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Course Outline

Introduction to Oracle Data Warehousing

  • Data warehouse architectures and applicable use cases
  • Distinguishing between OLTP and OLAP workloads
  • Essential elements of an Oracle DW solution

Designing Warehouse Schemas

  • Dimensional modeling utilizing star and snowflake schemas
  • Structure of fact and dimension tables
  • Managing slowly changing dimensions (SCD)

Strategies for Data Loading and ETL

  • Designing ETL processes with SQL and PL/SQL
  • Implementation of external tables and SQL*Loader
  • Executing incremental loads and CDC (Change Data Capture)

Partitioning and Performance Management

  • Partitioning approaches: range, list, and hash
  • Techniques for query pruning and parallel processing
  • Application of partition-wise joins and best practices

Optimization of Compression and Storage

  • Utilizing hybrid columnar compression
  • Establishing data archival strategies
  • Balancing storage for optimal performance and cost efficiency

Advanced Query and Analytical Features

  • Employment of materialized views and query rewrite
  • Application of analytical SQL functions (RANK, LAG, ROLLUP)
  • Conducting time-based analysis and real-time reporting

Monitoring and Tuning the Data Warehouse

  • Monitoring of query performance
  • Management of resource usage and workloads
  • Development of indexing strategies for warehousing

Conclusion and Future Steps

Requirements

  • Proficiency in SQL and foundational Oracle database concepts
  • Prior experience with Oracle 12c/19c in administrative or development capacities
  • Foundational understanding of data warehousing principles

Target Audience

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

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  • Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
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  • Format: Online (live), In-company (at your offices), or Hybrid.
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