DataKitchen DataOps Consulting Services
The benefits of DataOps, delivering faster with fewer errors, are desirable. But getting started can be hard. DataKitchen's DataOps Consulting Services provide concrete, actionable steps for success.
Key points
- Two ways to work with us: we advise your team, or we build and run the thing ourselves and hand it over.
- Everything runs on open-source DataOps TestGen and DataOps Observability, Apache 2.0, in your own cloud. There is no procurement cycle before you can start.
- You keep the code. Engagements end in a documented handover rather than a dependency, which means they have to end well to end at all.
- The people who scope the work deliver it. No separate delivery team introduced after you sign.
- If you do not know where you stand yet, an assessment is the cheapest way to find out: three and a half days, ending in a prioritised plan.
Meet the DataOps Experts
The people who scope the work deliver it, with decades of experience in data analytics, software engineering, and DataOps transformation.
Ready to get started?
Talk to our team about how DataKitchen services can accelerate your DataOps transformation.
Frequently Asked Questions
Common questions about working with DataKitchen
What services does DataKitchen offer?
Eight, in three groups. DataOps services are advisory: consulting and coaching, a DataOps assessment, and training. Data engineering is delivery: commercial pharma analytics, AI data engineering, and AI enablement. Data quality covers a managed service that runs quality across your estate, and a data quality assessment that writes rules against your tables and hands back a plan.
Do you advise, or do you build?
Both, and they are separate offers. Consulting, assessments, and training put your team in a better position to do the work. AI data engineering, commercial pharma analytics, and data quality as a service mean our engineers build and run it inside your team, then transfer it. Teams that need the platform running before they can hire for it usually start with the second kind.
Do we have to buy software first?
No. DataOps TestGen and DataOps Observability are Apache 2.0 and install in your environment, so nothing waits on procurement. That also means the tests, baselines, and dashboards an engagement produces stay with you when it ends.
Which service should we start with?
If you already know what is broken, start with the service aimed at it. If you do not, start with an assessment: the DataOps assessment if the problem is how your team builds and runs, the data quality assessment if the problem is the data itself. Both are three and a half days and end in a prioritised plan rather than a description of your current state.
Who actually does the work?
Named engineers who have run production data platforms rather than only advised on them, listed on each service page. Chip Bloche, Eric Estabrooks, Gil Benghiat, Aarthy Adityan and Chris Bergh lead the engagements. You get the people who scoped the work, not a delivery team introduced afterwards.
What happens when an engagement ends?
Your team owns the platform and keeps running it. The code was in your repository throughout, the software underneath is open source, and the handover is a scheduled transition with the architecture, tests, and runbooks written down. Some teams bring us back for the next phase; the plan is yours either way.