Data literacy is the proficiency in reading, interpreting, and communicating data findings and insights in context, with an understanding of where the data came from, how it was processed and analyzed, and the tools and techniques used to do so. Advanced data literacy skills also include the ability to make business recommendations and predictions based on this data analysis.
What is data litracy ?
Data literacy is the proficiency in reading, interpreting, and communicating data findings and insights in context, with an understanding of where the data came from, how it was processed and analyzed, and the tools and techniques used to do so. Advanced data literacy skills also include the ability to make business recommendations and predictions based on this data analysis.
Tips for improving data literacy at your organization
Here are a few steps that any organization can take to start improving data literacy right away, according to Gartner [2]:
Identify the most fluent data communicators in your organization. Before turning to outside resources, you should comb your existing organizational chart for employees who can share their knowledge with those who can benefit from it. This offers several benefits: it’s more budget-friendly to leverage talent that is already on the payroll, and these employees have likely already built relationships across teams. Your BI team is an obvious place to start looking, but don’t overlook other, less obvious teams. For example, your marketing team likely has several employees who are data literate from working with marketing analytics.
Search for data communication problem areas. To make the best use of your time and resources, it’s important to seek out target areas for your data training efforts. Talk to team leaders to uncover missed opportunities where poor data communication led to a failure to use analytical insights. This is also a good time to conduct a business-wide data literacy assessment (more on that in the next section).
Use data ambassadors to lead data education sessions. Using the data communicators that you identified in step one and the problem areas that you uncovered in, set up training sessions to close gaps where data communication barriers have led to missed opportunities. These sessions should be fun and open, rather than formal and prescriptive. Incorporate games and quizzes rather than sticking to a business-like presentation.
Move onto data workshops as a next step. Once your less data-literate employees have become a little more comfortable working with data, it’s time to let them get their hands dirty. Ask participants to bring real-life scenarios from their work where data insights could be useful. Encourage participants to use data terminology as much as possible, and share lessons across teams. Hopefully, you’ll even surface some projects that can be taken on by your BI team.
Encourage data and analytics leaders and their teams to lead by example. Holding education sessions and workshops is a great way to improve organizational data literacy, but it’s not the finish line. Improving data literacy is an ongoing journey, and your data and analytics leaders should focus on continued improvement by encouraging their colleagues to use the language of data in all relevant business situations.
