Streamlined data analysis and software development processes, saving 4,000 hours by introducing GitHub, GitLab, Bash, and Python CI/CD practices.

Situation. Both the data‑analysis work and the software development were being held back by the same thing: manual processes. Work moved from development to delivery in a slow, inconsistent way, and the analysis side had its own pile of repetitive steps someone was doing by hand every time.

Task. The aim was to streamline both by bringing modern automation and CI/CD practices to workflows that hadn’t had them.

Action. CI/CD practices went in, built on GitHub and GitLab, with Bash and Python doing the automation work underneath. The repetitive steps across both the data‑analysis and the development workflows got automated, and how work moved from development through to delivery got standardised so it was the same every time rather than reinvented per project. Bringing the analysis side into the same disciplined pipeline as the dev work was a big part of it — it had been treated as a separate, more manual world.

Result. The streamlined processes saved roughly 4,000 hours and sped up both the data analysis and the software development, and just as usefully made what got shipped more consistent — fewer surprises from work that had been done a slightly different way each time.