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Course Outline

Introduction to Data Warehousing

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

Oracle Data Warehouse Architecture

  • Key components: source data, ETL, staging, and presentation layers.
  • Star versus snowflake schemas.
  • 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 versus real-time loading.
  • Challenges in data integration and quality.

Query and Reporting Concepts

  • Basics of OLAP versus OLTP workloads.
  • How Oracle optimises queries for data warehouses.
  • Introduction to materialised views and aggregates.

Planning and Scaling Oracle Warehouses

  • Hardware and architecture considerations.
  • Benefits of partitioning and compression.
  • Oracle licensing and feature overview.

Use Cases and Best Practices

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

Summary and Next Steps

Requirements

  • A foundational understanding of relational databases.
  • Basic knowledge of SQL.
  • No prior experience with Oracle data warehousing is required.

Audience

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

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