When should you consider using BigQuery with Looker Studio? It's a powerful and flexible tool, but knowing when to make the switch is important.
If you've started with a Google Sheets-based data pipeline as your minimum viable product (MVP), you've likely tested its value and potential. Google Sheets offers less friction, making it quicker and easier to set up. However, when your proof of concept is in place and you're ready to scale, it may be time to consider BigQuery.
You might reach the limits of Google Sheets in terms of volume or complexity. If your data modeling becomes too slow or intricate for Google Sheets, it's a sign that data modeling in BigQuery is a better choice.
Sometimes the nature of the data modeling itself requires more advanced tools. For example, attribution modeling, complicated joins for data enrichment, or forecasting with machine learning are tasks that can be difficult in Google Sheets but are easier with BigQuery.
If report loading speed and user experience are important factors for your clients, they may benefit from switching to BigQuery. Faster load times can improve overall satisfaction with your reports. To learn more about the speed process of BigQuery, visit our how fast is BigQuery lesson.
Lastly, if you want to own and retain data modeling while keeping visualization in Looker Studio, using BigQuery allows you to maintain control over your "secret sauce." This way, you keep ownership of the data modeling layer without exposing it through visualization tools.
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