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