Software documentation for management, scheduling, and optimization of field operations

LookerStudio - Data source


Sign in to Google Looker Studio (Looker Studio): https://datastudio.google.com/

Cadulis Predefined Data Source

2-Click Creation from Cadulis Export

From the configuration page of your data export on Cadulis, you can directly click on Create a DataStudio/LookerStudio data source

This link will take you straight to the LookerStudio data source creation page, already filled in with your Cadulis download code.

Google Warning

The connector provided by Cadulis is currently under review. You may receive a warning message from Google.

If you used this method, you can skip directly to report creation

Manual Creation with the Code

Click on Cadulis activities data source

Enter your Cadulis code, obtained from the export configuration page.

To create a data source for tracking your Cadulis licenses: Cadulis licenses data source

Move on to report creation: your data source is now configured!

Data Source

Log in to your previously configured Cadulis data source: click on Create, then Data Source

Google Data Studio datasource


You now need to select the connector

Cadulis

Search for Cadulis and select the partner connector provided by “Cadulis SAS” Cadulis activities.

You can also use the link Cadulis activities data source

Enter your connection code (previously obtained from the export configuration on Cadulis) and confirm.

Remember to rename your data source so you can find it more easily!

Google Sheet

If you have set up the source as a Google Sheet, choose the Google Sheet connector

Select your Sheet file, as well as the sheet where you imported your data

At the top of the page, change the data source title: it will be easier to find later!

Click on Connect

Large Volume Ingestion

This method is not efficient for ingesting large volumes of data:

If you have more than a few thousand rows, you will probably need to use a faster or even sequenced ingestion method. Below is ingestion via bucket, but you could also use BigQuery or another big data engine ;)

Google Cloud Storage

If you have set up the .csv export to a Google bucket, choose Google Cloud Storage

Select your file from the bucket

At the top of the page, change the data source title: it will be easier to find later!

Click on Connect

Imported Fields

On this page, you can refine the data type for each field.

Google Data Studio datasource fields

On this page you can pre-calculate fields, such as a lat_lon field, required for map visualization

Don’t worry: you can always come back later to modify field types.

Your data source is configured!

You can always come back to modify it: refresh frequency, field types, etc.

Click on Create Report

Bonus: lat_lon Field Calculation

For the next step in this example, we want to display a map with the positions of interventions.

DataStudio requires a lat_lon type field, but Cadulis only exposes latitude and longitude separately.

  • Click on Add a field
  • Field name: enter lat_lon
  • In formula, write the following formula and save

CONCAT(location.latitude,",",location.longitude)
  • Finally, you need to change the field’s data type, select Geographic Data > Latitude,Longitude