MSU Extension Economic Development

For centuries, societies have established several key literacies that become the foundation for human functioning and interaction. Reading, writing, as well as numerical literacies are some examples of core literacies that has become essential parts of our lives. As technologies develop to facilitate our work, digital literacy became a key skill and it is more difficult to work and compete without basic understanding of how technologies work.

The rapid development of data processing technologies, coupled with the increasing abundance of open data, calls for a different type of literacy that could change the way we work and make decisions: data literacy. Simply put, data literacy is the ability to read, analyze, and communicate with data. More than just an understanding of statistics, it is about the ability to use data as a tool to guide decisions. This requires the knowledge of different tools and techniques to process data to turn it into meaningful information.

Being data literate enables one to understand the way data “speak.” Without data literacy, data is nothing but a collection of alphabets and numbers set to “collect dusts” deep in one’s computer folders. While many regard data as the new oil, we cannot reap the benefits of data without learning how to harvest it first.

Components of data literacy

Some key data literacy skills include data collection, data analysis, and data visualization. Data collection skills are fundamental to any form of data analysis. Understanding where and how to collect data is a prerequisite to all types of analysis. This might include the ability to navigate the internet for open data sources, or the ability to design surveys to collect data from different audiences.

Data analysis involves the ability to interpret and extract information from available data. Trends, patterns, and insights can be gathered during the process of data analysis. This requires an understanding of statistics and context from where and how the data was collected. There are various statistical tools available to facilitate data analysis. A basic understanding of how these tools work is prerequisite to conduct data analysis efficiently.

A good data analysis is usually followed by effective data visualization to communicate information and data with graphical representations. Data visualization can allow complex information to be communicated using visual tools. Charts, graphs, and maps are all examples of data visualization.

The case for data literacy

Contrary to popular beliefs, it doesn’t take expensive infrastructure to harness the power of data. For small-scale operations, common software like Microsoft Excel can be powerful tools to collect, analyze, and visualize data. Nowadays, open source (free!) data processing applications like Tableau Public allows anyone to turn data into insights. All it takes now is some knowledge of how to utilize these applications to process data.

While the importance of data literacy is increasingly emphasized in the private sector, it is not getting much traction in the public sector. Government agencies and community-based organizations are at the forefront of community development. Building data literate organizations should be a priority to all government agencies in order to remain relevant in an increasingly data-driven world. A more data literate public workforce could enable us to better utilize data to guide decisions that impact planning and development.

Where do you start?

          It can be overwhelming to think about how to promote a more data-driven organization, especially with limited public funds. This is where organizations like MSU Extension play a key role in providing resources and education to community leaders and government agencies in Michigan. MSU Extension’s Data Literacy for Community Development Webinar Series is an ongoing professional development opportunity to train community leaders in data collection, visualization and processing using open source applications that are widely available to the public. The four-part webinar series allow participants to understand fundamental data literacy skills that could change the way they see and utilize data. All registrants will have access to past recordings and resources even if they were unable to attend the sessions.