Data Engineering

“Data scientists spend around 80% of their time on preparing and managing data” - Forbes

Good data engineering enables great data science. We help our clients get their data from source to store with a lean & clean approach to software engineering:

• We helped Kingston Smith to automate parts of their audit process, including data ingestion, accounting quality checks and ETL into a SQL Server database.

• We’ve built Franchise Partners’ data architecture from the ground up, automatically retrieving, validating and transforming a large number of “dirty datasets” with potentially market predictive properties for usage within both business intelligence and machine learning applications.

• City Pantry needed routing software for their delivery drivers that could handle London’s unpredictable traffic. By leveraging open source components (Google’s OR-Tools & Django REST Framework) we were quickly able to build an effective and scalable drop-in replacement for their existing driver scheduling and routing systems.