As a general rule, Data Studio reports load more slowly when they have to deal with larger amounts of data. Use the tips below — in addition to keeping queries as simple as possible, and using only as many chart elements as you need in each report — to keep your reports running quickly.
Data Studio requests data on demand, so the fewer features you build in a report, the faster it will load. To reduce features in your reports, consider these steps:
- Choose a single page or data source account at a time.
- Shorten your date range or use a standardized date range like "Last week" or "Last month".
- Reduce the number of dimensions and metrics included in a single chart, graph, or report.
- Use fewer complex calculated fields or blended data sources.
- Reduce the number of charts or graphs on a single page.
Data Studio has a 6-minute limit on handling queries, and large data requests might cause your report to load slowly or time out. With the Extract Data connector by Google, you can explore a subset of your data and improve the speed and performance of your report, or build reports for certain cohorts of data. Learn more in our blog.
Subset with selected fields
By default, data sources are created with a full list of their supported dimensions and metrics, some of which you may not need. Using the Extract Data connector, you can handpick the dimensions and metrics that are meaningful for your reports.
Subset with a filter or date range
In the Extract Data connector settings, you can define a subset of data based on a filter condition or date range.
For example, if your campaigns are targeted at multiple locations, you can use a filter to define that "Country" is equal to the location of your choice, filtering the whole subset of data to that country. In the date range section, you can limit the dataset to a preset time frame or set custom start and end dates for your subset of data.
Data storage solutions allow you to extract data from data sources ahead of time. This means Data Studio won't have to request it on-demand while you're running your reports, significantly reducing the load on it and improving its performance.
Based on how much data you want to report, use either Google Sheets or a data warehouse or cloud storage solution to extract and store your data.
At Supermetrics, we support BigQuery, SnowFlake, Azure Synapse, Amazon S3, Google Cloud Storage, and Azure Storage. Learn more about our data warehouse and cloud storage products.