How Can Data Literacy Be Improved? A Targeted Learning Approach

Data is everywhere, and so is the need for data literacy. Whether it’s businesses making strategic decisions, healthcare professionals analyzing patient trends, or individuals managing personal finances, the ability to understand and interpret data is more essential than ever. But for many, data can feel overwhelming. The challenge isn’t a lack of interest, it’s a lack of access to the right tools and training to grow data skills in a meaningful way. Without a foundation in data literacy, even the most motivated people can struggle to make sense of information. So, what is data literacy? It’s the starting point for transforming confusion into confidence, and it’s a skill set everyone can build.

So, how can data literacy be improved in a way that feels approachable, practical, and enjoyable? Let’s look at a structured learning approach that helps people work with data and truly make sense of it.

What Does It Mean to Be Data Literate?

What is data literacy, really? It goes far beyond knowing how to work a spreadsheet. Data literacy is the ability to read, understand, create, and communicate data in a way that leads to action and insight. It includes a mix of technical skills and critical thinking, being able to analyze numbers, ask the right questions, recognize bias, and apply findings in real-world contexts. To grow data skills, individuals need more than formulas; they need the mindset and confidence to engage with data in meaningful ways. Strengthening data literacy is not just about the tools, it’s about how we think with data.s

MUST READ: The Future of AI-Driven Corporate Training

Steps to Strengthening Data Literacy

Improving data literacy and building strong data skills doesn’t happen overnight. It takes ongoing education, hands-on practice, and thoughtful reflection. To truly grow data skills, individuals need consistent opportunities to engage with data in context, not just one-time workshops or isolated training. According to Tableau and Forrester, “82% of decision-makers say all employees should have basic data literacy, but only 47% report access to relevant training.” This gap underscores the need to embed data literacy into daily operations and foster a culture where data is understood and valued. If you’re wondering what is data literacy in practice, it’s a shared language across teams, one that drives better decisions and deeper understanding. The following steps outline how individuals and organizations can develop and strengthen their data literacy journey.

Step 1: Building a Strong Educational Foundation

The first step is ensuring learners have a clear, structured way to build their knowledge. That means starting with the basics:

• Understanding different types of data and their uses. 
• Learning how to read charts, graphs, and tables effectively. 
• Recognizing the importance of ethical data use. 

To grow data skills across a workforce, organizations should invest in internal training programs and learning modules that build foundational knowledge. For self-learners, resources like books, online tutorials, and real-world case studies can support continuous development. These efforts directly impact performance, Qlik reports that “85% of data literate employees say they’re performing very well at work, compared with just 54% of the wider workforce.” This shows that data literacy isn’t a nice-to-have; it’s a performance driver. What is data literacy if not the ability to move from passive review to active interpretation? In today’s workplace, being able to apply data to real-world scenarios is what transforms raw information into meaningful insight.

Step 2: Gaining Hands-On Experience

Think about learning a new language. You can study vocabulary and grammar all day, but until you start speaking, you won’t truly grasp it. The same is true for data literacy. Hands-on experience is critical. Here’s how to obtain and refine these skils:

• Work with real datasets: Try analyzing a public dataset. 
• Clean and organize data: Learn how to structure messy data sets effectively. 
• Use visualization tools: Turn raw numbers into compelling stories. 

Organizations can grow data skills by making hands-on learning a part of everyday work. This means integrating more data-related tasks into employees’ daily workflows, encouraging them to ask data-driven questions, and offering mentorship from experienced analysts. These real-time applications help reinforce data literacy by turning abstract concepts into practical habits. What is data literacy if not the confidence to engage with data as part of decision-making, not just analysis? When organizations intentionally support these moments, they build a stronger foundation of data skills across the entire team.

Step 3: Cultivating Critical Thinking Skills

Data literacy isn’t just about working with numbers, it’s about thinking critically. A data-literate person should always ask:

• Where is this data coming from, and how reliable is it? 
• What assumptions might be influencing this analysis? 
• Could biases be affecting the interpretation of these results? 

Developing a healthy skepticism toward data is a key part of building strong data literacy. It empowers individuals and teams to move beyond surface-level analysis and question the source, context, and implications of the data they encounter. This critical mindset is essential to grow data skills, not just in understanding numbers, but in interpreting their true meaning and impact. What is data literacy if not the ability to think deeply, challenge assumptions, and apply insights with confidence? These habits elevate how we work with data every day.

Step 4: Making Data a Part of Daily Work and Decision-Making

For organizations, the ultimate goal should be to create a culture where data isn’t just something used by analysts, but rather that it informs decisions at all levels. Here are some ways to ensure this happens:

• Make data tools accessible to all employees, not just IT teams.
• Encourage employees to incorporate data-driven insights into reports and presentations.
• Provide feedback and foster discussions on how data is used in decision-making processes.

For individuals, one of the most effective ways to improve data literacy is to make data analysis part of daily life. Whether it’s tracking personal finances, analyzing social media trends, or evaluating fitness statistics, these everyday habits help grow data skills over time. What is data literacy if not the ability to interpret and apply information in real-world contexts? By practicing regularly, individuals not only strengthen their technical abilities, they build lasting confidence in how they engage with data.

MUST READ: Why AI Training is No Longer Just for IT Teams

Why Improving Data Literacy Matters

Data literacy isn’t just for analysts or tech professionals, it’s a universal skill that impacts every part of an organization. It should be treated as a shared language across departments, enabling teams to collaborate, interpret, and act on information more effectively. When organizations and individuals grow data skills, they unlock better decisions, deeper insights, and greater confidence in navigating complexity. What is data literacy if not the bridge between raw data and informed action? With the right approach and consistent practice, anyone can develop the data skills needed to thrive in today’s world.

So whether you’re an organization looking to train your workforce or an individual hoping to level up your skills, taking small, consistent steps toward better data literacy will pay off immensely.

At Data Society, we offer comprehensive training programs to help professionals and businesses establish data literacy. More learning and insights can be found here.

Frequently Asked Questions