Situation
A leading European construction and civil engineering company had ambitions to become more data driven and be able to scale the creation of data and AI products. But building the required data infrastructure and platform manually was not a viable option. The scale of the company’s ambition meant they needed a more better way to deploy and manage its data environment, whilst maintaining control of the data architecture.
Approach
Valcon helped the company move from a manual platform set-up to a reusable, code-based foundation for Azure Databricks. Together, we built the platform using infrastructure as code – Terraform was used to deploy an Azure Databricks Lakehouse, which created a modular foundation that could be reused, governed and updated. Databricks Asset Bundles were also applied as code, making it possible to deploy machine learning, AI and data products in a repeatable way.
This approach enabled much faster, more controlled delivery of new data and AI solutions for the company.
Results
- Reusable infrastructure that can be reused and gives the client greater control of its data platform.
- Faster delivery of AI, machine learning and data products.
- Reduced manual effort through repeatable deployment and lifecycle management, which accelerated the creation of new AI and data products on Azure Databricks.
- It gives the client stronger control over the platform that supports its data-driven ambition.
