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Colibri worked with Shell, one of the world's largest oil and gas companies, to deliver an Azure advanced analytics stack for its global lubricants business. Shell was struggling to design a solution capable of processing vast quantities of dirty data from various sources.
Shell, one of the world's largest oil and gas companies, had spent the last six months trying to deliver an Azure analytics stack for its global retail lubricants business. Struggling with the volume, veracity, and variety of data, as well as a lack of experience in delivering Azure data projects, the initiative was heading towards failure. Major issues included the time taken to manually deploy and execute the main data pipeline, an unstable data science environment, and a lack of automation and control around code changes.
Colibri were approached to redesign and re-implement the analytics platform from scratch, using a DevOps-first, cloud-first methodology to enable rapid evolution and prototyping of new use cases and ingestion of new data.
We rapidly embedded ourselves into the existing Data Engineering, Data Science, and DevOps teams, instilling a culture of automation and cloud-first thinking. This allowed us to quickly distil and simplify the architecture of the target data platform.
By working with existing business and engineering teams, we were able to develop a refined, prioritised backlog of development tasks, supported by a best-practice cloud and data architecture focused on solving only the core business requirements - something the project had previously failed to do.
We also sponsored the adoption of industry best-practice technologies, including Azure Storage, AKS, ACR, Spark, Kubernetes, and CircleCI, enabling engineering teams to significantly improve productivity while dramatically simplifying the platform’s architecture.
In just 10 weeks, we were able to reduce the time taken to deploy a new version of the data engineering or data science pipeline from weeks to minutes. Pipeline execution performance increased by more than 15x on a significantly larger data set.
We also delivered a state-of-the-art analytics infrastructure, supported by fully automated deployments, providing environments for data scientists to rapidly explore new use cases, and for data engineers to test the creation of new features in a scalable, repeatable fashion.
Reduced to within 6-second lead time
Faster predictions on customers' needs and capturing new opportunities
+ 20 headcount in the data team
Unlock growth, efficiency and innovation through data and AI
Turning raw data into actionable, competitive insight
Modernise with purpose. Transform with data. Scale with AI
Intelligent solutions built for real-world business impact
Empowering cloud-first operations with confidence
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