• Online, Self-Paced
Course Description

Examine architectures of data warehouse implementations, including logical and physical design. How to effectively implement and manage data warehousing projects is also covered.

Learning Objectives

Data Warehouse Essential: Architecture Frameworks and Implementation

  • recall essential architectural components of data warehouse along with the design considerations to successfully implement the right data warehousing solution
  • specify essential data warehouse architectural styles and frameworks, and compare Kimball and Inmon
  • identify the logical and physical data warehousing architectural models, with the emphasis on schema and objects
  • illustrate implementation scenarios of the logical and physical data warehousing models
  • list dimensional modeling principles and the differences between it and the ER model
  • specify how data warehousing can be used to facilitate information realization
  • illustrate the processes of extracting, loading, and transforming data in a data warehousing environment
  • recall data warehousing and ETL tools and specify how they are implemented real-time
  • recognize essential tools, components, features and how they are used to implement ETL
  • demonstrate how to use Talend to implement ETL
  • extract data from various sources, and transform and load the data in the intended destination

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Specialty Areas

  • Data Administration
  • Systems Administration
  • Systems Architecture