Course details

Data Warehouse Essential: Concepts

Data Warehouse Essential: Concepts


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

Explore the fundamentals of data warehousing and the approaches of implementing it.



Expected Duration (hours)
1.7

Lesson Objectives

Data Warehouse Essential: Concepts

  • identify the characteristics of strategic information and the need for data warehousing to manage strategic information
  • list the essential differences between OLAP and data warehousing capabilities
  • specify the essential guidelines that should be followed in order to implement a successful data warehouse project on the cloud and on-premise
  • compare essential on-premise and on-cloud data warehousing products and components
  • identify the essential characteristics of data warehouse projects
  • compare normalization and denormalization processes in data warehouse projects
  • compare the contrasting features of OLTP and data warehouse from the perspective of indexes, joins, data duplication, and data aggregation
  • differentiate global data warehouse from local data warehouse, and recognize critical features, capabilities, and implementation
  • recall essential data warehouse terms that are frequently used when implementing data warehouse projects
  • recall important data warehouse processes that are generally applied to facilitate business intelligence, including the essential ETL processes
  • recall how the ER schemas are implemented in data warehouse projects
  • specify how the star schemas are implemented in data warehouse projects
  • describe how the snowflake schemas are implemented in data warehouse projects
  • identify the critical capabilities of multi-valued dimensions and the essential comparison between weighted and impact reports
  • illustrate the architectural concept of reporting and classify the various essential types of reports
  • compare data warehouse, RDBM, data lake and their implementation scenarios
  • compare the critical features, capabilities, and the implementation scenarios of Azure and AWS data lakes
  • identify how to implement and facilitate data warehouse given a scenario
  • Course Number:
    it_dfdwes_01_enus

    Expertise Level
    Beginner