Data Engineering and Analytics

We choose based on your scale and team, common warehouses paired with a BI tool your people can use, and set them up in your accounts so the data stays yours.

Typically yes. We build pipelines from your databases, SaaS tools, and files into one warehouse, with quality checks so what lands is trustworthy.

All three, if you want. The pipelines pull your sources together, the modelled warehouse defines each metric once, and the dashboards read from that single layer, so the value is visible to the people who need it and every number traces back to a definition.

We build data quality checks into the pipelines, monitor them, and document how each metric is defined and where it comes from. When a figure looks off, there is a traceable answer rather than a shrug, which is what lets people trust the dashboard enough to act on it.

Yes. Source, infrastructure configuration and documentation are pushed to your repositories from day one, and the cloud accounts stay in your name. If we part ways, you keep everything and nothing stops working.

On scope. A one-to-two-week discovery produces an itemised estimate for a defined first release, so you see the full cost before committing to the build.

A focused v1 usually takes three to six months, shipped in two-week increments you can test as they land. A clickable prototype typically exists within fourteen days of the brief.

Yes. Our team works on GMT+6, with at least six hours of daily overlap with the Gulf, Europe, the UK, the US and Australia, and demos are recorded for anyone who missed the call.

We keep watching the metrics, respond to incidents and ship small improvements under a maintenance agreement, for as long as you want us. Runbooks and monitoring are in place from day one, so nothing depends on memory.