How to Connect Multiple Data Sources to Looker Studio

Most organizations use dozens of apps – be it for running a cross-channel ad campaign, bringing together sales data from different stores, or just for keeping track of projects. So, it’s often necessary to include quite a lot of data sources in a Looker Studio report.

However, the more apps you connect, the slower Looker Studio gets. In fact, it’s not that fast even with two data sources connected, so if you add dozens of them, performance will be severely affected. Such visualization might be quite hard to use, and you definitely don’t want your graphs to get frozen in the middle of a presentation. But how can you overcome this problem?

Read on to find out how to connect as many data sources as you wish and easily visualize your data from numerous apps without sacrificing performance.

If you need to use multiple data sources in Looker Studio, what are your options?

There are a couple of ways to do this. Which is right for you, depends on what apps you use and how many you want to connect to Looker Studio. Here are three main options:

• Connecting data sources natively. This allows you to connect multiple data sources to Looker Studio quickly and easily, and completely for free. The downside is that the number of apps offered by Looker Studio natively is very limited. Currently, there are only 23, and most of them are various Google products. If you need an app that’s not on the list, you’ll need a third-party connector.

• Using a third-party solution. Looker Studio features hundreds of partner connectors – solutions created by third-party developers. Whatever apps you use, the chances are, someone has already built a connector for them. An advantage of third-party tools is some of them allow blending data prior to importing it into the destination app. This means you can combine data from several sources in advance and connect all your data to Looker Studio as a single dataset. So, as a result, you will get a dashboard with data with multiple sources, and the performance won’t be affected. The downside is that these solutions are mostly paid. Also, you need to choose carefully because their quality and reliability may vary a lot. 

• Establishing a connection via an API. This method requires working with APIs and is more technical. It allows you to create a custom connection tailored to your specific use case. We won’t be covering this method in-depth as it’s already well described in Looker Studio’s API documentation.

In this article, we explain step-by-step how to use the first two options – native connectors and third-party solutions. For the latter, we will take as an example a popular data analytics and automation platform, Coupler.io. It can be useful for many data-related tasks, but what interests us now is that it allows you to extract data from over 70 business apps and transfer it to Looker Studio, as well as to Google Sheets, Excel, and BigQuery.

And, what’s important, Coupler.io has an in-built data transformation module. You can use it to blend data from multiple sources into one dataset before sending it to Looker Studio. In addition, Coupler.io can refresh your data in the destination app automatically on a schedule, supplying you with fresh data for near real-time monitoring.

Both options, native connectors and third-party solutions, have their advantages and can be a good fit for you, depending on your case. 

Let’s summarize what you get with each of the options in a brief overview.

Connecting Looker Studio to multiple data sources – a summary

Parameter	With native connectors	With a 3-party solution (Coupler.io)
Number of apps available	23	75+
App type	Mostly Google products	Popular business app from various domains
Apps available	Google Analytics 4 Google Ads Google Sheets BigQuery YouTube Analytics My SQL Google Search Console Google Ad Manager 360 Google Cloud Storage NEW Search Ads 360 PostgreSQL Search Ads 360 Campaign Manager 360 Cloud Spanner Cloud SQL for MySQL Display & Video 360	Facebook Ads LinkedIn Ads Google Ads Instagram Ads Mailchimp Pipedrive Excel Google Sheets Google Ads Google Analytics 4 Calendly Shopify Salesforce Hubspot YouTube Tableau Stripe See the full list of 70+ sources
Calculable metrics and blending data	Must be done on Looker Studio’s side and slows it down	Can be done on Coupler.io’s side prior to importing data to Looker Studio. Doesn’t affect your dashboard’s performance.
Performance with adding multiple data sources	Performance affected The more data sources you plug in directly into Looker Studio, the slower it gets	Performance not affected You can connect an unlimited number of sources to Coupler.io and blend your data. Then, Looker Studio will only be connected to one data source – Coupler.io
Price	Free for the native 23 sources, except for the cases when you need to pay for using the connected app (e.g, for queries in BigQuery).	Free for the 14-day trial, then from $49/month

So, if you want to connect 3 and more sources and/or not all your sources are available natively, then you should opt for a partner connector. You can use it to plug in even natively available apps as well – it will be easier to manage all the connections from one place.

