Data Fluency - Data Skills

  • 19m 59s
  • 20 questions
The Data Fluency - Data Skills benchmark measures whether a learner has been exposed to common data skills and understands their importance. This Benchmark is for any learner looking to upskill in data fluency around understanding the important of data, the value of data literacy, what it means to be data-driven and how to think with a data-first mindset. A learner who scores high on this benchmark demonstrates an entry level of understanding in understanding why data is important.

Topics covered

  • define concepts essential to data science like dataset, database, data analytics, data aggregation, and time series
  • define the relationship between big data and the value of data analytics
  • describe how to add structure to raw data and name big data tools that aid this process
  • describe the concept of big data and the history behind it
  • describe the process of deciphering correlations, market trends, patterns
  • distinguish between raw data, information, applicable knowledge, and general wisdom
  • identify the benefits of big data to organizations
  • identify the emerging trends in data analytics and their roles across industries
  • identify the key elements of the actionable insight formula
  • identify the right questions to ask to narrow down the problem
  • identify the steps to create an initial problem statement
  • identify the steps you take to ensure your decision making is data driven
  • name the components and benefits of data governance
  • outline the purpose and components of the data analytics maturity model
  • recognize the benefits of building your analytics literacy
  • recognize the importance of data visualization and reporting and tools commonly used for the same
  • recognize the key activities for refining and finalizing problem statements
  • recognize the key characteristics of big data
  • recognize the purpose of using data collaboration and visualization tools
  • recognize the steps for testing and validating assumptions