.
- Business intelligence teams.
14 Hours
Testimonials (1)
good explanation on each points and provide assignment for practices.