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 Duration 14 hours (2 days)

Course Outline

Foundations of Data Warehousing

  • Defining a data warehouse
  • Advantages of warehousing for analytics and reporting
  • Support for warehousing within Oracle Database 19c

Oracle Data Warehouse Architecture

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

Data Modeling Principles

  • Fact and dimension tables
  • Surrogate keys and data granularity
  • Fundamentals of Slowly Changing Dimensions (SCD)

Overview of ETL Processes

  • ETL overview and Oracle-supported tools
  • Batch versus real-time loading strategies
  • Obstacles in data integration and quality assurance

Querying and Reporting Fundamentals

  • Distinguishing between OLAP and OLTP workloads
  • How Oracle optimizes queries for data warehouse scenarios
  • Introduction to materialized views and aggregation

Planning and Scaling Oracle Warehouses

  • Considerations for hardware and architecture
  • Benefits of partitioning and compression
  • Overview of Oracle licensing and features

Real-World Applications and Best Practices

  • Case studies on warehouse design
  • Best practices for planning Oracle DW projects
  • Initiating a pilot implementation

Recap and Recommended Next Steps

Requirements

  • Familiarity with relational databases
  • Foundational knowledge of SQL
  • No previous experience with Oracle data warehousing is necessary

Target Audience

  • Data analysts
  • IT personnel intending to engage with Oracle data warehousing
  • Business intelligence teams

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