Skip to content
Start a conversation
Two data scientists working through notebook plots on a laptop, equations on the whiteboard behind
Platform

Databricks

One platform where your engineers, analysts and data scientists work from the same data, instead of each keeping their own copy.

Book a discovery call

One version of the data is worth more than three convenient copies of it.

What we do with Databricks

Delta Lake

Makes changes to your data safe and reversible, and lets you look at exactly what a table contained on a past date. That last part is what makes audits answerable.

Unity Catalog

One place controlling who can see what, with a history of past permissions rather than only the current state.

Layered data structure

Raw, cleaned and business-ready data kept separate, with checks between each layer so a problem is caught where it enters.

Scheduling and alerting

Jobs run in the right order, and when something fails overnight a named person hears about it.

Model tracking

For machine learning work, a record of which data and which code produced the model currently making decisions.

Works with

MLflow

Building predictive models and actually getting them into production, with a record of what produced them.

Power BI, Tableau and Looker

Connected directly, so the reporting layer reads the same governed data as everything else.

What clients use it for

Predictive work

Forecasting and anomaly detection on top of the same platform your reporting runs on.

Where it fits

We are not a reseller and we take no vendor commissions, so there is nothing riding on which platform you choose. What we care about is whether the setup can be operated by your team after we leave.

  • Recommended where it genuinely solves a problem you have, not as a default
  • Implemented as code in your repository, under your accounts
  • Handed over with runbooks for the failure modes we actually hit
Two engineers working at a rack of servers

We build it so your team can run it

Everything sits in your accounts, in your repository, from day one. No lock-in and nothing that depends on us remembering how it works.

The rest of the stack we work in

Common questions

Do we actually need this?

If your reporting is SQL-based and your data is well structured, quite possibly not. It earns its extra complexity when you have unstructured data or machine learning sitting alongside reporting.

Can it replace our data warehouse?

Technically yes. Whether it should depends far more on your team's skills than on the technology.

Ready to turn complexity into your next advantage?

Tell us what you are running today and what is not working. That is a more useful starting point than a platform comparison.

Book a discovery call