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Course Outline

Data Warehousing Fundamentals

  • Defining the concept of a data warehouse
  • Advantages of warehousing for analytics and reporting tasks
  • How Oracle Database 19c facilitates warehousing

Structure of Oracle Data Warehouses

  • Essential elements: source data, ETL, staging, and presentation layers
  • Comparing star and snowflake schema designs
  • Oracle utilities for managing DW environments

Data Modeling Principles

  • Fact and dimension tables
  • Concepts of surrogate keys and data granularity
  • Introduction to Slowly Changing Dimensions (SCD)

Overview of ETL Workflows

  • Introduction to ETL and tools supported by Oracle
  • Batch processing versus real-time data loading
  • Common challenges in data integration and quality management

Querying and Reporting Principles

  • Differences between OLAP and OLTP workloads
  • Oracle’s methods for optimizing warehouse queries
  • Introductory concepts of materialized views and aggregates

Planning and Expanding Oracle Warehouses

  • Considerations for hardware and architecture
  • The benefits of partitioning and compression
  • Overview of Oracle licensing and key features

Application Examples and Recommended Practices

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

Recap and Future Directions

Requirements

  • A grasp of relational database concepts
  • Fundamental proficiency in SQL
  • No previous exposure to Oracle data warehousing is necessary

Intended Learners

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

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Provisional Upcoming Courses (Require 5+ participants)

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