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Course Outline

Introduction to Oracle Data Warehousing

  • Overview of data warehouse architecture and use cases
  • Distinctions between OLTP and OLAP workloads
  • Key components of an Oracle DW solution

Warehouse Schema Design

  • Dimensional modeling: star and snowflake schemas
  • Understanding 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
  • Implementing incremental loads and CDC (Change Data Capture)

Partitioning and Performance

  • Exploring partitioning methods: range, list, and hash
  • Techniques for query pruning and parallel processing
  • Best practices for partition-wise joins

Compression and Storage Optimization

  • Implementing hybrid columnar compression
  • Developing data archival strategies
  • Optimizing storage for enhanced performance and cost-efficiency

Advanced Query and Analytics Features

  • Utilizing materialized views and query rewrite capabilities
  • Applying analytical SQL functions (RANK, LAG, 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
  • Establishing effective indexing strategies for warehousing

Summary and Next Steps

Requirements

  • Proficiency in SQL and a solid understanding of Oracle database fundamentals
  • Prior experience working with Oracle 12c/19c in administrative or development capacities
  • Foundational knowledge of data warehousing concepts

Target Audience

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

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