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Our 4 key takeaways from the 2022 Gartner® Market Guide for DataOps Tools

Unravel is recognized as a Representative Vendor in the DataOps Market in the 2022 Gartner Market Guide for DataOps Tools. Data teams are struggling to keep pace with the increased volume, velocity, variety—and complexity—of their data applications/pipelines. […]

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Unravel is recognized as a Representative Vendor in the DataOps Market in the 2022 Gartner Market Guide for DataOps Tools.

Data teams are struggling to keep pace with the increased volume, velocity, variety—and complexity—of their data applications/pipelines. They are facing many of the same (generic) challenges that software teams did 10+ years ago. Just as DevOps helped streamline web application development and make software teams more productive, DataOps aims to do the same thing for data applications.

According to a Gartner strategic planning assumption from this Market Guide, “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.”

The report states that “the DataOps market is highly fragmented.” This Gartner Market Guide analyzes the DataOps market and explains the various capabilities of DataOps tools, paints a picture of the DataOps tool landscape, and offers recommendations.

Our understanding on DataOps and some of the key points we took away from the Gartner Market Guide:

The way data teams are doing things today isn’t working.

One of the key findings in the Gartner report analysis reveals that “a DataOps tool is a necessity to reduce the use of custom solutions and manual efforts around data pipeline operations. Buyers seek DataOps tools to streamline their data operations.” In our opinion, manual effort/custom solutions require prohibitively vast amounts of time and expertise—both of which are already in short supply within enterprise data teams. 

No single DataOps tool does everything.

DataOps covers a lot of ground. Gartner defines the core capabilities of DataOps tools as orchestration (including connectivity, workflow automation, data lineage, scheduling, logging, troubleshooting and alerting), observability (monitoring live/historic workflows, insights into workflow performance and cost metrics, impact analysis), environment management (infrastructure as code, resource provisioning, environment repository templates, credentials management), deployment automation, and test automation. We think it’s clear that no one tool does it all. The report recommends, “Follow the decision guidelines and avoid multibuy circumstances by understanding the diverse market landscape and focusing on a desired set of core capabilities.”

DataOps tools break down silos.

A consequence of modern data stack complexity is that disparate pockets of experts all run their own particular tools of choice in silos. Communication and collaboration break down, and you wind up with an operational Tower of Babel that leads to missed SLAs, friction and finger-pointing, and everybody spending way too much time firefighting. DataOps tools are designed specifically to avoid this unsustainable situation.

Choose DataOps tools that give a single pane of glass view.

The Gartner report recommends to “prioritize DataOps tools that give you a ‘single pane of glass’ for diverse data workloads across heterogeneous technologies with orchestration, lineage, and automation capabilities.” The modern data stack is a complex collection of different systems, platforms, technologies, and environment. Most enterprises use a combination of them all. You need a DataOps tool that works with all kinds of workloads in this heterogenous stack for different capabilities and different reasons—which can be boiled down to the three dimensions of performance, cost, and quality.

We are excited that Gartner recognized Unravel as a Representative Vendor in the DataOps market, and we couldn’t agree more with their Market Guide for DataOps Tools recommendations.

 

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