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Why is Google Data Studio so slow?

Written by Alexander Billington, Community Growth Manager at Funnel
4 minute read

As a digital marketer, you likely spend considerable time building marketing reports in Google Data Studio. So you may occasionally get a little frustrated when it takes a while to load. It is that annoying amount of time, right? Not long enough to do anything else, but long enough for you to look at the ceiling and think about what you’re going to have for dinner tonight…

Not to worry, Funnel is here to help! I’m going to give you three solutions to speed up Google Data Studio.

  1. 1. Decrease the scope of your dashboard

  2. 2. Utilize Google’s extract data connector

  3. 3. Use Funnel’s Google Data Studio views to export your data

Automating marketing data is easy and simple with Funnel

What actually affects the performance of Google Data Studio?

Deep in Google’s help section, you’ll find an article explaining the following reasons for slow performance:

  • The performance of the underlying data set
  • The amount of data being queried by the visualizations in the report
  • The complexity of those queries
  • Network latency

Essentially, Google is suggesting a large amount of complex data flowing into a report could be responsible for slow performance.

While I can’t help you with network latency, there are three ways to speed up your marketing reports in Google Data Studio.

1. Decrease the scope of your dashboard

The first port of call is to take a look at your dashboard. As your marketing operation grows in complexity, the amount of information you want to report on typically increases. What started as a simple marketing report with a few breakdowns displayed in 4 or 5 widgets can easily become much larger with more granular breakdowns including multiple pages with lots of widgets.

When Google Data Studio refreshes the data in a dashboard, it does so by making a request for each widget, so naturally the more widgets, the larger the strain on performance. With this in mind, consider breaking up dashboards into different reports.

2. Google’s Extract Data Connector

This source type functions slightly differently from a typical data source. Rather than Data Studio requesting all of your data all the time from your source, Google’s extract data source can be set to only request some of your data some of the time.

So what does this mean in practice:

  • You can connect your data source with the extract data source and select the fields you want in your report rather than sending all your fields.
  • The connector then saves and stores that data in what can be thought of as an intermediate step between your data source and data studio.
  • Your report then only requests data from the selected subset that you have saved, which reduces ‘the amount of data being queried by the visualizations in the report’ and ‘the complexity of those queries.’

How Google Data Studio creates digital marketing dashboards

Downsides of Google’s Extract Data Connector

  1. You are limited to 100Mb of data which might not be enough for granular, informative reports.
  2. Data is not refreshed in real-time but daily, weekly or monthly, so you cannot maintain real-time automated reports in the same way.

3. Use Funnel’s Data Studio views to export your data

Once you have imported data from your various marketing platforms with our stable API connectors and organized that data using our flexible transformation layer, you have the option to export to your desired destination. 

There are two options when exporting data from Funnel to Google Data Studio.

A. Sending all of your data to Data Studio

  • Like a typical connector we discussed above, you can send all of your fields to Google Data Studio and work with them there.

B. Creating a subset of your data called a "view”

  • Funnel offers users the ability to create what we call “views”, a subset of your data to send to Data Studio. Here I have created a new view titled “UK Market 2021 Report”.

How to segment data before sending it to Google Data Studio

Like the extract connector, a view allows you to choose fields instead of all your data. However, the data stays in Funnel, so you aren't limited to 100Mb, and the data is refreshed in real-time.

Choosing the right metrics and dimensions for your marketing report

Once fields have been selected, in this case I've chosen eleven of my core data points, Funnel offers the opportunity to add filters and further reduce ‘the amount of data being queried by the visualizations in the report’ and ‘the complexity of those queries’.

Filters can be used to include or exclude parts of your data to narrow the subset further. In the example, you can see I have only included data from 2021 and from the UK market, but you can build your own logic and include or exclude data depending on the type of digital marketing report you want to produce.

Connecting data as fields to digital marketing report in Google Data Studio

Once you have selected your fields and created a view, you simply click connect to Data Studio, and then your chosen data appears in the report ready to use.

Working with marketing data in Google Data Studio dashboards

Like Google’s extract data connector, Funnel helps you reduce the amount of data being queried, but with two main advantages:

  • No limit of data being processed in Funnel so your report can be as granular as necessary
  • Data is updated in real-time, meaning you can maintain automated, real-time marketing reports

How to make Google Data Studio faster with Funnel

Click here to read more about creating Data Studio views in Funnel