What Does DataOps Mean?

The DataOps approach seeks to apply the principles of agile software development and DevOps (combining development and operations) to data analytics, to break down silos and promote efficient, streamlined data handling across many segments. DataOps is served by tools, technologies and techniques that combine multiple stages of a staged process to improve and enhance the management of data for enterprise use.


Techopedia Explains DataOps

Many different types of frameworks can facilitate a DataOps approach. The use of Apache Oozie to handle Apache Hadoop projects could be called DataOps, so could the use of ETL processes in a streamlined data flow. In general, DataOps replaces a “waterfall” or sequential strategy for analytics with one that involves “hand-holding” across teams and departments: For example, a universal agreement on semantics of data and metadata is a step on the road to applied DataOps. This idea was really only implemented in 2015 and later, and some experts see 2017 as ushering in more of a focus on DataOps for enterprise IT and data analytics.


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Margaret Rouse

Margaret Rouse is an award-winning technical writer and teacher known for her ability to explain complex technical subjects to a non-technical, business audience. Over the past twenty years her explanations have appeared on TechTarget websites and she's been cited as an authority in articles by the New York Times, Time Magazine, USA Today, ZDNet, PC Magazine and Discovery Magazine.Margaret's idea of a fun day is helping IT and business professionals learn to speak each other’s highly specialized languages. If you have a suggestion for a new definition or how to improve a technical explanation, please email Margaret or contact her…