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 Duration 21 hours

Course Outline

Foundations of Oracle Data Warehousing

  • Architectural patterns and practical applications for data warehouses
  • Distinguishing between OLTP and OLAP workloads
  • Key elements of an Oracle DW implementation

Designing Warehouse Schemas

  • Dimensional modeling techniques: star and snowflake structures
  • Roles of fact and dimension tables
  • Managing slowly changing dimensions (SCD)

Data Ingestion and ETL Approaches

  • Designing ETL workflows leveraging SQL and PL/SQL
  • Utilizing external tables and SQL*Loader for data movement
  • Implementing incremental loads and CDC (Change Data Capture)

Partitioning and Performance Enhancement

  • Various partitioning strategies: range, list, and hash
  • Optimizing through query pruning and parallel processing
  • Executing partition-wise joins and adhering to best practices

Compression and Storage Efficiency

  • Implementing hybrid columnar compression
  • Planning data archival strategies
  • Balancing storage optimization for both performance and cost efficiency

Advanced Querying and Analytics Capabilities

  • Leveraging materialized views and automated query rewrite
  • Applying analytical SQL functions such as RANK, LAG, and ROLLUP
  • Conducting time-based analysis and enabling real-time reporting

Monitoring and Data Warehouse Tuning

  • Tracking and assessing query performance
  • Managing resource allocation and workload balance
  • Developing effective indexing strategies for warehousing environments

Recap and Future Directions

Requirements

  • Solid comprehension of SQL and fundamental Oracle database concepts
  • Practical experience with Oracle 12c/19c in administrative or development capacities
  • Foundational awareness of data warehousing principles

Target Audience

  • Data warehouse developers
  • Database administrators
  • Business intelligence specialists

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