Coupler.io Blog

How to connect TimeTonic to Google Sheets, Excel, or BigQuery

export data from TimeTonic

From creating smart tables to streamlining team collaboration and building CRMs – without a doubt, TimeTonic offers its users impressive functionality. This popular management and collaboration solution allows companies to efficiently organize their data, automate repetitive tasks, and simplify processes. However, for some purposes, you might need to export your data from TimeTonic and work with it in another place. In this article, we’ll explain how to connect TimeTonic to Excel, Google Sheets, or BigQuery and extract your data automatically on a schedule.

How to connect TimeTonic to Google Sheets with Coupler.io

In our example, we’ll show you how to connect TimeTonic to Google Sheets with the help of Coupler.io – a reliable data analytics and automation platform. In particular, Coupler.io offers a data integration solution that allows you to export data automatically from more than 30 apps to Google Sheets, Excel, and BigQuery. The list of available data sources includes TimeTonic. The tool has the automatic data refresh functionality, so you can set a custom schedule for the updates, and Coupler.io will keep your TimeTonic data in a spreadsheet or database always synchronized.

Here’s how to connect TimeTonic to Google Sheets with the help of Coupler.io’s Google Sheets connector.

How to connect TimeTonic to Excel

If you need to connect TimeTonic to Excel, you can follow the same steps that we’ve described in the previous section when explaining how to export TimeTonic to Google Sheets. The flow is very similar. The only difference is that you need to select Excel as your destination when setting up the importer.

Then, connect your TimeTonic account and select the workspace, table and view to export data from – in the same way we’ve already described for Google Sheets.

Then, connect your Microsoft account and select a workbook to import data to.

After this, choose the import mode, set up the schedule for the updates, and run the importer. For more details, please check the previous section.

How to connect TimeTonic to BigQuery

To export TimeTonic to BigQuery, you can complete the same steps we’ve described in the How to connect TimeTonic to Google Sheets section.

You’ll just need to select BigQuery as a destination and provide some necessary settings.

You’ll also need to connect your BigQuery account. To do so, it’s necessary to provide your project ID and .json key. See the instructions on how to get the key

Then, specify the dataset and the table where you want to transfer your data. Turn on the Autodetect table schema function, and Coupler.io will structure your data automatically while importing.

After this, select the import mode and set up the schedule for automatic updates. Once everything is ready, run the importer.

Now you know how to connect TimeTonic to BigQuery automatically.

Why connect TimeTonic to a spreadsheet or database?

Importing your TimeTonic data to other apps can be very useful for certain purposes and cases. Let’s take a look at some of the benefits of connecting TimeTonic to Excel, Google Sheets, or BigQuery:

Which app to use to analyze data from TimeTonic?

In this article, we’ve explained how you can export data from TimeTonic to Google Sheets, Excel, and BigQuery. Each of these apps can help you analyze your TimeTonic data in-depth. In Excel, you can conduct advanced calculations and build self-updating dashboards using the app’s native functionality and transferring fresh data with Coupler.io. In Google Sheets, you can work with your data in a spreadsheet and easily share it with stakeholders for collaboration or presentation. Another option is to connect Google Sheets to Looker Studio and build professional visualizations for advanced analysis. If you transfer your data to BigQuery, you can analyze it using the app’s in-built machine learning algorithms. This can help you better understand your processes and make valuable forecasts for the future.

Exit mobile version