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Course Outline

Overview of Data Warehousing

  • Defining the data warehouse
  • Advantages of warehousing for analytics and reporting
  • Warehousing support provided by Oracle Database 19c

Architecture of Oracle Data Warehouses

  • Primary components: source data, ETL, staging, and presentation layers
  • Comparing star and snowflake schemas
  • Oracle tools for managing data warehouse environments

Principles of Data Modeling

  • Fact and dimension tables
  • Surrogate keys and data granularity
  • Fundamentals of slowly changing dimensions (SCD)

Introduction to ETL Workflows

  • Overview of ETL and tools supported by Oracle
  • Batch processing versus real-time loading
  • Challenges associated with data integration and quality

Concepts in Querying and Reporting

  • Understanding OLAP and OLTP workloads
  • Methods for Oracle query optimization in data warehouses
  • Introduction to materialized views and aggregates

Strategic Planning and Scaling for Oracle Warehouses

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

Application Scenarios and Best Practices

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

Recap and Future Directions

Requirements

  • Familiarity with relational database systems
  • Foundational proficiency in 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
 14 Hours

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