Dataliterate

Dataliterate is a term used to describe the ability to read, understand, analyze, and communicate with data. It encompasses interpreting data visualizations, assessing data quality, recognizing biases, and using data to support arguments and decisions. Dataliterate individuals can ask pertinent questions about data sources, selection, and limitations, and translate numeric findings into actionable insights for non-technical audiences.

Origin and usage: The term has emerged in data literacy and education communities in the 2010s and 2020s to supplement data literacy with a more action-oriented emphasis. In practice, dataliterate individuals apply data skills across contexts—work, education, and civic life—rather than focusing solely on statistical concepts.

Core competencies: Core competencies include statistical literacy, data visualization literacy, data cleaning and preparation, basic analytics, critical thinking about methodology, data ethics and privacy, and communication of findings to diverse audiences.

Applications: It is used in schools, corporate training, and civic contexts to promote evidence-based decision making, data-informed policy discussions, and responsible data use.

Relation to other terms: It overlaps with data literacy and data fluency; definitions vary by source; some treat dataliterate as the practical application of data skills in everyday life or professional settings.

See also: Data literacy, data fluency, data storytelling, data ethics.