We developed and deployed a scalable Lakehouse environment leveraging AWS Databricks. The solution was designed to support both Data Engineering and Data Science teams with streamlined, modular, and reusable workflows that can be adapted and employed across different client projects, maximising efficiency and scalability. Moreover, our modular design ensures component reusability, significantly reducing development time for onboarding new clients and increased adaptability to evolving business needs.
The Lakehouse we built leverages a medallion architecture and infrastructure-as-a-code approach with Terraform to optimise data management and processing. This multi-layered approach supports data quality and accessibility, as well as a variety of analytical applications by providing a scalable, ACID-compliant environment optimised for efficient data analytics and reporting. It also facilitates rapid deployment of new data models and analytics capabilities.
Finally, creating the foundation for more sophisticated data-driven decision-making processes based on advanced analytics and machine learning models, enabled Signol to elevate and scale their product offering in a robust and reliable manner.
