Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Introduction to Data Warehousing
- Defining a data warehouse
- The value of warehousing in analytics and reporting
- How Oracle Database 19c supports warehousing capabilities
Oracle Data Warehouse Architecture
- Essential components: source data, ETL, staging, and presentation layers
- Comparison of star and snowflake schemas
- Oracle utilities for managing DW environments
Data Modeling Principles
- Fact and dimension tables
- Surrogate keys and data granularity
- Foundations of slowly changing dimensions (SCD)
Overview of ETL Processes
- Introduction to ETL and Oracle-compatible tools
- Batch loading versus real-time loading
- Obstacles related to data integration and quality
Querying and Reporting Fundamentals
- Distinguishing OLAP from OLTP workloads
- Methods by which Oracle optimizes queries for data warehouses
- Introduction to materialized views and aggregate tables
Planning and Scaling Oracle Warehouses
- Considerations for hardware and system architecture
- The benefits of partitioning and compression
- Overview of Oracle licensing and features
Use Cases and Best Practices
- Case studies in warehouse design
- Recommended practices for planning Oracle DW projects
- Initiating a pilot implementation
Conclusion and Recommended Next Steps
Requirements
- Familiarity with relational databases
- Foundational knowledge of SQL
- No previous experience with Oracle data warehousing is necessary
Target Audience
- Data analysts
- IT personnel intending to engage with Oracle data warehousing
- Business intelligence teams
Testimonials (1)
good explanation on each points and provide assignment for practices.
