Data Lakes Competency (Intermediate Level)

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

Topics covered

  • define a governed data lake and list its advantages
  • define data lakes and describe their evolution from Hadoop
  • describe data swamps and their characteristics
  • describe the architectural differences between data lakes and data warehouses
  • describe the architecture of a modern data lake
  • describe the data processing strategies provided by MapReduce V2, Hive, Pig, and Yam for processing data with data lakes
  • describe the differences between a data lake and a data warehouse
  • identify the features data lakes provide as a part of the enterprise architecture
  • implement Lambda and Kappa architectures to manage real-time big data
  • list and compare prominent data lake platforms
  • list and define the key concepts related to data lakes
  • list and describe the different maturity stages of data lakes
  • list and describe the risks and challenges associated with data lakes
  • recognize how to derive value from data lakes and describe the benefits of critical roles
  • recognize how to use data lakes to democratize data