Data literacy: what is it and why is it essential for success?

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Business leaders looking to gain a competitive advantage can do so by prioritizing data literacy for employees across all departments and levels of their organization. With data literacy skills, employees better understand how business data works and how to use it, enabling them to be more effective and streamline processes for the organization. Read on to learn more about what data literacy is and how you can implement data literacy initiatives across your business.

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What is data literacy?

Data literacy refers to the ability to read, understand, communicate, analyze, and infer information from data, putting it all in context. Forbes defines data literacy as effectively using data everywhere for business actions and results. Data literacy is often associated with data science, which uses analytical methods to extrapolate insights from data.

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Data literacy is usually seen as an individual skill, but it is also an organizational skill; widespread data literacy helps organizations achieve better business outcomes by extracting more value from their data.

With the growing importance of data literacy in organizations and the abundance of data, there is a greater emphasis on establishing data literacy training programs and appointing chief data officers to continuously assess and improve data literacy in the organization.

Why is data literacy important to your business?

Data literacy skills are not just required by the analytics or IT team; all departments and roles within an organization can benefit from data literacy. Data literacy empowers employees to ask the right questions, collect the right data, and connect the right data points to gain meaningful and actionable business insights. It also ensures that all employees understand how to manage and use data in a manner that is ethical and compliant.

According to a recent Qlik data literacy survey of 6,000 employees, including 1,200 executives, 85% of business leaders believe that data literacy will be critical to business success in the future. The survey also found that the majority of business leaders expect their teams to make decisions based on data.

Remarkable technological advances have been made in the fields of machine learning, artificial intelligence and big data. However, there is a lack of data savvy professionals who have the skills to use data effectively. With the right data literacy training, organizations have the knowledge to optimize these emerging technologies for a variety of industrial and consumer applications.

Data literacy is also important for the user and customer experience. It helps with faster decision making, improved productivity and data-driven critical thinking. Employees can use data literacy skills to make their operational processes more efficient, improve sales performance, and make other improvements to their roles and responsibilities. These improvements trickle down to customers who benefit from higher quality products.

Examples of data literacy and use cases

The following data management frameworks and tasks work best when the entire organization consists of data-savvy employees:

Data ecosystems

Data literacy is helpful in establishing and maintaining a reliable data ecosystem, which can include physical infrastructures such as cloud storage or service space and non-physical components such as software and data sources.

Data management

Organizations use data governance to manage their data assets so that they are complete, accurate and secure. Data management is not the sole responsibility of any particular team; the entire workforce must have the appropriate data literacy levels to contribute to its success.

Many organizations have data policies that all employees must understand and adhere to. This includes how to access sensitive data, how to keep data safe, and other data processes.

Data dispute

Data wrangling is the process of converting raw data into a more structured and usable format. Data wrangling helps reduce errors in the data. An organization may have individuals or automated software for data wrangling, but any employee who works with any form of data also plays a role in preserving data in an acceptable format.

Data visualization

By creating a visual representation of data, such as a chart or graph, data professionals can more effectively communicate insights derived from data. Visualization can include infographics, tables, videos, charts, and maps. Both the creators of these visualizations and the stakeholders to whom they are presented need at least basic levels of data literacy to understand the implications of the data ahead.

Important data literacy skills

The most basic data literacy skills are knowing the difference between different types of quantitative and qualitative data, including nominal, discrete, continuous, and ordinal. Being able to trace the source of data is also an important part of basic data literacy. Knowing the type of data and being able to assess its quality helps minimize misconceptions and biases about data and maximize understanding of data.

At a higher level of data literacy, individuals begin to recognize the nuances and limitations of data. For example, a survey question formulated in different ways can lead to very different answers and qualitative data results. Likewise, data visualizations can be misleading. Data literacy helps professionals minimize misinterpretation of visual data as data literate individuals can identify trends, gaps, outliers and patterns in data.

Whether their general understanding of data is more basic or advanced, it is paramount that employees understand data concepts relevant to their individual roles. For example, anyone working in digital marketing would benefit from understanding terms in marketing data such as web traffic, page views, unique visitors, and impressions.

Conclusion

If organizations want to be truly data-driven, it shouldn’t just be the tech experts who are getting data literate; everyone in the workplace must develop data literacy skills to keep the business competitive and compliant.

Business intelligence experts and data scientists can coach their colleagues to become data literate. However, it should be an organizational level commitment that covers all employees with data literacy training and other support tools.

Companies may not immediately see the value of providing data literacy education to all their employees, but the long-term benefits are clear: knowledgeable people can expertly question and analyze data logic, applying their data-driven knowledge to any business problem they need to solve.