Case Study

Water Supply Company – Google ML

Written by Mike D'Arcy
Senior Project Manager

Year implemented: 2023


The customer is a major supplier of drinking water to million of consumers across England, with over 1,000 employees working across its network in water treatment and customer service, as well as maintaining over 9,000 miles of pipe.


We collaborated with them on a data strategy involving decommissioning legacy databases & building a GCP data lake. This allowed the customer to make data publicly available in line with regulations and follow their data modernisation strategy.


The customer’s AWS data lake was a copy of their old data, but it was managed by a  tool that was unreliable and only used for one task. This made it difficult for them to share its data with others and be a leader in the industry, but they needed a new data strategy that used a better tool to repeatedly put their data into a new system that could be used for more things.


We helped the customer build a new data system that can store and analyse data in real-time. This system uses Google Cloud Datastream to move data directly from various data sources to Google BigQuery, without the need for extra steps or tools. It also keeps the data up-to-date by streaming changes to BigQuery as they happen to make better decisions faster.


This solution helped the customer to analyse its data in near real-time and build predictive insights using BigQuery Machine Learning (BQML). The scalable and secure data warehouse makes it easy for them to share curated datasets publicly and seamlessly, in line with industry regulations.

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