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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.

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