6 Types of Filters in Tableau: How You Should Use Them

Tableau is one of the most popular tools in data visualization and analysis that facilitates brands across all domains to leverage the reckoning potential of acquiring Business Intelligence. For its seamless capability to yield readable insights and simplified dashboards, tableau has been instrumental for even non-technical subscribers to have access to personalized datasheets.

Tableau Filters benefit organizations because they help them present insightful data to clients and business stakeholders. This data is presented in the form of a worksheet or a dashboard. This facilitates better decision-making in business. The tableau filters can filter out sensitive data and share it only with those with access authority.

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There are different types of filters in a tableau that can be used to organize data based on predefined conditions and use them for data visualization. Such ability to filter large data sets in the Business Intelligence tool helps prepare for analysis, including removing irrelevant data records, reducing data sizes for faster processing, and more. The filters are required to highlight any underlying insights that can be derived from the data upon visualizing in a readable, actionable format. Check out our data science courses to learn more about data visualization.

You can go through the different types of Tableau filters discussed below if you are confused about which of the following are appropriate uses for filters in tableau? select all that apply.

Different Types of Filters in Tableau

Filters are a smart way to collate and segregate data based on its dimensions and sets to reduce the overall data frequency for faster processing. There are six different types of filters in tableau desktop based on their various objectives and are mentioned below as per their execution steps.

1. Extract Filters

As understood by its name, the extract filters are used to extract data from the various sources, by saving a screengrab of the way it gets added on your file. Such methods can help in lowering the tableau queries to the data source. As soon as you are done extracting data into your dashboard, you can create the extract and execute Hide All Unused Files to clear the columns unused in the datasheet of your panel. 

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The extract filter in Tableau extracts a tiny subset of data from the primary data source. Subsequently, Tableau creates the data set’s local copy, which will be saved in the repository.

This filter allows you to save a screenshot of how it appears in your workbook. The corresponding methods decrease Tableau queries. The data size can be decreased even more by implementing the dimension filter or measuring the extract as needed.


The steps to create an Extract filter in Tableau:

  1. Connect Tableau with the text file.
  2. Click on the “Extract button”. It will create a local copy in the Tableau source.

iii. Select the “Edit” option from the drop-down menu close to the Extract button in the upper right corner. It will open the Extract Data window. Now select the “Add” option in the Window.

  1. In this step, you need to select a Tableau filter condition from the “Add Filter” window. You can add any of the displayed fields as an Extract filter. Now select the category from the list and then click “OK”.
  2. A filtered window will be shown. It depicts data that was extracted through the Extract Tableau filter. You can customize the list or use all values within the list.

The extract filter is one of the versatile tableau filters. This is because it presents various options in addition to the general category to extract data. For example, the Wildcard option helps you to filter fields through a Wildcard match. It allows users to type the character, and the field will be filtered as per the match. The various types of matches are:

  1. Contains: Select the members if the member name comprises typed characters.
  2. Starts with: Select the members if the member name begins with typed characters.

iii. Ends with: Select the members if the member name terminates with typed characters.

Exactly matches: Select the members if the member name precisely matches with typed characters. 

These matches help you to customize your data and finally provide you with filtered data.

 You can filter data using various Byfield conditions after implementing the below steps:

  1. Select the “Condition” tab in the Filter window.
  2. Click on the “Byfield” button.

iii. Select the name of the field you want to filter.

  1. Now select the aggregation type like average, sum, and median from the drop-down list.
  2. Select an operator from the drop-down list.
  3. Enter the value to filter the selected field.

vii. Click “OK”.

2. Data Source Filter

Used mainly to restrict sensitive data from the data viewers, the data source filters are similar to the extract filters in minimizing the data feeds for faster processing. 

The data source filter in tableau helps in the direct application of the filter environment to the source data and quickly uploads data that qualifies the scenario into the tableau workbook. To execute such processes, you need to go to the Data Source tab and select the Add option in the upper right corner. 

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Clicking on the Add option in the menu would open into a dialog box, where you can select the field and choose through the values you want to record. Once you press confirmation, you shall be presented with a summary of the presets selected from the data source filters. 

3. Context Filter

A context filter is a discrete filter on its own, creating datasets based on the original datasheet and the presets chosen for compiling the data. Since all the types of filters in tableau get applied to all rows in the datasheet, irrespective of any other filters, the context filter would ensure that it is first to get processed.

Despite being constrained to view all data rows, it can be implemented to choose sheets as and when required to optimize its performance by minimizing the data efficiently. 

