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 Duration 14 hours

Course Outline

Introduction to Data Warehousing

  • Defining the concept of a data warehouse.
  • The advantages of warehousing for analytics and reporting purposes.
  • How Oracle Database 19c supports warehousing capabilities.

Oracle Data Warehouse Architecture

  • Essential elements: source data, ETL processes, staging areas, and presentation layers.
  • Comparing star schemas versus snowflake schemas.
  • Oracle tools utilized for managing data warehouse environments.

Data Modeling Concepts

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

Overview of ETL Processes

  • An introduction to ETL and the tools supported by Oracle.
  • Distinctions between batch loading and real-time data ingestion.
  • Common obstacles in data integration and quality management.

Query and Reporting Principles

  • Distinguishing between OLAP and OLTP workloads.
  • Methods Oracle employs to optimize queries for data warehouses.
  • Introduction to materialized views and aggregate structures.

Planning and Scaling Oracle Warehouses

  • Considerations regarding hardware and architectural design.
  • The benefits of partitioning and data compression.
  • An overview of Oracle licensing and feature sets.

Applications and Recommended Practices

  • Real-world case studies on warehouse design.
  • Best practices for planning Oracle data warehouse projects.
  • Steps for initiating a pilot implementation.

Recap and Future Directions

Requirements

  • A solid grasp of relational database systems.
  • Foundational proficiency in SQL.
  • No previous background in Oracle data warehousing is necessary.

Target Learners

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

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