Data Studio
The Redivis DataStudio connector allows for researchers to any connect any data source that they have access to with Google Data Studio. DataStudio provides comprehensive tooling for creating interactive visualizations and dashboards.
The Redivis DataStudio connector is currently in Beta. Note that DataStudio will mark the connector as "unverified" while it is in Beta, and please contact us if you have any issues.
To create a new data source, first click this link to navigate to the Redivis Connector.
You will then be prompted to authorize your Google Account for the Redivis connector.
Next, you must provide a Redivis API access token to authenticate your account. You can create a new access token on your workspace settings page. This token must have the data.data scope enabled. Learn more about API access tokens here.
Finally, specify the table that you want to import. If the table belongs to a project, you will need to specify the name of the project and the username of the project owner. If the table belongs to a dataset, you will need to specify the name of the dataset as well as the username of the dataset owner.
Advanced users: you may also specify a custom query to reference multiple tables at once. Note that this query follows the same syntax and naming conventions as the specified in the Redivis API.
You may share your DataStudio reports with whomever you wish. However, each report viewer (or editor) will need to authenticate with their Redivis credentials, and they must have data access to the underlying Redivis table(s) in order to interact with data in the report.
If you share a report with someone and they don't have access to the underlying data, they will see a data source configuration error. They may need to request access to the dataset(s) on Redivis, or may need to update their access credentials in DataStudio.
Finally, some dataset owners assign export restrictions to their datasets. Certain tables may be bound by these export restrictions and cannot be imported into DataStudio (for example, if the data can only be exported to a specific compute environment, or if there are export size limits that the table exceeds). In this case, you can return to Redivis and request an export exception for the table (export exceptions for the DataStudio export location are coming soon).
DataStudio does have an initial learning curve, but after a short investment you will find that you're able to produce powerful, elegant interactive visualizations in minutes.
Some researchers may want to dive right in, though we recommend taking a look at the DataStudio help documentation for some helpful resource in getting started.
