Gartner: “Select a DataOps Platform for 2020”

by | Mar 3, 2020 | Blog, DataOps Principles

In Gartner’s recent write up for technical professionals, “2020 Planning Guide for Data Management“, they highlight 10 critical trends for 2020. The most exciting one for us at DataKitchen is #10, DataOps.  


We are most excited that Gartner is advocating the need for a DataOps Platform: “Select a DataOps platform to integrate functions that support rapid deployment and governance.” As a provider of a DataOps platform, we are biased, but could not agree more!

For the first time, Gartner describes the architectural components of a DataOps Platform. You can learn more by following this LinkedIn post and reading the the 2020 Planning Guide for Data Management.

The document expresses ideas similar to what we have written in about in our blog and white papers. I wanted to highlight a few key points and use them as jumping-off points to our writings and features that we have built-in our product.

  • “…, test, monitor, … and alert for failure … Detect data drift automatically”:  
  •   “Capture metrics and reports at the right granularity”:
  • “Provide Version Control”: 
    • Please read about our view of this here.
    • Our product supports version control natively
  • “Manage .. metadata … and activity logs”:  
    • Keeping data about data is central to moving fast
    • We built that in our product as Orders.
  • “Automate deployment of the code, frameworks, libraries and tools”
  • “Create and maintain the environment … “
    • We think environments that teams work in are central ideas for collaboration and coordination.
    • A considerable part of our product is Kitchens. We are DataKitchen, remember?
  • “DataOps can span the entire gamut from data ingestion all the way to data delivery. This is a complex chain of components.”   

We do feel very proud that one of our articles on DataOps Architecture has had some influence on Gartner. Check out the similarities below (one small nit:  Gartner mixed up the order of Dev and QA environments).


Finally, we do have a bone to pick with the authors at Gartner. They said:  “And because this is a nascent process, there are no end-to-end tools or products that provide an all-encompassing solution for DataOps.” 

WE DISAGREE .   We have built an end-to-end product for DataOps here at DataKitchen! 

Sign-Up for our Newsletter

Get the latest straight into your inbox

By DataOps Phase

Go from zero to DataOps in four incremental phases
Lean DataOps Overview Production DataOps Development DataOps Measurement DataOps Enterprise DataOps

By Buzzword

DataOps is the foundation for these common use cases

Data Observability
Data Mesh
Self-Service Operations

By Platform

DataOps brings agility to any environment

Hybrid Cloud DataOps
Cloud DataOps

By Team

DataOps makes any team more productive

Business Analytics
Central Data/IT
Data Science/AI

DataOps FAQ

All the basics on DataOps

DataOps 101 Training

Get certified in DataOps

Customer Stories

See how customers are using our DataOps Platform

Upcoming Events

Join us to discuss DataOps

Maturity Model Assessment

Assess how your organization is doing with DataOps
Share This