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
- Understanding data warehouse architecture and its application scenarios.
- Distinguishing between OLTP and OLAP workloads.
- Key components of an Oracle data warehouse solution.
Warehouse Schema Design
- Dimensional modeling techniques, including star and snowflake schemas.
- Structuring fact and dimension tables.
- Managing slowly changing dimensions (SCD).
Data Loading and ETL Strategies
- Designing ETL workflows using SQL and PL/SQL.
- Utilizing external tables and SQL*Loader for data ingestion.
- Implementing incremental loads and Change Data Capture (CDC).
Partitioning and Performance
- Partitioning strategies: range, list, and hash.
- Leveraging query pruning and parallel processing.
- Best practices for partition-wise joins.
Compression and Storage Optimization
- Application of hybrid columnar compression.
- Strategies for data archival.
- Balancing storage optimization for performance and cost efficiency.
Advanced Query and Analytics Features
- Using materialized views and automatic query rewrite.
- Advanced analytical SQL functions such as RANK, LAG, and ROLLUP.
- Conducting time-based analysis and generating real-time reports.
Monitoring and Tuning the Data Warehouse
- Techniques for monitoring query performance.
- Managing resource usage and workload distribution.
- Effective indexing strategies for data warehousing.
Summary and Next Steps
Requirements
- Proficiency in SQL and core Oracle database concepts.
- Practical experience with Oracle 12c or 19c in an administrative or development capacity.
- Foundational understanding of data warehousing principles.
Target Audience
- Data warehouse developers.
- Database administrators.
- Business intelligence specialists.
21 Hours
Testimonials (1)
good explanation on each points and provide assignment for practices.