What does it mean to be data literate?

It depends on you. As mentioned previously, data literacy can mean different things to different people.

Individual/personal data literacy

At its most basic, a person's data literacy can be thought of as their ability to read, write, understand, communicate, and work with data in different ways. In this sense, individual data literacy is very similar to having data skills. However, it is important to remember that data literacy is not just about having data skills—especially highly technical data skills. These highly technical data skills such as data analytics or data science form only a very small part of data literacy.

One good thing about individual data literacy and individual data skills being similar is that it makes it easier to build and improve individual data literacy. For example, one of the best ways to build your data literacy is to learn the Data Pipeline and using it for doing data-driven projects.

Organizational data literacy

Organizational data literacy is a bit more complex and harder do build. Factors such as leadership, vision, internal processes and mechanisms all have an effect on an organization's data literacy journey. Individual data skills of organization members are not—and should not be—the end-all-be-all of what it means to be a data-literate organization.

From an organizational perspective, some of the people who take part in building data literacy and fostering data culture in an organization will have no analytic interactions with data and may never need to. The table belows shows an example of this: different roles in an organization have different interactions with data and thus appreciate and utilize data differently.

Going further, we can say that a data literate or data-ready organization isn't just one that has the most number of data analysts or data scientists but one that:

• Uses data as evidence for evidence-based decision making;
• Uses data ethically;
• Builds and fosters data culture within the organization;
• Knows its data and its data users; and
• Empowers its members to learn, improve, and share their data skills and knowledge through activities such as data socialization.