Best practices and features for Data Studio reports

In this guide, we have compiled best practices and features for building advanced reports in Data Studio using Supermetrics connectors. Please take into consideration that most of the features mentioned here are native features built by Google. If you have any issues with these features, you can seek additional help in the Data Studio help center.


ON THIS PAGE


Data blending

The data blending feature in Data Studio gives you the flexibility to connect and blend data from several tables or data sources into one single source using one or several joined keys. To build a blended data source from scratch, please refer to our step-by-step instructions for using the Data Studio blending feature.


Below you can find common issues with blending data and how to avoid them.


Data is not joined correctly

If you've found that the individual data sources are not joined correctly in the blended data source, check if the individual data sources share joined values. You can first display the data by each data source, check if they have shared values, and then blend them together. 


For example, if you use Campaign as the join key between Table 1 and Table 2, the two data sources should share the exact same Campaign values — Data Studio is case-sensitive. The campaign "supermetrics" from Table 1 will not join the campaign "Supermetrics" from Table 2, and the blended table only shows the data of the farthest left table (Table 1).


If you use Date as the join key, make sure that the first table (farthest left table) covers all the date ranges. Data Studio uses a left outer join for blending, meaning data will be returned for all records from the farthest left table and all matching records from the right tables. If the first table is missing some time periods, the tables on the right will not show any data for these periods either.


Even if you use Date as a join key correctly, the blended table may show an "Invalid argument type" error message. Learn more about the invalid argument type error.


Duplicated results

You may find the blended data source to show duplicated results or more rows than the original data. In the example below, on July 1, 2021, the Amount spent in Table 1 is 1,749.17 but in the blended table, the Amount spent shows 50,725.93 — exactly 29 times the original value.


The reason for duplicated results is a misconfiguration in the blended data source. A dimension has been added to the second source, creating a one-to-many relationship in which one record in the table can be associated with many records in another table. In the example above, Table 2 has 29 campaigns on July 1, 2021, which will match and appear 29 times when referencing the date from Table 1, causing the duplicated results.



To avoid this behavior, consider using dimensions only in the join keys and removing any fields in the Dimensions section that can lead to the one to many, many to one, or many to many relationships. If you wish to keep the dimensions, create a calculated field with the formula MAX(X) so the field will return only one row per value. 



Calculated fields

Calculated fields let you create new metrics and dimensions derived from your data. There are two types of calculated fields in Data Studio: data source and chart-specific fields, both of which have different advantages and limitations. See the Data Studio help center to learn more about calculated fields.


Calculations using basic operations

In the calculated field, you can perform any arithmetic calculations: addition (+), subtraction (-), division (/), and multiplication (*). A green checkmark will be displayed to confirm your formula is valid.



Calculations using functions

In addition to basic operations, Data Studio provides a list of functions for calculated fields.

Please see the Data Studio help center for a full list of functions.


Case function

With the Case function you can define one or more conditions for returning data, for instance to create new categories or groupings of data. You can use the Case function to build a new field both on a chart and data source level.

Please see the Data Studio help center for more information on the Case function


In the example below, we want to show only two categories: Paid and Other. The Paid group will only contain the medium "cpc" while the Other group will contain all other mediums. 


The field can now be used to categorize data based on the defined conditions.


Troubleshooting calculated fields

If you run into error messages in your calculation, you may be applying illegal functions on the original fields. See the Data Studio help center for more troubleshooting help on calculated fields.


Other useful tips for using calculated fields

How to add images/creatives to your report from URL fields

Converting null values to zero

Filter results by a field containing punctuation marks



Filters

With filters, you can refine or reduce the data shown in your report based on defined conditions. You can apply filters to a specific chart, control, page, or the whole report. To get started with filters, please refer to our getting started guide and the Data Studio help center.


Please note that a filter is set per data source and can't be shared among multiple data sources. If you want to use the same filtering setting with another data source, you can duplicate it and adjust it to a new data source.


Filter controls in Data Studio

In addition to chart-specific filters that can only be set by report editors, with filter controls also viewers can change the filter conditions and narrow down the results. Please see the Data Studio help center for more information and a list of available filter controls.


For example, with a Drop-down list viewers can select which data to view from a list that is based on a dimension.


With an Advanced filter, viewers can select a search operator and input a specific value for filtering the data.



Known issues with filters

Getting "null" or "No Data" with unique metrics and filters

Discrepancies in Data Studio when using a filter


Data subsets for faster performance

Data Studio has a limitation of handling more than 6-minute queries as it requests data on demand. If you request for a lot of data, your Data Studio dashboard might 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.


To learn more, see our detailed blog post on the Extract Data connector and how to set it up.


Create a subset with only necessary fields

A normal data source will be created with a full list of supported dimensions and metrics, some of which you may not need at all. Using the Extract Data connector, you can handpick the dimensions and metrics that are meaningful for your reports.


Create a 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.



Other solutions with a large amount of data include our data-storage solutions: Supermetrics for Google Sheets, BigQuery, Snowflake, Amazon S3, Azure Synapse and Storage, and Google Cloud Storage. These tools will store all your data and allow you to analyze it whenever needed.


Tips and tricks for building charts

Decimal precision

When reporting on data in a number format, you may want to display fewer or more decimal places. You can adjust the decimal precision of a chart in the STYLE tab Metrics section.



Set the range by data

When working with a time series chart, the data from your selected date range may be squeezed in the middle of a chart that displays a longer time period. You can adjust the chart axis in the STYLE tab X-Axis section by selecting the Range by Data setting.


Comparison metrics and running calculations

In Data Studio, you can compare your data to total and running values. You can access the comparisons and running calculations as you edit a metric. See the Data Studio help center to learn more about adding comparison metrics and running totals.


For example, you can use the Running delta option to calculate the difference between the current row and the previous row for a view of increasing or decreasing values. 



Data Studio troubleshooting guides

  • Error: Authentication failed: See the guide here.
  • Community connector error: You are using the free version of Supermetrics for Data Studio: See the guide here.
  • How can I transfer license, report, and data source to a colleague: See the guide here.
  • Error: The owner of this component has revoked the data source. To resolve this, please contact the owner of the data source: See the guide here.
  • Error: This action is not supported when you are signed in to multiple accounts in the same domain or on multiple consumer accounts. Log out and try again: See the guide here.
  • Not all accounts are displaying in the drop-down list: See the guide here



Did you find it helpful? Yes No

Send feedback
Sorry we couldn't be helpful. Help us improve this article with your feedback.