Workhy offers a comprehensive platform designed to help entrepreneurs set up, manage, and grow their businesses online. By providing end-to-end solutions, Workhy simplifies company formation processes and financial management. Their services include company establishment, tax return preparation, online bookkeeping, and acquiring registered addresses.

Workhy collects, analyzes and utilizes a lot of customer data. Previously, they had a manual process, relying on their data engineer running scripts from their computer, uploading data to BigQuery, and building dashboards on Metabase.

Challenges Before Bruin

Before using Bruin, Workhy faced significant challenges in scaling data pipelines, ensuring data quality, and tracking data lineage. These issues slowed their development and deployment processes, hampering overall productivity.

Previous Workflow

Previously, Workhy used Metabase for visualization and developed dashboards in Python using Visual Studio Code. Data updates were periodically done by writing Python files to the cloud and sometimes manually uploading CSV files due to file type and size constraints. Since incremental data updates were not possible, the entire dataset had to be queried and re-uploaded each time. During this period, development continued on scripts for other tables, which were run manually.

Every time the business users had questions, Alperen, the data engineer in the team, had to build report calculations in Python, run them on his computer manually, and visualize the results on Metabase.

Choosing Bruin

Workhy chose Bruin for its seamless integration with Google Cloud Platform (GCP), robust data lineage tracking, and serverless architecture, which reduced operational overhead. Bruin's user-friendly CLI tools were ideal for their small team, and the platform's suitability for firms with lower data maturity levels made it essential for them. As part of the development experience, Bruin’s Visual Studio Code extension made getting started very easy for the team.

The first usecase the team wanted to utilize Bruin for was their ARR/MRR reporting dashboard. As part of this effort, Alperen first copied the raw data from their MySQL instances to BigQuery using Bruin’s ingestr integration, writing a few lines of configuration. After that, Alperen built the core data models around customers and transactions using SQL & Python, and deployed the full pipeline on Bruin Cloud after the local execution was successful. Since then, Bruin Cloud has been successfully executing all of their pipelines on a daily/hourly schedule automatically.

Impact with Bruin

Since implementing Bruin, Workhy has experienced faster development cycles and improved data quality. The expert support from the Bruin team has been invaluable, providing best-practice insights that have streamlined their operations. As a result, they've efficiently set up their BigQuery as their data warehouse, ingested data from their MySQL databases, created pipelines, and maintained comprehensive tracking, greatly enhancing their data analytics capabilities.

In addition to the technical impact, Workhy has also seen a significant improvement in developer productivity, as well as a strong upskilling of the team thanks to the close collaboration with Bruin team. Utilizing the weekly check-in conversations with the Bruin team, Workhy has been able to improve their data engineering practices and data quality significantly.

“Thanks to Bruin, we have been able to automate all the manual parts of our data pipelines. We are able to focus on our business users' needs while delivering insights faster than ever before.“

Currently, Workhy runs all of their pipelines on Bruin Cloud in an automated fashion, achieving 4x faster time-to-insight on their data questions.