The data that you collect for your business is very important…but it is only as important as the level of understanding and insights that you gain from that data, and how it can help you to make the right decisions to move your business forward. Simply looking at numbers is not enough to help you understand how your business is performing, and that is where data analysis with the use of visualization comes in.
Visualizing data can be as simple as entering data into Excel and using filters and sorting, or as complex as using programs like Tableau. For example, basic analysis in Excel could include filtering data by state then sorting revenue from highest to lowest to determine which state brings in the highest revenue for your business. A more complex level of analysis in Excel, as mentioned in last week’s blog post, would be to add dimensions and then utilize a Pivot Table to customize how you view the exact data that you want to get information from. Excel also allows you to add charts to represent the information visually with graphs, etc.
For more complex data visualization, one could use programs such a Tableau that provide a plethora of features – including the ability to analyze data at different levels and produce multiple formats of visualizations. For example, in Tableau, one could add multiple Excel spreadsheets and then connect the sheets if they have a common field. You could then add measures, dimensions, and hierarchies to further analyze your data and then produce visualizations that are easily understood by those needing to gain insights from the company’s data. Tableau does require additional training to be able to effectively utilize the tool, so the developer offers many how-to videos in the learning and support section of their website.
Visualizing data is important because, often, it greatly improves how we understand the information being provided and this increases the likelihood that the insights gained will be used properly. Without visualizations, we run the risk of misunderstanding data or not being able to truly analyze the data at all.
Check out last week’s post