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Duration 21 hours
Course Outline
Overview of Oracle Data Warehousing
- Data warehouse architecture and applicable use cases
- Comparing OLTP and OLAP workloads
- Essential components of an Oracle DW solution
Designing Warehouse Schemas
- Dimensional modeling through star and snowflake schemas
- Structure and function of fact and dimension tables
- Managing slowly changing dimensions (SCD)
Data Loading and ETL Methodologies
- Designing ETL processes using SQL and PL/SQL
- Leveraging external tables and SQL*Loader
- Implementing incremental loads and CDC (Change Data Capture)
Partitioning and Performance Enhancement
- Partitioning techniques: range, list, and hash
- Utilizing query pruning and parallel processing
- Best practices for partition-wise joins
Compression and Storage Optimization
- Applying hybrid columnar compression
- Formulating data archival strategies
- Balancing performance and cost through storage optimization
Advanced Query and Analytics Capabilities
- Implementing materialized views and query rewrite
- Employing analytical SQL functions such as RANK, LAG, and ROLLUP
- Conducting time-based analysis and real-time reporting
Monitoring and Tuning the Data Warehouse
- Tracking and assessing query performance
- Managing resource usage and workloads
- Developing indexing strategies specific to warehousing
Recap and Future Steps
Requirements
- A solid grasp of SQL and core Oracle database fundamentals
- Practical experience with Oracle 12c/19c in either administrative or development capacities
- Foundational knowledge of data warehousing principles
Target Audience
- Data warehouse developers
- Database administrators
- Business intelligence specialists
Testimonials (1)
good explanation on each points and provide assignment for practices.
