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Duration 21 hours
Course Outline
Introduction to Oracle Data Warehousing
- Understanding data warehouse architecture and its various use cases
- Distinguishing between OLTP and OLAP workloads
- Identifying the core components of an Oracle DW solution
Warehouse Schema Design
- Dimensional modeling techniques: star and snowflake schemas
- Structure and usage of fact and dimension tables
- Managing slowly changing dimensions (SCD)
Data Loading and ETL Strategies
- Designing ETL processes utilizing SQL and PL/SQL
- Implementing data ingestion via external tables and SQL*Loader
- Executing incremental loads and Change Data Capture (CDC)
Partitioning and Performance
- Partitioning methods: range, list, and hash
- Optimizing query pruning and parallel processing
- Best practices for partition-wise joins
Compression and Storage Optimization
- Utilizing hybrid columnar compression
- Developing effective data archival strategies
- Balancing storage optimization for performance and cost efficiency
Advanced Query and Analytics Features
- Leveraging materialized views and query rewrite capabilities
- 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 analyzing query performance
- Managing resource usage and workload distribution
- Implementing indexing strategies tailored for warehousing
Summary and Next Steps
Requirements
- Solid grasp of SQL and core Oracle database concepts
- Practical experience with Oracle 12c/19c in administrative or development capacities
- Foundational understanding of data warehousing principles
Intended Audience
- Data warehouse developers
- Database administrators
- Business intelligence specialists
Testimonials (1)
good explanation on each points and provide assignment for practices.
