Course Outline

Introduction to Oracle Data Warehousing

  • Data warehouse architecture and use cases
  • OLTP vs OLAP workloads
  • Core components of an Oracle DW solution

Warehouse Schema Design

  • Dimensional modeling: star and snowflake schemas
  • Fact and dimension tables
  • Handling slowly changing dimensions (SCD)

Data Loading and ETL Strategies

  • ETL process design using SQL and PL/SQL
  • Using external tables and SQL*Loader
  • Incremental loads and CDC (Change Data Capture)

Partitioning and Performance

  • Partitioning methods: range, list, 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 performance and cost

Advanced Query and Analytics Features

  • Materialized views and query rewrite
  • 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 for warehousing

Summary and Next Steps

Requirements

  • An understanding of SQL and Oracle database fundamentals
  • Experience working with Oracle 12c/19c in an administrative or development role
  • Basic knowledge of data warehousing concepts

Audience

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

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  • Flexible Schedule: Dates and times adapted to your team's agenda.
  • Format: Online (live), In-company (at your offices), or Hybrid.
Investment

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