Fixing Slow Looker Studio for Better Performance

If you're experiencing slow performance in Looker Studio, don't worry, you're not alone. A large number of users are affected by this issue.

The first step to fixing slow Looker Studio is to check your data source. If your data source is not optimized, it can lead to slow performance. For example, if you have a large dataset with many fields, it can slow down your reports.

One way to optimize your data source is to use Looker's built-in data processing features. These features can help reduce the amount of data being processed, making your reports load faster. By enabling data processing, you can improve the performance of your Looker Studio reports.

By following these simple steps, you can significantly improve the performance of your Looker Studio.

Worth a look: Looker Studio Not Showing All Data

Looker Studio can be slow due to its 6-minute limit on handling queries, causing large data requests to slow down or time out your reports.

Large amounts of data can slow down your reports, making them load more slowly when processing large amounts of data.

You don't have to pay to create and set up a Looker Studio account, but the free version has limitations.

The performance of the underlying data set can also cause poor performance, especially if it's dealing with a great volume of complex data.

Google Data Studio reports can be slow due to the native Sheets connector or other Partner Data Connectors, which can be resource-intensive and slow.

Google Sheets is not designed to hold massive amounts of data, and the connector wasn't built to retrieve huge amounts of data quickly.

Data Studio returns to the original data source, discarding previously-arrived data, because it's not built to cache the results intelligently.

Dealing with incredible amounts of data all at once can slow down Looker Studio, especially if you haven't optimized it in a long time.

Network latency issues or using 3rd party connectors can also cause performance issues in Looker Studio.

Optimizing Looker Studio and its data sources is key to improving performance and preventing slowdowns.

Check this out: Field Editing in Reports Looker Studio

Optimizing data source queries is key to faster performance. This involves ensuring that underlying data sources are optimized for performance, writing efficient and well-structured queries to retrieve only the necessary data, and avoiding unnecessary joins.

Data sampling can significantly reduce query execution time and improve report loading speed. This is especially useful for large datasets where retrieving a subset of data for visualization is feasible.

Reducing visual elements on a page can also improve rendering time. Consider breaking down complex reports into multiple pages or dashboards to limit the number of visual elements.

Using aggregated data instead of raw, granular data can reduce the amount of information to be processed and improve rendering speed.

Here are some specific tips to optimize your Looker Studio reports:

Reducing dashboard complexity is key to speeding up Looker Studio. A cluttered dashboard can affect load times, so aim to use fewer dimensions in your reports and avoid too much data blending or pre-calculated fields.

Worth a look: Dashboard Google Data Studio

Having multiple charts and widgets on a report page increases the number of queries made upon loading, which can slow down your report's performance. Reducing the number of charts can help remove noise and keep your system from running too slowly.

You can try consolidating multiple widgets into one, such as replacing a group of scorecards that share the same data source with a single table or combining multiple time series charts with different metrics under one graph including optional metrics.

Another way to reduce the charts of a page is by allocating them to multiple pages. By doing that, the report will still include the same amount of charts, but each page will require fewer queries, resulting in faster loading times.

To minimize the use of custom calculations, filters, and data blends, remove unnecessary calculated fields in your data sources, optimize data blends, and delete outdated filters. These actions can help you achieve the speeds you need.

Using extracted data sources, such as the Extract Data connector in Google Data Studio, can also help speed up your reports. This connector allows you to explore a subset of your data by pulling them from your connectors and storing them as cache for later use.

Additional reading: Looker Studio Data Sources

Here are some common issues that can slow down your Looker Studio reports and their solutions:

Adjusting the data freshness of your data sources can be a game-changer for optimizing the performance of your Looker Studio dashboard.

You can set the data freshness interval to a longer time period, such as every 12 hours, to reduce the frequency of updates. This can help alleviate the burden on your data source and improve overall performance.

By utilizing the caching feature of Looker Studio, your browser can make a local copy of the most recent data, which can be accessed again without making the required queries from your data source.

For more insights, see: Looker Studio Open Source

If you're struggling with Looker Studio's slow performance, you might want to consider an alternative solution.

Using a dashboard platform with native integrations can greatly improve your experience. For example, Whatagraph offers 40+ native integrations to popular social media, PPC, e-commerce, and data analytics platforms.

Native integrations are much faster and more stable than 3 party connectors, which can result in a significant improvement in querying and visualization speed. This is evident in the example of a heavy widget that used to take about a minute to load, but now loads in just 10 seconds.

Whatagraph's custom API allows you to connect any platform or tool directly, while Google Sheets integration enables you to import any structured data from spreadsheets. BigQuery integration is also available, allowing you to connect your Google BigQuery data warehouse and visualize any data set stored there.

If you can't find your source in Whatagraph's list of integrations, or if you work with custom client-specific metrics, or use a niche marketing tool, Whatagraph still has you covered.

Related reading: Custom Query Looker Studio

Improving the performance of Looker Studio can enhance the user experience and efficiency. Here are three ways to make your Looker Studio runs faster.

First, to speed up Looker Studio, you can follow the tips that help you understand some of the ways that you can get better performance out of this tool. These tips can take your data visualization needs to new levels.

One way to improve performance is to improve the performance of Google Data Studio, which can be enhanced by following best practices. Improving the performance of Google Data Studio can also enhance the user experience and efficiency.

You can also improve performance by making your Google Data Studio runs faster, which can be done by following three ways: improving the performance of Google Data Studio, using the tips to get better performance out of Looker Studio, and taking your data visualization needs to new levels.

To get better performance out of Looker Studio, you can use the tips that help you understand some of the ways that you can get better performance out of this tool.