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Table of contents
1.
Introduction
2.
Introduction to Filters in Tableau
3.
Features and Uses of Filters
4.
Examples of Filters
4.1.
Filter Dates
4.2.
Filter Dimensions
4.3.
Filter Measures
5.
Introduction to Various Types of Filters in Tableau
5.1.
Context Filters
5.2.
Extract Filters
5.3.
Data Source Filters
5.4.
Dimension Filters
5.5.
Measure Filters
5.6.
User Filters
6.
Frequently Asked Questions
6.1.
Do we need to learn coding to operate Tableau?
6.2.
Why are Filters helpful in Tableau?
6.3.
How many types of filters are there in Tableau?
6.4.
How can we add a filter in Tableau?
7.
Conclusion
Last Updated: Mar 27, 2024

What are Filters in Tableau?

Author Nidhi Kumari
0 upvote

Introduction

Tableau is a BI(Business intelligence) tool used for data visualisation. It helps to visually represent your data in a dashboard or worksheet. Tableau provides a single view of your complex data.

What are Filters in Tableau?

Companies use Tableau to identify patterns for business intelligence analysis, visualise data, and make the data easier to interpret. In Tableau, filters are beneficial for building dashboards or worksheets. Tableau provides six different types of filters to perform filtering. Let’s start this article by discussing what are filters in Tableau, and then we will move to the types of filters in Tableau.

Introduction to Filters in Tableau

To view only the data you are interested in, filtering is a useful tool in databases. The process of filtering involves deleting a specific value or range of values from a result set.

Based on parameters such as measures, dimensions, or sets, Tableau enables you to filter particular views or entire data sources.  Tableau filters are necessary to focus on any underlying ideas that can be derived from the data once it has been visualised in a clear, usable manner.

Both basic instances based on field values and complex calculations or context-based filters are supported by Tableau filters. Tableau filters are based on a criterion to reduce the number of records in the database. Even sensitive information can be filtered and shared only with those authorised to see it. What you wish to restrict your data set to will primarily influence which Tableau filter you select or which Tableau filters you combine.

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Features and Uses of Filters

Here is a list of various features and uses of filters in Tableau.

Features and Uses of Filters
  • Reduce the size of your data collections: Using filters you can reduce the size of your data to use them efficiently.
     
  • Exclude all unwanted dimension components: Filtering this kind of field typically entails choosing the values to include or exclude because dimensions contain discrete category data. 
     
  • Improve the underlying data: Filtering improves the quality of the underlying data by cleaning up the database. Other than Filtering one can also use Adding, Splitting, Grouping, and Renaming operations to clean up the underlying data.
     
  • Set date ranges: For properties with date, dateTime, and time data types, date range filters are supported. The results on a dashboard can be narrowed down to data that falls within (or outside of) specific date and time groupings using date range filters.
     
  • Measures if required: Quantitative data fields are often referred to as measures. Tableau's Measure filter supports a number of operations and aggregate functions, including sum, median, average, standard deviation, and others.
     
  • Simplify and arrange data: Filters provide data filtering and sorting options in Tableau visualisations. You may organise and customise your fields using its various features.

 

Examples of Filters

Let’s see an example of filtering to understand what are filters in Tableau.

Examples of Filters

Filter Dates

One can use the filters in the dates. Each option is displayed when a date field is pulled from the filter window. When applying the date field, Tableau handles it in three different ways. It can apply a filter by using an absolute date, a relative date measured against today, or a range of dates.

For example, You might be interested in your company's 30-day records or Year-to-Date sales. You can use relative date filters for the last 30-day records. You can also use the filter date option to view all orders placed between May 1 and June 1, 2023, for a range of dates.

Filter Dimensions

One can use the filters in the dimension fields. The filtering uses logical expressions such as greater-than- or less-than-conditions based on category values.

For example, One can apply dimension filters to the product subcategory of a company sales data. We design a view to display profit for each product category according to the delivery method.  For example, there will be three categories: land, sea, and air.