What’s important here is to find a tool that will feature most or all of your apps. And it also needs to have data transformation capabilities so that you can blend data before sending it to Looker Studio and then plug it in as one data source. Then you will get a visualization with data from multiple sources, and the performance won’t be affected.

If you opt for a tool that doesn’t offer data transformation, you will have to plug in data sources into Looker Studio one by one, making it slow. The same goes for connecting several apps separately with native functionality.

In the next sections, we explore this in more detail.

How to connect Looker Studio to multiple data sources in bulk with Coupler.io

In this example, we will connect Google Ads, Facebook Ads, and LinkedIn Ads to Looker Studio to create a cross-channel report.

Setting up an automated integration consists of two parts. First, we will plug in the three apps into a Coupler.io importer. Then, we will connect it to Looker Studio and enable scheduled data transfers. 

Step 1. Connecting multiple data sources

• Select your first data source and the destination – here, it’s Google Ads and Looker Studio.
• Alternatively, you can select any of the 70+ available business apps, including GA4, Mailchimp, Airtable, Instagram Ads, and many others.

• Click Add Account and connect your Google Ads account. Then, press Continue.

• Select the data entity you want to export from the drop-down menu. In our example, it’s Campaigns.
• Then, choose your Ad account. If you have several sub-accounts in your Google Ads account, you can add more than one. Click Continue.

• In the next step, specify your preferences for additional settings, such as date range for your report, conversion window, and some others. If you don’t have any preferences, you can skip this part. By default, Coupler.io will load data for the last 30 days. Then, click Finish and Proceed.

• Now, let’s add the second app and then blend campaign data from both sources into one dataset. Press Add one more source.

• By default, you will see the same app pre-selected as a new source – in our case, it’s Google Ads. If you want to extract other data entities from Google Ads, you can proceed and repeat the same steps, but select another data entity. Google Ads with the other entity will be added as a new data source. You can add as many as you like.

• But in this example, we are going to connect another app – Facebook Ads. Press Change and then select the app you want to add from the dropdown list.

• After this, complete the same steps that we’ve already described for Google Ads – press Add account, connect your account, select data  entity (Campaigns, the same as for the first source), and specify other settings.
• To make our data visualization more informative, we will add a third data source – LinkedIn Ads. Here’s what the result looks like:

• As we are exporting Campaign data from all three apps, we can now blend it into one dataset. Press Transform data. On the Preview results tab, you can see the result of combining data from the three sources. 

• Since data is combined based on column names and each of these apps use a different naming convention, you’ll need to perform some transformations right away. Our suggestion would be to determine the set of metrics you want to collect for each channel (e.g. Impressions, Clicks, Conversions) and adjust the naming in each of the sources. Hide the columns you won’t need so that the dataset becomes easier to process and understand (added bonus – by importing less data to Looker Studio, you make it faster). 

• In Coupler.io’s data transformation module, you can also add new columns with calculated fields for custom metrics, hide or rearrange columns, sort and filter your data, and so on. After this, jumping back to the Preview results tab, you’ll see a nicely combined dataset to send to Looker Studio. Once everything is ready, click Proceed.

Step 2. Connecting the selected sources to Looker Studio

• Now, let’s plug in your Looker Studio account. Follow the instructions in the wizard to generate a token, then copy it and click the Looker Studio button. 

• Complete the remaining connection steps following the instructions in Coupler.io’s interface: authorize access for Looker Studio and paste the token into the respective field. After this, click the Connect button. 

• Then return to the Coupler.io interface and finalize setting the importer to schedule automated updates. First, click Save and Run to transfer the latest data.

• Data from the three apps was successfully imported into Looker Studio.

