DataOps 2025

By 2025, a Data Engineering team guided by DataOps practices and tools will be 10 times more productive than teams that do not use DataOps !

Gartner’s Strategic Planning Assumption

By 2025, one-half of organizations will have adopted a DataOps approach to their data engineering processes, enabling them to be more flexible and agile.

Ventana Research


DataOps is an engineering methodology and set of practices for rapid, reliable, and repeatable delivery of production-ready data and operations-ready analytics and data science models (source

Wayne Eckerson, Eckerson Group

Operationalizing Data Integration for constant change and continuous delivery1

DataOps is a collaborative data management practice focused on improving the communication, integration and automation of data flows between data managers and data consumers across an organization.


DataOps is the new way of thinking about working with data, it provides practitioners like architects & developers an ability to onboard and scale data projects quickly while giving operators and leaders visibility and confidence that the underlying engines are working well. It is a fundamental mindshift that requires changes in people, processes, and supporting technologies2.

Data Operations (DataOps) is a methodology focused on the delivery of agile business intelligence (BI) and data science through the automation and orchestration of data integration and processing pipelines, incorporating improved data reliability and integrity via data monitoring and observability. DataOps has been part of the lexicon of the data market for almost a decade and takes inspiration from DevOps, which describes a set of tools, practices and philosophy used to support the continuous delivery of software applications in the face of constant changes.

Matt Aslet, Ventana Research

Gartner Key Findings

DataOps is becoming a necessity. Care capabilities include:

  • Orchestration
  • Observability
  • Test Automation
  • Deployment Automation
  • Environment Management

Gartner Recommendations

  • Procure as a cost optimization solution
  • Understand the diverse market landscape and focus on a desired set of core capabilities
  • Prioritize single pane of glass tools


  1. Source StreamSets ↩︎
  2. Source StreamSets ↩︎