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This content is part of the Essential Guide: Guide to telling stories with data: How to share analytics insights
Definition

data literacy

Contributor(s): Ivy Wigmore

Data literacy is the ability to derive meaningful information from data, just as literacy in general is the ability to derive information from the written word.

The complexity of data analysis, especially in the context of big data, means that data literacy requires some knowledge of mathematics and statistics. To deal with that complexity, many organizations are hiring specialists called data scientists, who have advanced analytical skills. Some enterprises have also added a C-level employee, the Chief Data Officer (CDO), to ensure that the organization realizes the full value from its data. 

Nevertheless, because data is so crucial to a business' success, an increasing number of organizations demand some degree of data literacy from all employees. 

Data literacy skills include the following abilities: 

  • Knowing what data is appropriate to use for a particular purpose.
  • Interpreting data visualizations, such as graphs and charts.
  • Thinking critically about information yielded by data analysis.
  • Understanding data analytics tools and methods and when and where to use them.
  • Recognizing when data is being misrepresented or used misleadingly.
  • Communicating information about data to people lacking data literacy, an ability sometimes referred to as data storytelling.

See Uldis Leiterts' TEDx talk, The Age of Data Literacy:

 

This was last updated in July 2015

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