Who doesn’t like a special lens that enables us to zoom in on important data, showing the patterns and details that may have missed. Such a super tool which assists us in making sense of the complex data is Tableau Filters. Tableau filters will make your data stories more exciting and clearer from making the data work quicker with “Extract Filters” to smarter queries with “data source filters”. Tableau Filters are the robust feature in Tableau that allows businesses to produce advanced results by presenting insightful data in powerful dashboards. Using filters in Tableau, business enterprises can make better business decisions. Moreover, filtering deletes a range of values or removes irrelevant or needless records from Tableau's source dataset. Further, using filters in Tableau for an organization has many benefits. In this blog, you will explore what Tableau is, Tableau filters and their types, and how to apply them.
Tableau is the topmost one among the popular BI and data analytics tools. It empowers businesses and individuals to use data analysis to make the most of their data. Tableau allows users to build multiple charts, graphs, maps, and dashboards to analyze and visualize data for better decision-making. Moreover, Tableau is used across various industries worldwide. Many leading global brands such as Coca-Cola, Skype, Citigroup, Wells Fargo, Amazon, Facebook, and many others use Tableau in their operations.
In other words, Tableau is a powerful reporting tool that combines data collected from different data sources for visualization. Data visualizations represent data most insightfully. Further, Tableau makes the data easier to understand for business users and other individuals. It helps them make many informed decisions by analyzing the whole data in a single place. Furthermore, Tableau can integrate with other platforms or tools like Hadoop, MongoDB, etc.
Filters in Tableau are the smart way to separate data on various factors, removing irrelevant data from the source dataset. Tableau filters help users to minimize the data frequency for better and faster data processing. Moreover, filters in Tableau help to build powerful dashboards, and they also restrict the size of datasets for better use. Also, these filters help businesses to simplify and arrange data in a better way. In other words, Tableau filters allow the sorting of large data sets for business organizations for better analysis. It makes the data size minimum, helps with faster processing, and delivers the results on time. Also, these filters help highlight the underlying data insights derived from visualizations functionally.
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Filters in Tableau provide the most brilliant way to split large datasets and reduce their size to a minimum for better data processing. There are different types of Tableau filters available for other purposes.
The name of the Filter itself says that it helps to pull out data from a data source. The extract filters in Tableau help sort out the small data extracted from a different or an actual data source. After data extraction, Tableau helps to create a local copy of the data for storage in its repository. Also, it helps to further reduce the size of your dataset for analysis.
To build an Extract filter in Tableau, you can follow the below steps:
This Tableau filter helps to filter or sort out any sensitive or important data and restricts it from other viewers. Also, it reduces the data feeds additionally. Further, it allows viewers with some access rights for viewing underlying data. Data source filters are performed on both links: live and extract. The Tableau filter helps to implement the filter area to the actual data quickly. Also, it uploads data much faster and fits the space inside the workbook of Tableau.
Some Tableau filters work independently and generate their results. Context filters in Tableau are the independent filters separate from the other filters. They help to build different datasets from the actual datasheet and compute the predictions inside the filtered dataset. Also, you can use this Filter to improve the performance of many vast data sources. Even if viewing the entire data rows is unnatural, you can apply it to select the sheets as you need to optimize the performance by reducing the data size. The following are the steps for the Context Filter:
In the Tableau filters, dimension filters are the non-accumulated filters generally applicable to columns such as Client Name, Region, Country, City, etc. Based on the task you are performing, you can filter the data category wise. In other words, dimension filters are those when you use a particular dimension or volume to filter data inside a workbook. You can apply this type of Tableau filter in different types using top/bottom conditions, formulas, or wildcards. To apply it:
You can use the measure filter in Tableau to filter the data where the data values exist in terms of measure. Using this Filter, you can compute various actions like Sum, Standard Deviation (SD), Avg, Median, etc. functions. In the Tableau measure filter, you will have the following filter types:
You can do the same within a specific configuration whenever you drag the data for filtering. All aggregated or accumulated filters are applied after non-aggregated filters, and the measure filters are applicable to compute the fields with computable data.
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You must load the required data into the Tableau Workspace and then create data visualizations. There are specific steps to perform the above actions. After these steps, you can add filters in the Tableau dashboard in the following way:
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Conclusion
Thus, you have learned about Tableau filters, types of filters, and their implementation process in Tableau. These filters help users to sort out sensitive data while loading data into the workspace. It helps to resize the large dataset to reduce efforts and faster processing. Hence, you can perform different organizational tasks using these filters in Tableau.
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Tableau Filtering is the feature in Tableau and the process of deleting the irrelevant values from the result dataset.
Measure Filters are considered much faster than other filters except the Extract and Data Source filters.