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.
Course Outline
Introduction to Oracle Data Warehousing
- Data warehouse architecture and practical use cases.
- Comparing OLTP and OLAP workloads.
- Core components of an Oracle DW solution.
Warehouse Schema Design
- Dimensional modelling: star and snowflake schemas.
- Fact and dimension tables.
- Managing slowly changing dimensions (SCD).
Data Loading and ETL Strategies
- Designing ETL processes using SQL and PL/SQL.
- Utilising external tables and SQL*Loader.
- Implementing incremental loads and Change Data Capture (CDC).
Partitioning and Performance
- Partitioning methods: range, list, and hash.
- Query pruning and parallel processing techniques.
- Partition-wise joins and best practices.
Compression and Storage Optimisation
- Hybrid columnar compression.
- Data archival strategies.
- Optimising storage for both performance and cost-efficiency.
Advanced Query and Analytics Features
- Materialised views and query rewriting.
- Analytical SQL functions such as RANK, LAG, and ROLLUP.
- Time-based analysis and real-time reporting.
Monitoring and Tuning the Data Warehouse
- Monitoring query performance.
- Managing resource usage and workload.
- Indexing strategies tailored for warehousing.
Summary and Next Steps
Requirements
- A solid understanding of SQL and Oracle database fundamentals.
- Prior experience working with Oracle 12c/19c in an administrative or development capacity.
- Foundational knowledge of data warehousing concepts.
Audience
- Data warehouse developers.
- Database administrators.
- Business intelligence professionals.
21 Hours
Testimonials (1)
good explanation on each points and provide assignment for practices.
