As data becomes increasingly intertwined with not just our professional lives but our personal ones as well, the importance of data literacy on a widespread level will only continue to become more of a pressing need. But while awareness may exist, it doesn’t always translate into actual knowledge.

 A recent study of a data literacy gap among young people serves as an excellent illustration of this point. According to the study, while most of the young people (aged 16-21) surveyed consider data an important element of their future lives and careers, only 43 percent consider themselves data literate. In fact, more than half of the respondents were unfamiliar with the concept altogether.

Obviously, modernizing education programs to be more data-centric needs to be a critical part of familiarizing the future workforce with these concepts, but that doesn’t mean enterprises are off the hook. In order to become more data-driven, companies need to ensure that all organizational roles and departments are data literate. With that in mind, below are seven tips for increasing data fluency for the uninitiated.

1. Uncertainty is Inevitable

When it comes to data, you may often need to use comparative estimates or projections. One way to avoid potential misunderstandings due to uncertainty is to communicate information via visuals and infographics.

2. Understand What You’re Working With

There is a wide range of data types, and it’s important to recognize them and their approaches. Again, this helps prevent potential misunderstandings and mistakes.

3. Sources Matter 

Encourage non-technical roles to understand the importance of reputable data sources, as well as the differences between aggregated and normalized data.

4. Keep It Organized 

Effectively managing data requires attention to detail—this one can’t be overstated enough!

5. Look for Patterns 

Don’t settle on the first insight you uncover. By digging deeper and analyzing outliers and anomalies, you may develop a broader understanding or uncover new trends that weren’t evident via a superficial analysis.

6. Analyze Responsibly 

Point out trends and interesting distributions of the data, but be careful never to equate correlation with causation.

7. Data Literacy is an Ongoing Exercise 

You don’t need to be a data master in order to begin analysis. Continuing to learn, practice, and collaborate with others on data initiatives is key to broadening your skillset and doing your part to make the entire organization more data-driven.

For more on the data-driven imperative and what you can do to overcome cultural roadblocks, check out this previous APEX of Innovation post.