Data Literacy

TL;DR

Ability to read, manipulate, and analyze datasets to extract useful information.
Convert raw data into clear visualizations (e.g., bar charts, scatter plots) to reveal trends and relationships.
Use statistical and machine learning techniques to build predictive models and communicate findings across data types (numbers, text, images, video).

Definition

Data literacy is the ability to read, work with, analyze, and communicate data effectively.

Explanation

Data literacy enables people to handle data in multiple forms and use it to gain insights and make informed decisions. It is increasingly important in a data-driven society as organizations rely on data to inform their decisions and operations. Being data literate involves tasks such as creating visualizations to represent raw data in digestible formats and applying statistical or machine learning techniques to build models that make predictions.

Examples

Data visualization

A data literate person might create a bar chart to show how the sales of a product have changed over time, or a scatter plot to show the relationship between different variables.

Predictive modeling

A data literate person might use data about a person’s age, income, and location to predict their likelihood of voting in an election, or use data about a patient’s medical history and current symptoms to predict their likelihood of developing a certain disease.

Use cases

Valuable for anyone who works with data, whether they are a data scientist, a business analyst, or a journalist.

Data visualization
Statistical techniques
Machine learning