What Is Data Literacy and Why Does It Matter?

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data literacy

An international survey by technology company Accenture in 2020 found that 75% of C-suite executives believe that all or most of their employees are proficient at working with data. However, only 50% of middle managers felt the same way. And what about the employees themselves? Only 25% felt that they were fully prepared to use data effectively, and only 21% said they were confident in their level of data literacy.

Clearly, there’s a big disconnect between how executives view their organization’s level of data literacy, and what the employees of that organization believe about themselves. Perhaps these survey results indicate a lack of confidence when it comes to data skills, or maybe miscommunication about what standards are expected on a company-wide level. 

Either way, these findings illustrate that companies need to understand what data literacy is and assess how well their employees understand it. Because business leaders agree: At this point, some level of data literacy is a non-negotiable necessity for employees at all levels across an organization. 

What Is Data Literacy?

Just as a literate person can read texts, analyze their meaning, and communicate ideas through writing, a data-literate person can read data, analyze its meaning, and communicate ideas and insights about the data to other people. Several helpful definitions include:

  • “The ability to derive meaningful information from data, just as literacy in general is the ability to derive information from the written word.” (TechTarget)
  • “Includes statistical literacy but also understanding how to work with large data sets, how they were produced, how to connect various data sets and how to interpret them.” (
  • “The ability to read, work with, analyze and communicate with data regardless of your role, skill level, or the BI tools you use. Improving data literacy hones your decision-making skills. You learn to ask the right questions of your data, interpret your findings and take informed action.” (Qlik)
  • “The ability to read, write and communicate data in context, including an understanding of data sources and constructs, analytical methods and techniques applied, and the ability to describe the use case, application, and resulting value.” (Gartner)

What all these definitions have in common is that they focus on having the skills necessary to make data useful. Just as it’s useless to look for answers in a book written in an unknown script, having all the data in the world doesn’t help a business one bit unless they understand how to interpret and use that data. 

Examples of Data Literacy Skills

Of course, data literacy does not look the same for everyone in an organization. A sales manager would not be expected to have the same skills or knowledge as a data scientist. However, anyone who works with data or makes decisions based on data needs at least basic data literacy skills. Examples of these skills include the ability to:

  • Understand statistical concepts such as median, average, standard deviation, correlation vs. causation, and signal vs. noise
  • Gather, clean, filter, sort, and analyze data
  • Interpret graphs, charts, and visualizations
  • Critically assess data: understand its limitations, how it was collected, and what it represents; recognize mistakes and avoid misleading uses of statistics
  • Make business decisions based on an accurate understanding of the data
  • Explain the output of data systems or algorithms 
  • Communicate findings to people who are less data-literate through data storytelling
  • Use data to support a message, narrative, business case, or argument

Why Is Being Data-Literate Important?

Data literacy is a job requirement for someone like a data analyst or a data scientist. But why does it also matter for people who don’t have the word “data” in their job title? 

In general, if data is siloed off as the domain of only a few elite experts, there will be a limited common language to discuss data across the entire organization. That will make the business less efficient, and it will be harder for managers and other employees to use data to identify problems or glean insight into business strategies. 

According to a 2020 report from Gartner, 35% of CDOs cite poor data literacy as one of the top roadblocks to establishing an effective data and analytics team. The report recommended building data literacy in an organization by starting a pilot program of data literacy skills training, focusing on team members who have demonstrated enthusiasm about data and an understanding of its importance. 

“Without data-literate employees across the business, business leaders will remain unclear about what data it has, what the data could be used for and the quality of the data,” the report states. “As a result, organizations will fail to identify potential business opportunities.”

In a recent interview for DATAVERSITY®, technology expert and business leader Asha Saxena noted that she constantly speaks with data leaders who wonder why none of their employees are using the applications and new technologies that they invested so much time and money into. Often, the issue is data literacy: People do not understand the value of data or how to use it.

“Organizations have so much data, but they don’t understand the consumption and application because of the gap in data literacy. If the data does not teach to innovate, then what good is that data?” said Saxena.

According to a 2023 report from Datacamp, the majority of business leaders believe that data literacy is important for their organizations’ daily tasks. So, where to begin?

How to Build Data Literacy in an Organization

Building data literacy in an organization is a long-term project, often spearheaded by the chief data officer (CDO) or another executive who has a vision for instilling a culture of data in their company.

In a report from the MIT Sloan School of Management, experts noted that to establish data literacy in a company, it’s important to first establish a common language so everyone understands and agrees on the definition of commonly used terms. 

Second, management should build a culture of learning and offer a variety of modes of training to suit different learning styles, such as workshops and self-led courses. 

Finally, the report noted that it’s critical to reward curiosity – if employees feel they’ll get punished if their data analysis reveals a weakness in the company’s business strategy, they’ll be more likely to hide data or just ignore it.

Donna Burbank, an industry thought leader and the managing director of Global Data Strategy, discussed different ways to build data literacy at DATAVERSITY’s Data Architecture Online conference in 2021. She said organizations can make the process fun and even gamify it by letting employees complete classes and trainings to earn badges. 

These badges could be broken down by level to show what data skills they bring to the table: For example, a “data citizen” could be someone who brings dashboards to meetings, a “data builder” could be someone with self-service skills, and a “data expert” could be someone who can build warehouses or do advanced analytics. 

“I think it’s a progression, and I think it’s really helpful when you’re doing a data literacy campaign to kind of break that out so people don’t become overwhelmed with it,” Burbank said. She also suggested having specific tests and certifications to ensure that the badges measure real skills and are not just “buzzwords.”


The age of COVID-19 illustrated the critical importance for everyone to have basic data literacy. Nearly overnight, it became common for every major news outlet to have a data dashboard on their homepage with all the latest charts, graphs, and statistics about case counts, seven-day rolling averages, hospitalization rates, and more.

Just as consumers have come to understand and appreciate the role of data in their everyday lives, businesses have come to understand that all of their employees must be data-literate as well. 

Focusing on data literacy will help organizations empower their employees, giving them the knowledge and skills necessary to feel confident that they can use data to drive business decisions. As MIT senior lecturer Miro Kazakoff said in 2021: “In a world of more data, the companies with more data-literate people are the ones that are going to win.”

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