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Course Outline

Introduction to Oracle Data Warehousing

  • Data warehouse architecture and common use cases
  • Differences between OLTP and OLAP workloads
  • Core components of an Oracle Data Warehouse solution

Warehouse Schema Design

  • Dimensional modeling: 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
  • Utilizing external tables and SQL*Loader
  • Incremental loads and Change Data Capture (CDC)

Partitioning and Performance

  • Partitioning methods: range, list, and hash
  • Query pruning and parallel processing
  • Partition-wise joins and best practices

Compression and Storage Optimization

  • Hybrid columnar compression
  • Data archival strategies
  • Optimizing storage for both performance and cost efficiency

Advanced Query and Analytics Features

  • Materialized views and query rewrite capabilities
  • Analytical SQL functions (RANK, LAG, ROLLUP)
  • Time-based analysis and real-time reporting

Monitoring and Tuning the Data Warehouse

  • Monitoring query performance
  • Resource usage and workload management
  • Indexing strategies specifically for data warehousing

Summary and Next Steps

Requirements

  • A solid understanding of SQL and fundamental Oracle database concepts
  • Experience working with Oracle 12c/19c in administrative or development roles
  • Basic knowledge of data warehousing principles

Target Audience

  • Data warehouse developers
  • Database administrators
  • Business intelligence professionals
 21 Hours

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