As a Cloud Engineer at DataCore Analytics, I was responsible for the deployment of our project’s backend on the Google Cloud Platform. One of our most challenging projects required us to handle a large influx of data from global users. We adopted Google BigQuery for its serverless, highly scalable, and cost-effective data warehouse solution.
There was a steep learning curve, but thanks to the GCP’s detailed documentation and my team's persistent efforts, we were able to configure BigQuery to manage our data effectively. We used Google Dataflow for real-time and batch data processing and Google Pub/Sub for event-driven computing and analytics.
Following this implementation, our application gained enhanced performance and scalability. We managed to achieve a significant reduction in processing times, further improving service delivery and enhancing client satisfaction.