Data Literacy
Up to this point in the Data Journey, you’ve learned a bit about what data is, how it functions, and what it can be used for. The next time you engage in a conversation about data, you’ll hopefully have something to contribute!
It’s easy to perceive data and its workings as somewhat mystical. We often talk about things like “the cloud”, and use terms like “surfing”. It all seems very light and ethereal. Providers of digital products and services strive to make their offerings as user-friendly as possible, largely concealing the intricate processes that run behind the scenes.
Indeed, the technology is sophisticated—it’s been developed gradually over many decades—but it’s far from magical. “The cloud” and “the net” are simply metaphors for a physical infrastructure consisting of underwater cables, server farms and so on. It’s actually something decidedly physical, tangible, and real. And there are people out there who actually have a deep understanding and control over these systems.
What is data literacy, and why is it so important?
Data literacy refers to being able to understand, use and engage with the data we encounter in our everyday life. It’s the ability to read, understand, analyse and think critically about data and its use.
The term “literacy” is sometimes equated to just reading and writing abilities. But that’s too narrow a perspective. According to the Great Norwegian Encyclopedia, literacy encompasses a range of skills that allow one to understand, create, communicate, navigate, and participate in evolving societies. The United Nations has even declared literacy as a human right.
What makes data literacy so critical, in fact, is the central theme of the Data Journey. Let’s delve into it below.
But hold on: Do we all need to be fluent in data to partake in society? Must everyone pursue extensive IT education to secure a job and a life? Absolutely not.
Not everyone is a specialist in fields like language or economy, either, but many still have a basic level of knowledge that’s enough for one to grasp what it’s all about, and a certain level of understanding that allows one to keep up with changes in the field—and why it matters.
What kind of competence does data literacy involve?
To be able to write and read, you need to master a set of skills. Some are basic: To start with, you need a vocabulary. Then a simple understanding of grammar. Later you should learn sentence construction, verb conjugation, word classes and so on. A higher level includes things like the ability to communicate, to argue and to accumulate and share knowledge.
The same applies to data literacy.
Let’s take a closer look at the skills and areas of competence that make up data literacy, roughly ranked from basic to more advanced:
Data users and citizen data scientists
Interpreting, structuring and refining data is obviously not something just anyone can master in a jiffy. This competence is in high demand across all industries and businesses. Today, “everyone” is looking for a good data scientist.
Much of the hardest work, such as collating data from various sources, is increasingly supported by good digital tools. At the same time, more and better tools are emerging for non-specialists to use to explore, analyse and gain insight from the data.
As the process becomes more streamlined and analysis tools more user-friendly, an increasing number of people can start working with data and uncover valuable insights. We often refer to these non-experts who interact with data as “citizen data scientists” or simply “data users”.