Although Tableau is a powerful data analysis tool that can drive your business to success, understanding how to build the relationships in the platform as well as using the interface toolbar are essential criteria to that success. Data is always complex in nature and without the proper tools such as filtering, sorting, and grouping the data would be less likely insightful. Therefore, in this article I will be talking about the importance of these tools in making the data actionable and how to utilize them in Tableau.
Tableau Tools:
Filters: Filters helps extract, display, or analyze a subset of the data that satisfies certain criteria to learn valuable information about particular dataset. For example, considering a retail that sells various clothing products that has dataset with details on product sales, including product categories, sales figures, geographic locations, and dates. Once the data is structured with the right relationships, some filters can be utilized are region and time range. The region filter can help the business to track and compare the performance of sales across different regions, such as lowest revenue and highest product demand in specific regions. By adding the time range filter, the business can track the performance of specific month or year and compare it to current time data. This helps the business to understand the growth and decline demand of specific timeframe and how sales trends varies overtime.
Sorting: Sorting involves rearranging the data components in a structured way to make it simpler to analyze, interpret, and meaningfully present the data. For instance, considering the same clothing retail from pervious example, the business wants to know which are the top-selling products by quantity. By sorting the data in descending order, the business can easily identify the top-selling product by quantity, and by apply the region filter, the company can also learn where are the top-selling product in terms of quantity in each region. This helps the business to determine which products are performing well and which are underperforming in terms of quantity in each region so that they can adjust their resource allocation.
Grouping: Data grouping is the process of classifying or combining data elements with comparable qualities or traits into definite groups. It helps summarize and simplify the data to analyze and interpret. Given the previous examples involving the same business scenario, the business wants to group its top, moderate, and low selling products in each region into three distinct groups that contains all States data filtered and sorted in descending order. By looking at product performance in each regions in descending order, the business can identify and group the top 33.33% States in each region as well as the moderate and low performing states. The business now can easily determine which group of states that make the most sales in each region. Analyzing the data identify opportunities further growth of these high-performing states across the region by concentrating on maximizing the strategies and resources. Additionally, it makes it easier to manage inventory and stock, and it prioritizes with high sales to satisfy consumer demand.