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 Duration 14 hours

Course Outline

Introduction to Data Warehousing

  • Definition of a data warehouse
  • Advantages of warehousing for analytics and reporting
  • Support for warehousing via Oracle Database 19c

Oracle Data Warehouse Structure

  • Core elements: source data, ETL, staging, presentation
  • Comparison of star and snowflake schemas
  • Oracle tools for managing DW environments

Data Modeling Principles

  • Fact and dimension tables
  • Surrogate keys and granularity
  • Fundamentals of slowly changing dimensions (SCD)

Introduction to ETL Workflows

  • Overview of ETL and tools supported by Oracle
  • Batch vs. real-time loading
  • Challenges in data integration and quality

Query and Reporting Principles

  • Basics of OLAP vs. OLTP workloads
  • How Oracle optimizes queries for data warehouses
  • Introduction to materialized views and aggregates

Planning and Scaling Oracle Warehouses

  • Hardware and architectural considerations
  • Benefits of partitioning and compression
  • Overview of Oracle licensing and features

Use Cases and Best Practices

  • Case studies on warehouse design
  • Best practices for planning Oracle DW projects
  • Initiation of a pilot implementation

Summary and Next Steps

Requirements

  • Familiarity with relational databases
  • Foundational knowledge of SQL
  • No prior experience with Oracle data warehousing is necessary

Target Audience

  • Data analysts
  • IT personnel planning to engage with Oracle data warehousing
  • Business intelligence teams

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