Data Essentials

  • 15m
  • 15 questions
The Data Essentials benchmark will measure your ability to recall and relate the underlying concepts of data. You will be evaluated on the value of good quality data, ethical data practices, mitigating bias in data decision-making, how to use evidence-based decision-making, techniques for data analysis, and data protection best practices. A learner who scores high on this benchmark demonstrates that they have the essential data skills and can understand and grasp the underlying data concepts and practices.

Topics covered

  • distinguish between scoping and validating data evaluation criteria
  • distinguish between structured and unstructured data
  • identify how bias is created, its types, and strategies to recognize and avoid data bias
  • identify the key attributes of data quality
  • identify types of threats to data that businesses need to protect against
  • identify various data visualization elements
  • identify what data ethics is, why it is important, and when it should be considered
  • list the key principles of data ethics
  • outline how to select the right visualization to communicate a specific message
  • recognize best practices for effectively protecting data
  • recognize best practices for identifying key data needs
  • recognize key attributes of effective data governance
  • recognize the critical consequences of a data breach for a business
  • recognize the key data standards considerations you should make
  • sequence the stages of the data lifecycle