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 Duration 14 hours

Course Outline

Fundamentals of Data Warehousing

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

Architecture of the Oracle Data Warehouse

  • Essential elements: source data, ETL, staging, and presentation layers
  • Comparison of star and snowflake schemas
  • Oracle utilities for managing DW environments

Principles of Data Modeling

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

Overview of ETL Processes

  • Introduction to ETL and Oracle-integrated tools
  • Contrast between batch and real-time loading
  • Common hurdles in data integration and quality assurance

Concepts in Querying and Reporting

  • Distinguishing between OLAP and OLTP workloads
  • Mechanisms Oracle uses to optimize warehouse queries
  • Introduction to materialized views and aggregate data

Strategy and Scaling for Oracle Warehouses

  • Considerations regarding hardware and architectural design
  • Advantages of partitioning and data compression
  • Overview of Oracle licensing and feature sets

Real-World Applications and Best Practices

  • Case studies on warehouse design
  • Recommended practices for initiating Oracle DW projects
  • Steps for launching a pilot implementation

Recap and Future Directions

Requirements

  • Familiarity with relational database systems
  • Fundamental 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 warehouse environments
  • Business intelligence teams

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