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 Duration 14 hours

Course Outline

Fundamentals of Data Warehousing

  • Definition and scope of a data warehouse
  • Advantages of warehousing in analytical and reporting contexts
  • How Oracle Database 19c facilitates warehousing capabilities

Oracle Data Warehouse Structural Design

  • Core elements: source data, ETL, staging, and presentation layers
  • Comparing star and snowflake schema structures
  • Oracle utilities for managing data warehouse environments

Data Modeling Principles

  • The role of fact and dimension tables
  • Understanding surrogate keys and data granularity
  • Basics of slowly changing dimensions (SCD)

Overview of ETL Processes

  • Introduction to ETL and Oracle-validated tools
  • Distinctions between batch and real-time data loading
  • Addressing challenges in data integration and quality assurance

Querying and Reporting Principles

  • Differentiating OLAP and OLTP workloads
  • Methods Oracle uses to optimize data warehouse queries
  • Introduction to materialized views and data aggregation

Strategic Planning and Scaling Oracle Warehouses

  • Considerations regarding hardware and architectural design
  • Benefits of partitioning and data compression
  • Overview of Oracle licensing and available features

Practical Applications and Best Practices

  • Review of warehouse design case studies
  • Recommended approaches for planning Oracle DW initiatives
  • Initiating a pilot implementation project

Recap and Future Directions

Requirements

  • A fundamental understanding of relational databases
  • Foundational knowledge of SQL
  • Prior experience with Oracle data warehousing is not mandatory

Target Audience

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

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