SKILL BENCHMARK

CompTIA Data+ Literacy (Beginner Level)

  • 19m
  • 19 questions
The CompTIA Data+ Literacy (Beginner Level) benchmark measures your knowledge of key data analytics concepts, common roles in data science, and the basics of working with databases. You will be evaluated on your recognition of key concepts surrounding databases and their use in the modern world, various data types, and the relationship of data with modern database systems. A learner who scores high on this benchmark demonstrates that they have a good understanding of the basic data concepts required for the CompTIA Data+ certification Data Concepts and Environments domain.

Topics covered

  • define unstructured and semi-structured data and their key characteristics
  • describe different types of databases
  • describe key/value pairs and their purpose
  • describe the purpose and role of relational databases
  • identify the features and purpose of structured data and its key characteristics
  • identify the purpose and role of data lakes and data lakehouses
  • identify the purpose and role of non-relational (NoSQL) databases
  • identify the purpose of database schemas, including the three basic schema types, differences between schemas and instances, and the advantages of database schemas
  • install and configure Python, Visual Studio Code, and PowerShell 7
  • outline database components
  • outline the purpose and role of data marts
  • outline the role of databases in application development
  • outline the role of slowly changing dimensions, including reasons to keep historical and current information
  • outline undefined fields and their role in databases
  • recognize the purpose and role of self-driving databases
  • work with a snowflake schema and identify its purpose, advantages, and disadvantages
  • work with a star schema and identify its purpose, advantages, and disadvantages
  • work with primary and foreign key relationships between tables in a relational database
  • work with the features of defined rows and columns

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