• To set up the schedule for the updates, toggle on the Automatic data refresh feature. Then, specify your preferences. In our example, we selected daily updates at 9:00 AM, Monday to Friday. At this time, Coupler.io will regularly send fresh data from the connected sources to Looker Studio. Click the Update Schedule button once you are ready.

• Press View Results in the top right corner to start working with your data.
• In the next step, you can preview the fields that are about to be included in your report. You can also check and edit field types if needed. Click Create report to start visualizing your metrics in a new report. 

If you are new to Looker Studio and need help with creating different chart types and building a dashboard, you can check our Looker Studio Tutorial: Dashboard for Beginners. Alternatively, you can request help from our data analytics team, and they will build a comprehensive dashboard for you and help you with data analysis and any other data-related tasks.

In this section, we connected Looker Studio to Facebook Ads, Google Ads, and LinkedIn Ads. Curious to see what the final result looks like? Then take a look at our examples of ready-to-use dashboards built in Looker Studio with the help of Coupler.io.

How to connect multiple data sources in Looker Studio one by one (natively)

In case you don’t need a data automation solution for your current tasks, let’s explore the native method. As we’ve already mentioned, if you plug in three or more data sources into Looker Studio one by one (not as a single dataset), your visualization will slow down. The more sources you add, the slower it gets. (This refers to connecting data sources separately both with a native method and via third-party connectors). However, such an option might do the trick for some use cases. Let’s see how it works.

For example, we have an Audience Behaviors Overview dashboard. Now the report is connected to Google Analytics, and we want to add Another Google Analytics account to consolidate this data. Let’s see how to do this.

• To connect multiple data sources to Looker Studio, open the report you want to edit and press the Add data button in the menu bar as shown below.
• Alternatively, you can achieve the same result by going to Resource -> Manage added data sources -> Add data source, or just click +Add data in the lower right corner.

• After this, you will see the list of available connectors. Select the connector you need and follow the instructions to add the selected data source to your Looker Studio account. In this example, we’ll connect another Google Analytics account. 

• Click on the Google Analytics tile, and then click Authorize. Log in to your account to connect it. Then, select the sub-account and property you need and click Add.
• For other apps, these steps will be mostly the same.

• After this, the data source we’ve just added appears on the list in our report. ​​Google Analytics data from the second account is now available.

• If the data source is already connected (for example, if you use it in another report), there’s a slightly different way to add it. You can press Add data as we did in the beginning, then switch to the My data sources tab. Select the source you want to connect and click the Add button. It will be included in the report sources shortly.

Using the method described above, we can connect more sources to the report. 

However, it’s worth mentioning that Looker Studio allows you to connect no more than 5 sources per app. For example, you can connect 5 tabs from Google Sheets, but you can’t connect 6 or more tabs. If this is a blocker for you, you can use Coupler.io to blend data from multiple sources before loading it to Looker Studio – in such a case, Looker Studio will treat this as just one data source, Coupler.io.

Now you can use multiple data sources in Looker Studio. However, remember that the more sources you plug in, the slower your dashboard will get. If you also need to sort or filter your data or perform some calculations, this will further affect performance. Such a visualization might be difficult to use.

So, if you need to connect a lot of apps, it makes sense to consider a third-party tool that can connect to all or most of these apps, blend data on its side, and load a ready-to-use dataset to Looker Studio. We already explained how to use this method in the previous section.

Now, let’s see how you can combine data from different sources in a Looker Studio report.

How to use Looker Studio with multiple data sources in one chart

Once all your data sources are connected, you might want to combine their data in one chart or table. To do so, you will need to use Looker Studio’s data blending functionality (that is, if you decided not to blend data with a third-party connector).

There are two main methods that allow you to do so:

• Automatic blending – in this case, you select two tables you want to merge and let Looker Studio analyze them and decide what join key to use and how to combine your data. This method is quick, and sometimes it works smoothly. But quite often you will need to edit the results as Looker Studio doesn’t always merge data the way you wanted to.

