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Duration 21 hours
Course Outline
Introduction to Oracle Data Warehousing
- Data warehouse architecture and practical applications.
- Distinguishing between OLTP and OLAP workloads.
- Essential components of an Oracle data warehouse solution.
Warehouse Schema Design
- Dimensional modeling using star and snowflake schemas.
- Structure and role of fact and dimension tables.
- Managing slowly changing dimensions (SCD).
Data Loading and ETL Strategies
- Designing ETL processes using SQL and PL/SQL.
- Leveraging external tables and SQL*Loader for data ingestion.
- Implementing incremental loads and Change Data Capture (CDC).
Partitioning and Performance
- Partitioning techniques: range, list, and hash.
- Optimizing through query pruning and parallel processing.
- Utilizing partition-wise joins and adhering to best practices.
Compression and Storage Optimization
- Implementing hybrid columnar compression.
- Developing data archival strategies.
- Balancing storage usage for optimal performance and cost efficiency.
Advanced Query and Analytics Features
- Working with materialized views and query rewriting.
- Applying 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 workload distribution.
- Selecting appropriate indexing strategies for warehousing environments.
Summary and Next Steps
Requirements
- Proficiency in SQL and a solid grasp of Oracle database fundamentals.
- Hands-on 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.