The context filter helps in applying a relevant, actionable context to the entire data analysis in tableau. If there are multiple filter preset categories used in the worksheet, dividing it into many parts can overall turn into a context filter in itself that guides all the other filters present in the datasheet. 

It helps you to generate data sets by employing appropriate presets for compilation. It is always processed first, although other tableau filters are used. The multiple preset categories existing in the worksheet can be categorized into several parts that would work like a context filter. The data sets are generated according to the original datasheet. Moreover, the data can be efficiently minimized to allow viewing of all data rows, notwithstanding the constraints. You can choose the sheets when required.

You need to open the Context menu of a prevailing categorical filter and choose “Add to Context”. The context is calculated after the view is created. Subsequently, the context is used to count all other filters.

Go to the context menu of a prevailing categorical filter and select Add to Context to make a Context filter in tableau. Once the view is created, the context is calculated. The context is then used to calculate all other filters. You can use Context Filter to find the topmost 10 subcategories of items in the Furniture category.

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4. Dimension filter

Now that you’ve chosen the data, you can access the values highlighted or remove them from the selected dimension, represented as strikethrough values. You can click All or None to select or deselect based on your operation in case of multiple dimensions. 

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5. Measure Filters

In this filter, you can apply the various operations like Sum, Avg, Median, Standard Deviation, and other aggregate functions. In the next stage, you would be presented with four choices: Range, At least, At most, and Special for your values. Every time you drag the data you want to filter, you can do that in a specific setting. 

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Aggregated filters are always employed after non-aggregated filters, irrespective of the order present on the Filters pane. Measure filters are used to measure fields comprising quantitative data.

Measure filter in tableau shows four types of filters, as mentioned below.

  • Range: Selects the range of values to incorporate into the result
  • At least: Selects a measure’s minimum value of
  • At most: Selects a measure’s maximum value
  • Special: Selects null or non-null values

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6. Table Filters

The last filter to process is the table calculation that gets executed once the data view has been rendered. With this filter, you can quickly look into the data without any filtering of the hidden data. 

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In addition to these six major types of filters in Tableau, you may have to use other types of filters. Some of them are discussed below.

 Quick filter:

It helps you to quickly access different filter types in Tableau through the right-click option. It owns features required to fulfill all typical filtering needs. You can implement Quick filters in Tableau on measures or dimensions.

Global filter:

It can be used over multiple worksheets by using the same source data in a workbook. Moreover, it can be used on all worksheets by utilizing the same data.

 Cascading filter:

It allows for the selections in the first filter to modify the options in the second filter. So, it restricts the values to those that are only significant to the first filter. Moreover, it avoids users from choosing irrelevant data. Hence, it offers an improved user experience.

 User filter:

Its alternate name is row-level security. This filter in tableau restricts and administers the data that users can view or access depending on the authority specified.


This is how different types of filters in tableau work in various processes.

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What are some of the basic filters in Tableau?

Filtering is the process of removing certain information from the available data by putting different filters. Tableau is the most widely used data visualization tool with plenty of features to simplify the process. Tableau provides both basic filters to deal with simple scenarios and advanced context-based filters for performing complex calculations. The three types of basic filters available in Tableau are: Filter Dates – This filter is applied on the date fields to remove specific date entries that are not required. Filter Measures – This filter is applied to the measure fields to remove specific measures based on the requirements. Filter Dimensions – This filter is applied on the dimension fields for removing certain measures that are not required for the calculation.

What is the difference between a normal filter and a quick filter in Tableau?

In Tableau, filters are useful for restricting the data from the database. There are different types of filters available in Tableau for performing different functions. Every filter has its own purpose and use, which makes it a worthy one in the list of available basic and advanced filters in tableau. A normal filter is useful for restricting the database's data based on the selected measure or dimension. This traditional filter can be created by simply dragging a field onto the shelf of filters. Quick filter helps us view all the filtering options and filter every worksheet on the dashboard by changing the values dynamically. This could be done even during the run time within the range that has been defined.

What are the different types of filters based on the purpose available in Tableau?

Tableau filters can be utilized for restricting the number of records that are present in a worksheet. Different types of filters are applied to a dataset based on the purpose and requirements. The filters are executed in a particular order for performing all the actions. The following is the list of the filters that are sorted in the order of their execution in Tableau: Extract filters Data Source filters Context filters Dimension filters Measure filters Every filter has its own purpose and is used for organizing and simplifying the available dataset in different ways through its application.

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