Filter Measures

One can use the filters in the measure fields. The measures fields' calculations are the basis for measure filtering. As a result, while dimension filters only allow values to be filtered, measures filters only allow computations based on fields.

For example, If you want to sum up all the sales of the current year. You can use the measure filter, to sum up all the twelve months' sales. It supports several operations and aggregate functions, including sum, median, average, and standard deviation. 

Introduction to Various Types of Filters in Tableau

There are mainly six types of filters in Tableau. Let’s understand them one by one.

Types of Filters in Tableau

Context Filters

The context filter aids in providing a pertinent, helpful context to Tableau's overall data analysis. The context is determined after the view has been constructed. Then, all other filters are calculated using the context. Select Add to Context from the context menu of an existing categorical filter to create a context filter. 

For example, you can use a context filter for your company sales data to discover the top 10 or top n subclasses of products in the Sales category. The standalone context filter is a separate filter that builds datasets based on the source datasheet, and the presets selected for data compilation. 

Extract Filters

Extract filter is used when the user extracts data from the data source. This filter takes a very limited data selection from the original data source. In the first step extract filter pulls a small selection of data from the main data source. 

Tableau then builds a local copy of the data set that will be stored in the repository. After connecting the text file to Tableau, you'll find the Live and Extract options in the top right corner of the data source pane.

Data Source Filters

The Data Source Filter in Tableau applies the filter directly to the data source, enabling rapid data uploads. You must open the Data Source tab and choose the Add option in the top right corner to carry out such activities.  

The Data Source Filter supports both active and extracted connections. Additionally, it can aid in reducing the volume of records in the data set.

Dimension Filters

Tableau filters, called Dimension Filters, are used on dimensional data. Dimensions in Tableau are separate fields that are often any field with categorical or qualitative data. The values that are highlighted or removed from the selected dimension using the dimension filter are shown as values with a strikethrough. 

It's a filter that is not aggregated and lets you add dimensions, groups, sets, and bins.  In the case of many dimensions, you can choose All or None to pick or deselect according to your operation. A Dimension Filter can be applied using the top or bottom conditions, wildcard match, and formula.  

Measure Filters

Quantitative data fields are frequently referred to as measures. The Measure Filter is a Tableau filter that lets users filter data based on a measure's values. Utilising various operations like sum, median, average, standard deviation, and other aggregate functions, you may change the data. 

You would be given four options for your values at the following stage: Range, At least, At most, and Special. 

User Filters

The User Filter in Tableau is the filter that secures a dataset's row-level data. The workbook can be used once it has been published on a server.  Row-level security is another term for it. 

Depending on the authority supplied, this filter in Tableau limits and manages the data that users can access or view. Different filtering criteria might be used for various users. It involves limiting the data that a user can access based on who is viewing the dashboard.

Frequently Asked Questions

Do we need to learn coding to operate Tableau?

No, you don't need coding experience to operate Tableau, but you do need the analytical mindset of a coder. Tableau is a BI solution mostly used for data visualisation. Tableau is an accessible and robust solution for data analytics because there are no prerequisites for learning it.

Why are Filters helpful in Tableau?

In Tableau, filters are beneficial for building dashboards or worksheets. Filters can assist in reducing the size of data sets for practical usage and eliminate pointless dimension components by cleaning the underlying data. Filters help in creating data ranges for analysis.

How many types of filters are there in Tableau?

There are six types of filters in Tableau. The name of these six filters is Context filters, Extract filters, Data source filters, Dimension filters, Measure filters, and User filters. In the business world, these filters promote improved decision-making. 

How can we add a filter in Tableau?

The first step is to Open the workbook in Tableau Desktop and establish a connection to the data you wish to filter. Select the worksheet and create a filter by choosing Server >Create User Filter. Then select the region that you wish to analyse.

Conclusion

In this article, we extensively discussed what are filters in Tableau. Filters in Tableau can assist in reducing the size of data sets for practical usage and eliminate pointless dimension components by cleaning the underlying data.

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