In her latest post, Eva Murray outlines the essential starting blocks to take into account if you want to improve data literacy in your organization.
In the data-rich working environments of today, it is crucial for people to be data literate and therefore proficient in working with, understanding and communicating data effectively.
Much like literacy in general, data literacy is becoming an essential skill without which many of us could not do our jobs to the best of our ability.
We are seeing an increasing focus and reliance on data analysis for decision-making across all facets of business. From product development to production, distribution, marketing and sales, data has become a key factor in many roles that previously depended on expertise and experience. It has also created countless new jobs and whole industries.
To make the most of your data, you have to not only lead by example and improve your data literacy. You must ensure that your people receive the training and access to the resources they need to continuously develop and grow their own data skills.
Not everyone who works with data feels confident in their data literacy skills
Many organizations are at a point where they want and need to progress from working with unwieldy spreadsheets to using best of breed analytics solutions. This is crucial if they want to remain competitive by utilizing their data better. With this step comes the opportunity to democratize data and give more people access to it, as modern analytics tools make it easier for them to work with data, spot trends, outliers and patterns and communicate this information to their peers. It is essential, however, to ensure that anyone using these tools genuinely understands how they work and has a grasp of the fundamentals of statistics and data analysis, so that their own analyses and findings are based on the correct assumptions and techniques.
Training your people in statistics and Loading...data visualization is essential
When it comes to working with self-service analytics and Loading...data visualization tools, it is not enough to simply let people connect to a data source, start exploring data and sharing their findings. To avoid incorrect conclusions, your organization must provide the necessary training to users.
What could this look like?
For one, the topic of statistics should be covered at a basic level to ensure people understand the different aggregations of data, such as averages, means, medians as well as the concepts of standard deviation and distribution. This helps them to treat the data correctly during their analyses. It is also important to discuss and teach how data should best be communicated. This involves the different ways to visualize data, using charts, dashboards, interactive reports, infographics and more. It also involves the language used to share findings, conclusions and recommendations. And, of course, communicating data should always include visual concepts such as the use of color, logos, icons and shapes.
Maximize your use of the software tools in your stack
In addition to teaching your people statistics and how to communicate data, there is a third element: teaching them how to use software most effectively. With the availability of online courses, free content and countless video tutorials, many of us are self-taught in areas such as data analysis software. From my own experience, however, I can promise that attending some formal training on your chosen analytics software will work wonders for how efficiently you work with data and how much enjoyment you get out of it. Providing training courses for your analysts helps them maximize their use of the tools at their disposal, work more efficiently and develop new and more advanced solutions.
Training your people on these three aspects of data literacy is a great way to improve the use of analytics in your organization and the value you get from it. It also helps to lift the levels of data literacy. In the next article we will focus on how you can ensure that these positive effects are felt all the way through the decision-making process.
Eva Murray, Technology Evangelist, Exasol