Course Outline

Introduction to Data Warehousing

  • What is 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, presentation
  • Star vs snowflake schemas
  • Oracle tools for managing DW environments

Data Modeling Concepts

  • Fact and dimension tables
  • Surrogate keys and granularity
  • Slowly changing dimensions (SCD) basics

Introduction to ETL Processes

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

Query and Reporting Concepts

  • 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 architecture considerations
  • Partitioning and compression benefits
  • 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

  • An understanding of relational databases
  • Basic knowledge of SQL
  • No prior experience with Oracle data warehousing required

Audience

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

Delivery Options

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