Filters are a key part of any dashboard in Data Studio, as they help you to present and visualise the data most relevant to you and your report users. Most commonly, filters are applied to specific widgets, for example a table showing the activity of Mobile sessions only, or a scorecard showing the count of a specific event. These types of filters differ from controls, as they cannot be adjusted while in the View mode of a dashboard.
How To Create A Filter
Creating a filter is a very easy process, with two main methods of doing so: The first involves opening the Data properties menu of any widget by clicking on it, and at the bottom of this menu you’ll see the Filter section, and a button for Add A Filter. Note, this is on the left side of the menu, with the right hand side listing your available fields, the dimensions and metrics within your data source. Once you’ve clicked the Add A Filter button, you will see a list of the filters currently attributed to your dashboard. You can select one of these, or click on Create A Filter.
The second method is very similar, starting with the Resources tab at the top of the Data Studio, and entering Manage Filters. This also brings up the list of available filters, with a button to Add A Filter at the end of the list. Whichever method you choose, you’ll end up the same result: The Create Filter menu.
This is where you’ll put the pieces together to form your new filter, such as the name of the filter, the Data Source it applies to, and the rules or clauses that form the filter itself. We recommend using very clear naming conventions when building your filters, such as “Device Category = mobile” or “Event Label = Add To Cart”; it will make life a lot easier down the line as the dashboard becomes more bespoke and more detailed.
Of course, while the name of a filter is important for user experience, the most important elements are the Data Source and the clauses. Select the Data Source your filter will be using, and you’re ready to write your first clause. There are only two options to begin with here: Include or Exclude. These work exactly as you’d expect, with the Include option only bringing in data that exactly matches the clause you create, and Exclude removing all data that matches the clause.
You’ll now have to select a Dimension or Metric that your clause is based on, Device Category for example. Once you’ve done this, another drop-down will appear, prompting you to select a condition. This is the next step of your clause, with conditions including operators like “Equal to”, “Contains”, “Starts with”, “RegExp Contains”. The list of conditions will differ slightly for Metrics, with operators like “Between”, “Greater than or Equal to” and “Less than” being available.
Once you’ve named your filter, assigned a Data source, and written at least one clause, you’ll be able to save your filter and apply it to your dashboard where relevant. You can of course create more complex filters, using the OR clause or the AND clause, creating additional rules within your filter. A single filter can have up 10 OR clauses applied, although a single widget can hold up to 75 clauses in total, so you could add multiple filters to a single component.
Applying Filters At Different Levels
We’ve looked at how a filter is applied to an individual component, but you can also apply your filters to multiple widgets (a group), an entire page, or the whole dashboard. To filter a group of widgets, you must first create your group by selecting the relevant widgets, then right-clicking or opening the Arrange tab, and selecting Group. When you first select a group, you’ll see the Group Properties menu in place of the Data and Style menu you would normally see when selecting a widget. At the bottom of this menu, you’ll see an option to Add A Filter, known as a Group Filter.
We can cast our filter net even wider by selecting the Page tab at the top of the interface, and entering Current Page Settings. This opens a very similar menu to the Group Properties, but this time these settings will apply across the whole page. This also adds a new element to the Data menu for every component on the page. If you navigate to the Filter section of a component’s Data menu, you see the Page Filter you’ve just applied, and a toggle for Inherit Filters. This allows you to decide whether individual components accept or reject the Page-level Filter. This is potentially a much more efficient method of applying filters across the an entire page, or the majority of a page, rather than manually adding filters to each and every component.
Finally, setting up a Report-level filter works much the same as its Page-level equivalent, however you’ll start the process by clicking on the File tab, followed by Report Settings. You can then once again toggle this on and off using the Inherit Filters options in components’ Data properties.
What Order Are Filters Applied?
A good question, pre-emptively assuming you’ll ask it. With multiple filters at play, prioritisation is required in the form of a filter hierarchy. In other words, the order in which filters are applied. The easiest way to remember this is that the higher level of filter, the earlier it is applied. Google refer to this as “filter inheritance”, and the order of inheritance or hierarchy is as follows:-
Bonus Tip: This hierarchy also applies to Data Controls, but in reverse, so if you have a Report-Level date selector for “This Month”, but have a page on your report dedicated to a quarterly marketing campaign, you can add a Page-Level date selector for the quarter to the page, which will trump the existing Report-Level selector. Additionally, if you wanted to show a specific chart of the campaign’s performance throughout the year, you could add a component-level date selection to that specific chart, and not worry about this applying to the rest of the page or report.
The Importance Of Filters In Data Studio
Hopefully this short guide has given you a better understanding of how Filters operate in Google Data Studio. Filters are one of the most important elements when using Google Data Studio, acting as an integral part of customising your report as you create efficient data dashboards. They can be used to refine your presented data, improving the user experience and efficiency of your dashboards, making It easier to see relevant data, and allowing you and your users to spend more time conducting analysis and forming insights.
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