The data that has been gathered and imported into Tableau is just the starting point for data analysis. The insights gathered from the program’s information are possible because of the specific tools used in the platform. Without knowing how to manipulate the data provided, analysis would not be possible using Tableau. Once a user becomes familiar with the programs features and understands how they work and how they relate to the information, exploration of the data can begin. With a moderate skill set in Tableau, you can uncover valuable information to support data-driven business decisions. Below we’ll explore the filter function.
Filters are a very useful tool when manipulating data in tableau. When you’ve decided on the information that you would like to explore, filtering allows you to pull only relevant data to the specific query. Filters can be used by the filtering shelf, an interactive filter, or in the sheet view. Using the filtering shelf requires dragging dimensions into the panel to the left of the sheet view labeled, filter, and selecting which dimensions you’d like to keep or remove. An interactive filter is accessible by right-clicking on a property in the dimensions panel and selecting show filter. This will add the property to your sheet. Lastly, you can click a data point directly on the populated sheet and choose to include or exclude the information for the sheet view. Filtering is useful when trying to get a narrower view of the aggregate data, like within specific categories or subcategories. For example, I would like to determine how many of a private practice’s patients are male and with hypertension. I would filter out the category of women, and only include the subcategory of hypertension.
Are there specific patient trends you think will help in knowing how to improve the healthcare service you provide? Maybe you’d like to determine how often patients visit your practice for routine check-ups or if a particular age group of female patients have underlying heart conditions. Filtering your information can be used to pull the data necessary to examine these trends. If you haven’t, read my last blog on Tableau: Live or extracting data and joins.