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Course Outline

Introduction to Data Warehousing

  • Defining a data warehouse.
  • Benefits of warehousing in analytics and reporting.
  • Oracle Database 19c support for warehousing.

Oracle Data Warehouse Architecture

  • Core components: source data, ETL, staging, presentation.
  • Star schema versus snowflake schema.
  • Oracle tools for managing DW environments.

Data Modeling Concepts

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

Introduction to ETL Processes

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

Query and Reporting Concepts

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

Planning and Scaling Oracle Warehouses

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

Use Cases and Best Practices

  • Warehouse design case studies.
  • Best practices for planning Oracle DW projects.
  • Initiating a pilot implementation.

Summary and Next Steps

Requirements

  • Familiarity with relational databases
  • Fundamental knowledge of SQL
  • No prior experience with Oracle data warehousing is required

Target Audience

  • Data analysts
  • IT staff planning to engage with Oracle data warehousing
  • Business intelligence teams
 14 Hours

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