SKILL BENCHMARK
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
