Written by Tamr
“Within the next year, the number of data and analytics experts in business units will grow at three times the rate of experts in IT departments, which will force companies to rethink their organizational models and skill sets.” – Gartner, Introducing DataOps Into Your Data Management Discipline, 31 October 2019, Ted Friedman, Nick Heudecker
This influx of data-minded people in an organization, coupled with intense pressure to make data perform, is negatively impacting the pace at which data and analytic leaders can achieve progress and enact meaningful data transformations. Traditional strategies and frameworks that they are using are straining under the pressure brought on by modern data’s volume, velocity, and variety. As a result, projects fail and timelines for completion are continually extended.
In order to achieve the speed and reliability of project delivery that they desire, data leaders are searching for new methods to maximize their chances of success and allow them to realize the potential that remains untapped in their organization’s data.
Tamr has written extensively on the topic. From defining what is DataOps, to identifying the key principles of a DataOps ecosystem, we’ve been thinking about and practicing DataOps strategies from the beginning. But now it’s not just Tamr. Interest in DataOps is exploding. For example, Gartner notes that end-user client inquiry data shows a 200% YoY increase in 2019 DataOps related questions.
We feel a good place to start in order to help improve chances of success, and introducing DataOps techniques in a focused manner, Gartner wrote, Introducing DataOps Into Your Data Management Discipline.
Because of its value, we’re offering the entire report as a complimentary download. We believe you will learn strategies Gartner recommends to make DataOps adoption a success, including:
- How to introduce DataOps strategies and techniques
- Enable greater reliability, adaptability and speed in data and analytics work
- Increase data effectiveness by enabling collaboration across key roles
- Revive data projects that failed due to lack of collaboration
Get your complimentary copy. If you have further questions about how to successfully implement a successful DataOps infrastructure, or how Tamr fits into a DataOps ecosystem, please book time to talk with us.