3 Common Misconceptions About Data Literacy (and why they’re wrong!)

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What do you know about data literacy?

If someone asked you, “are you data literate?” how would you respond? If your answer is 🤷🏼‍♀️, you’re not alone — but this one’s for you!

Data literacy is a buzzword that has become increasingly more common in today’s world, and for good reason! The amount of data in the world is expected to reach over 180 zettabytes by 2025, which means it’s growing… and fast.

Data is everywhere. It’s how Netflix knows what TV shows to recommend, how Amazon knows what products to show you, and how TikTok cultivates your FYP. (Yes, this means you’re to blame for what you see on your FYP!)

Having a solid grasp on what data is, how it’s used, and why it’s important is essential. And guess what! That’s essentially what data literacy IS.

Our definition of data literacy is this:

The ability to interpret, manage, analyze, and communicate with data

If you’re thinking you can just leave the data literacy to the data scientists and analysts, though, think again. Luckily, this brings us to our first common misconception…

Data literacy is just for data professionals.

Data literacy is all about making data-driven decisions, regardless of your job title or industry.

Maybe you’re thinking, “I don’t work with data; why do I need data literacy skills?”

Here’s the thing: no matter where you work or what industry or department you work in, your organization uses data, too.

Human resources professionals use data to identify training needs or analyze workforce demographics. They can use data to make decisions about which employees should receive a promotion and to help understand employee attrition rates.

Healthcare professionals use data from electronic health records, like patient demographics and diagnoses. They use data for claims and insurance purposes, as well as for operational purposes. Speaking from experience, healthcare professionals also use data to guide treatment planning and goal setting.

Sales professionals use data to analyze customer demographics and forecast sales trends. They can use data to improve productivity and efficiency or to understand the patterns in their sales processes.

The common theme here? None of these people have the title of data analyst or data scientist. They’re everyday people who work with data and thus, need data literacy skills.

But the question becomes: what level of data literacy is right for you?

That brings us to our second common misconception, which is…

Data literacy is one-size-fits-all.

The great thing about data literacy is this: your level of literacy should be based on the skills you need in your job function.

We think about three different levels of data literacy:

• Someone who is conversational with data can understand basic data concepts and interpret straightforward analytics outputs. They don’t have the ability to manipulate data or perform an analysis themselves. These people are who we call the data interpreters. They’re non-analysts who are consuming and potentially making decisions based on analytical outputs.
• The person who is data literate is someone who can interpret, manage, and analyze data for a basic descriptive or diagnostic analysis. They might have limited to no experience conducting advanced analyses or presenting to stakeholders. These people are citizen analysts. They aren’t necessarily analytics specialists but they do leverage data in their role.
• Last is the person who is data fluent. This is someone who has the skills to think strategically, design and conduct complex analyses, and clearly share insights to technical and non-technical audiences. These are the data specialists. They’re professionals in specialized data roles like BI Analysts, data scientists, or data engineers.

Data literacy isn’t about getting to a fluent level. It’s about having the skills you need to succeed in your specific role.

If you noticed in the descriptions above, data literacy involves abilities like interpreting basic charts and graphs and communicating insights with stakeholders. One thing that these skills share? They don’t involve advanced technical skills, which brings us to our third and final common misconception…

Data literacy is just about the numbers and requires advanced technical skills.

Let’s revisit Maven Analytics’ definition of data literacy:

The ability to interpret, manage, analyze, and communicate with data

Our definition of data literacy certainly doesn’t involve “the ability to calculate R-squared” or “the ability to write a Python script”! While numbers are obviously part of data, data literacy is about more than that. It’s about understanding the story and context behind the data, what the data means.

In fact, data literacy often comes down to soft skills, rather than technical ones.

• Can you use critical thinking skills to interpret the meaning of the chart in front of you?
• How would you solve data quality problems like outliers or incorrect data types?
• Have you evaluated the information available to you objectively and without bias?
• What graph would be best to clearly communicate your insights?

Sure, numbers and advanced technical skills can be a part of data literacy but they’re not the entire story.

So now what?

It’s becoming more and more obvious that data literacy skills are for everyone, no matter your job function, industry, or department. They allow you to make better, more data-driven decisions that have solid evidence behind them. And, with data growing exponentially (see 180 zettabytes above), now is the time to…

Assess your own data literacy skills

1. Do you feel comfortable looking at a chart and understanding what it means?
2. Can you figure out what type of data you’re looking at and where it comes from?
3. Are you able to analyze data to find patterns, trends, and insights?
4. Would you know which chart or graph to use to communicate your findings?

Determine what data skills you need in your job function

1. Are you expected to interpret charts and tables?
2. Does your job involve finding and gathering data?
3. Do you analyze data to provide insights to others?
4. Are you asked to communicate your findings?

Take steps to bridge the gap between where you are and where you want to be

Whether you decide to take a course, read a book, or join groups dedicated to data literacy, what matters is that you’re making moves toward becoming more data-literate. I’m confident that you’ll quickly see how valuable of a skill it is and will continue to be.

I hope these steps will help you figure out exactly how to begin your own data literacy journey!

Ready to start your journey toward data literacy? Check out our brand new course: Data Literacy Foundations! It’s 2.5 hours long and is built for everyone. Plus, it’s FREE!

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Happy learning!