Data Warehousing Competency (Intermediate Level)

  • 20m
  • 12 questions
The Data Warehousing Competency (Intermediate Level) benchmark assesses your recognition of core data warehousing concepts. You will be evaluated on your skills in recognizing high-level elements of data warehousing, architectures, and techniques. Learners who score high on this benchmark demonstrate that they have a solid understanding of intermediate-level data warehousing techniques.

Topics covered

  • compare and contrast various data warehousing schemas, such as Star, Snowflake, etc.
  • define a data warehouse and its characteristics
  • define fact table measures, describe how measures are added and loaded, and outline the steps for implementing a fact table in a data warehouse
  • describe batch processing in a data warehouse with an industry use case
  • describe different key concepts and benefits related to modern data warehouses
  • describe how a data warehouse is different from a database and how data warehouses are used for business intelligence
  • describe how data warehouse keys work, specifying the importance of surrogate keys
  • discuss real-time data processing in a modern data warehouse with an industry use case
  • name and define three main tiers of a data warehouse
  • outline stream data analytics in a modern data warehouse with an industry use case
  • outline the architecture and various processes involved in a modern data warehouse
  • recognize various techniques that are commonly encountered in a modern data warehouse