• Step-by-step blending – with this method, you will need to manually configure the tables you want to blend, choose the dimensions and metrics, and specify how to blend them (select the fields to include into your join key). This requires more effort, but you will get a more quality result.

Let’s take a quick look at both options.

Blending data in Looker Studio automatically

Here are the steps to combine data from two data sources in one table:

• Connect your data sources to Looker Studio. 
• Add data you want to blend to the report, then select the charts you are going to merge and right-click to see the menu. Select Blend data.

• Looker Studio will merge your data automatically. Then, check the result and use the menu on the right to make the edits, if necessary. For more advanced settings, such as changing the join operator for your join key, click the pencil next to your data source. We’ll talk a bit more about the join operator types in the next section.

Combining data in Looker Studio step by step

• Connect your data sources to the Looker Studio report.
• In the Looker Studio menu, click Resource -> Manage blends -> Add a blend.
• Add the tables you need to combine and choose metrics and dimensions to blend. 
• You will also need to select a join type so that Looker Studio knows how to blend your data. 

There are five join types, or join operators, in Looker Studio:

• Left outer – creates a dataset containing matching rows from the right table, plus non-matching rows from the left table. This is a default option. 
• Right outer – Pulls all matching rows from the left tables, plus non-matching rows from the right table.
• Inner – blends only matching rows from the left and right tables, and leaves out the rest.
• Full outer – creates a dataset containing all rows from the left tables and right table, whether they match or not.
• Cross – returns every possible combination of rows from the left and right tables.

In the join conditions section, you will also need to specify how dimensions in table A correspond to those in table B and what to combine with what. This set of fields will be your join key – parameters for “joining”, or blending, your data.

• Once ready, click Save. Specify the name for the new blended dataset in the upper right corner, in the Data source name field. Press the Save button below.
• That’s it! Now your blended dataset is ready for use. You can find it in the list of data sources under the name you specified in the previous step.

If you need more details about blending data from multiple data sources in Looker Studio, check out our Looker Studio Blend Data Tutorial.  

Note: if you use Coupler.io, you can blend data in an easier way with the help of Coupler.io’s data transformation functionality.

Examples of Looker Studio dashboards combining data from different sources

In the previous sections, we explained how to connect Looker Studio to multiple data sources. If we add enough data entities from each source, we will get a comprehensive dataset that can be visualized in an insightful dashboard like the one below.

See the interactive version of the PPC reporting dashboard in Looker Studio.

This data visualization was built by Coupler.io’s data analytics team. The dashboard is interactive and self-updating. It’s connected to Coupler.io, which, in turn, is linked to LinkedIn Ads, Facebook Ads, and Google Ads. It allows you to track sign-ups, conversion rate, impressions, and other metrics.
Of course, you can build similar dashboards using datasets from other different data sources. 

And here’s another example of a useful dashboard showing the performance of a sales team. This dashboard is also self-updating and interactive, which allows you to zoom in and explore your data from various angles.

See the interactive version of the Sales analysis dashboard in Looker Studio.

You can find more dashboard examples on our Data analytics services page in the Actionable dashboards section, as well as in our Free Templates Collection.

If you want to use our dashboards as templates or need any help with visualizing or understanding your data, contact us, and our data analysts team will help you with your challenges.

What is the best way to visualize data from multiple data sources in Looker Studio?

Using native connectors and opting for third-party tools are both viable methods that allow you to connect multiple data sources to Looker Studio. 

The first method is a good option if you only need to connect several apps and if they are mostly Google products and, therefore, come with a native connector.

However, for more complex Looker Studio reports, or simply for reports with different data sources that are not included in the native options, you will need to use a third-party solution. For example, Coupler.io can help you plug in more than 70 different apps. It offers you some valuable additional functionality, such as an intuitive data integration module and the ability to manage blended data with ease. You can also use it to automate and streamline all your data flows across your organization and increase efficiency with automation and optimization.

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