Data is a significant and valuable resource for any business. The impact data has on organizations, their performance, ability to grow and maximize their potential is contingent upon data usage and application.
Tableau enables a business to analyze its data by using its various features such as filters, sorting, and grouping to discover insights that can be leveraged and help business leaders and managers make informed decisions.
Tableau Data Analyzing Features
Data filters are crucial in analyzing data because it narrows and limits the data shown to enable users to focus on pertinent information. Data are filtered by marks or individual data points, headers, or selecting data points from the view.
Data filters can be created by dragging fields such as measures or quantitative data, dimensions or categorical data, table calculations, and dates from the data pane to the Filters shelf. Data, when interactive filters are in view, is included or excluded. Interactive filters allow users to interact with the filter.
Data filters can be completed at the record or row level in the data source, in the aggregated view, or before the data is imported into Tableau.
Tableau enables users to control the order in which data appears in a table through the sorting feature. Sorting data in Tableau allows users to discover relationships between fields.
Data sorting in Tableau occurs in various ways, such as utilizing single click options from a field label, header, or axis. Data is also sorted manually from the Sort menu, legends and headers, and toolbar sort icons. Moreover, data can be sorted for specific fields through customization by sorting options such as alphabetic, manual, field, data source order, and nested using the sort menu in Tableau. While the alphabetic option sorts alphabetically, the manual option allows the user to choose a value and move it into the desired position.
The data source order option in the Sort menu allows data sorting based on the organization of data in the data source, and it is most common for relational data sources. The data source is a natural sort order in which multidigit numbers are sorted alphabetically and handled as a single character.
The field and nested option allow users to decide on the field with a value used to determine the data sorting. However, the data sorted is nested or non-nested. Data values that need sorting appear in multiple panes. Nested sorts consider the value independently per pane, sorting the rows per pane and does not convey aggregated information about how the values compare overall. Conversely, the non-nested sorts, although they may appear to be or perceived as incorrect in a single pane, takes into account the data values across panes and having an equivalent order of values per pane and consistently conveys the way aggregated values compare overall.
Grouping data in Tableau is a vital tool for users working with and handling large databases. It helps answer hypothetical questions and corrects data errors. Grouping data simplifies and reduces large numbers of dimension values by joining them into higher-level categories. Combining dimension values based on their similarities allows users to create groups used for analysis because they can convey insights.
Groups are created in Tableau to combine and merge two or more values in a field in various ways, including accessing the field option in the data pane and selecting data in the view, followed by clicking the group icon. Tableau enables users to group all remaining or non-grouped members with a feature known as the Other group. Additionally, the Include Other option helps compare specific or emphasizing certain groups.
Data filters and sorting is fundamental in increasing the user’s ability to explore data in greater detail. Additionally, as previously mentioned, data grouping is essential to simplify the vast amounts of data in databases that users encounter by combining and merging values based on similarities to develop a comprehensive and unified view of the data for analysis and obtain hypothetical answers to questions to discover insights. For instance, Chipotle, an American chain restaurant established in more than 2,400 locations worldwide, experienced difficulties analyzing their data before implementing Tableau. Chipotle’s diverse data sources prevented Chipotle from seeing their restaurants in a unified view to grasping a complete understanding of their restaurant operations and its operational effectiveness. Chipotle had several reports with similar information that created confusion across the company because the data reports had various sources of truth.
Chipotle realized they needed to group and organize their data into one central location accessible for everyone in the company to view together in the same manner and with an understanding of success consistently. Tableau enabled Chipotle’s Director of Business Intelligence, Zach Sippl, to create a prototype to show his executive team different ways and possibilities to view their data in a manner that they have never experienced.
According to Zach Sippl, “We were able to take this one metric and, from the top of our enterprise, be able to have a guided experience. Based on what we saw, go from that top of the enterprise, all the way down to an individual restaurant, to pinpoint exactly where we had amazing success or exactly where we really needed to focus. We started with our top leaders to help them understand where they could go with data.”
With a newly implemented self-service business intelligence (BI) platform with Tableau, Chipotle created a centralized view of their restaurant operations to view and track their effectiveness on a national level and use data to drive change, eliminate inefficiencies, and make data-driven decisions. Furthermore, the degree of accessibility to Tableau’s data increased Chipotle’s employee productivity, efficiency, and effectiveness. The rate at which reports were generated and delivered for strategic projects tripled from a quarterly basis to monthly and reduced and saved the company over 10,000 hours per month.
A business’s success in any industry consists of its ability to maximize its potential by applying knowledge, skills, and available resources efficiently and effectively. Tableau is essential in providing businesses with the tools necessary to attain actionable insights from their data to drive business growth, obtain optimal results, meet their goals, and achieve success.