Scalista is an Austrian online and mobile marketing agency that helps organizations grow in a very complex landscape. They have a proprietary project, Cloudista, for data harvesting.
They failed to connect Google BigQuery to Tableau to build reports.
The project had to be modified due to the updates of used Python libraries.
QA testing was required for the project’s flawless performance.
The problem of the failed connection between BigQuery and Tableau was detected and eliminated.
A new approach to building Tableau reports was developed.
Project maintenance for flawless performance was completed.
The Client’s users receive correct reports in a timely manner.
You need custom analytics if
1. We designed a new approach to data transfer from BigQuery to Tableau via Google Sheets.
Firstly, we conducted research to find out the root of the problem—why it was impossible to connect BigQuery to Tableau. The reason was that the system used a custom request with a lot of calculated fields to enable the connection. It failed to deliver due to a limited request length.
To solve the problem, we developed a new approach: with the help of a custom request, the data from BigQuery was regularly exported to Google Sheets. Then, Google Sheets was easily connected to Tableau, which allowed for building analytical reports.
Here is an example of a Google Sheet data mart:
2. The Cloudista performance was refined.
During the project, we discovered some ETL-related problems. Since the project is coded in Python, and the versions of the used libraries were updated, we needed to make the appropriate changes. After studying the code, project documentation, technologies, and the libraries’ changelogs, we edited the code for flawless performance.
What’s more, we compared the data from Facebook and Google Ads with the data sourced by the ETL project. Some modification of data processing was required.
If you need help with selecting or creating data analytics tools, feel free to contact us.
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