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Course Outline

Fundamentals of Data Warehousing

  • Defining the role of a data warehouse.
  • Advantages of warehousing for analytical and reporting purposes.
  • Support capabilities of Oracle Database 19c for warehousing.

Structure of Oracle Data Warehouses

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

Principles of Data Modeling

  • The function of fact and dimension tables.
  • Understanding surrogate keys and data granularity.
  • Introduction to slowly changing dimensions (SCD).

Overview of ETL Workflows

  • ETL overview and tools supported by Oracle.
  • Differences between batch and real-time loading methods.
  • Common obstacles in data integration and quality management.

Querying and Reporting Principles

  • Distinguishing between OLAP and OLTP workloads.
  • Oracle’s approach to optimizing queries for data warehouses.
  • Introduction to materialized views and aggregate functions.

Designing and Scaling Oracle Warehouses

  • Considerations for hardware and system architecture.
  • Benefits of partitioning and data compression.
  • Summary of Oracle licensing and available features.

Practical Applications and Industry Standards

  • Examination of real-world warehouse design scenarios.
  • Recommended practices for planning Oracle DW projects.
  • Initiating a pilot implementation phase.

Conclusion and Future Directions

Requirements

  • Familiarity with relational database systems
  • Foundational proficiency in SQL
  • No existing expertise in Oracle data warehousing is necessary

Intended Learners

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

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