What we do
What we review in your Databricks
- Jobs and pipelines that fail silently
- Cluster and job cost
- Unity Catalog access
- Inactive users
- Quality of the tables that feed reports and models
Data platforms
Databricks controller: jobs that fail silently, costly clusters and access nobody needs Your Databricks processes data, and the bill grows
We review your Databricks so the data feeding your models and reports is correct and your cluster cost makes sense.
Book a meeting29%
cloud spend wasted, the first increase in five years
Flexera, 202689%
data leaders with AI in production who have seen wrong outputs
Salesforce, 2025
The model
Every team creates jobs, notebooks and clusters, more and more with help from AI. They work the day they launch. Over time, some fail silently and others stay on with nobody needing them.
Jobs that fail and leave tables half written
Clusters running with no work
AI models trained on broken data
Unity Catalog permissions nobody reviews
Shall we talk about your case?
A 30-minute meeting to see what you have and what to review first.
Broken data flows into your models
What comes out of Databricks feeds reports and AI models. If the input is broken, so is the output, and the compute cost is paid all the same.
Cost
Clusters and jobs that cost more than they deliver.
Correct data
Silent failures caught before they reach a model.
Governance
Unity Catalog access and inactive users.
What you receive
What you receive
- The broken jobs and the tables they affect
- The clusters and jobs you can adjust
- The access and users nobody needs
- A one-page summary for leadership
Two ways to work with us
Review a new system once before it ships, or keep everything under control every three months.
Before production
Review a new system
Send the app, website or database you built with AI and get every gap with its fix before you deploy.
- One-time review
- Security, database and performance
- Fix plan before go-live
Every three months
Keep it all under control
We review your code, servers and data platforms each quarter: broken flows, idle users and costs.
- Quarterly review
- Broken data flows and unused licenses
- Before and after report each quarter
Frequently asked questions
Why review Databricks every three months?
Because every quarter new jobs and clusters appear, and silent failures and costs grow while nobody is looking.
Do you change anything in our workspace?
Not without your approval. We deliver the plan and apply the changes together with your team if you ask us to.
What savings can I expect?
It depends on your usage. We measure it in the first review with your own clusters and jobs, with no numbers promised in advance.
Book a meeting
Tell us what worries you. In the meeting we explain how we solve it.