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 Duration 14 hours

Course Outline

Fundamentals of Data Warehousing

  • Defining the concept of a data warehouse
  • The value of warehousing for analytics and reporting capabilities
  • How Oracle Database 19c supports warehousing needs

Architecture of Oracle Data Warehouses

  • Core elements: source data, ETL processes, staging areas, and presentation layers
  • Comparing star and snowflake schema designs
  • Utilizing Oracle tools to manage data warehouse environments

Principles of Data Modeling

  • Roles of fact and dimension tables
  • Understanding surrogate keys and data granularity
  • Introduction to slowly changing dimensions (SCD)

Overview of ETL Processes

  • General ETL concepts and Oracle-supported integration tools
  • Differentiating between batch and real-time data loading
  • Addressing challenges in data integration and quality assurance

Querying and Reporting Strategies

  • Distinctions between OLAP and OLTP workloads
  • How Oracle optimizes query execution for data warehouses
  • Overview of materialized views and aggregate structures

Planning and Scaling Oracle Warehouses

  • Key hardware and architectural considerations
  • Advantages of partitioning and data compression
  • Overview of Oracle licensing and available features

Application Scenarios and Best Practices

  • Review of warehouse design case studies
  • Recommended practices for planning Oracle DW projects
  • Steps for initiating a pilot implementation

Recap and Future Directions

Requirements

  • Familiarity with relational database systems
  • Foundational proficiency in SQL
  • No previous hands-on experience with Oracle data warehousing is necessary

Target Audience

  • Data analysts
  • IT personnel preparing to engage with Oracle data warehousing solutions
  • Business intelligence specialists and teams

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