Gartner: 3 Ways to Deliver Customer Value Faster with DataOps

A summary and recommendations for further reading

by | Oct 5, 2020 | Blog, DataOps Principles

Slow deployment is a challenge for many data organizations.  In fact, many organizations experience lengthy cycle times for creating analytic environments or deploying new analytics that run weeks and months.

In their recent report, 3 Ways to Deliver Customer Value Faster with DataOps, Gartner points out that DataOps is a solution to data deployment bottlenecks, yet confusion over what DataOps is and how DataOps can help hampers implementation at many organizations. DataOps involves a focus on your underlying data process and, like us, Gartner urges practitioners to avoid a technology-centric view of DataOps for success.

Gartner recommends three approaches to DataOps based on how an organization consumes data. We share additional resources supporting these approaches below.

Utility Value Proposition

In this case, data is a utility that is used regularly.  The ecosystem “focuses on removing the roadblocks to data access and management, providing access to a range of data sources quickly.”

For implementation, the focus should be on “continuous integration and deployment of new data sources and operational excellence in the form of automation. Data quality, SLA compliance and pipeline resiliency should all be automated as much as possible, which means going as far as to include automated testing in the deployment cycle.”  

Enabler Value Proposition

According to Gartner, the enabler value proposition works best for teams supporting specific business use cases. “DataOps must focus on early and frequent collaboration with the business unit stakeholders who are the customers for a specific product serving their use case.”

Metrics are also essential.  In addition to key business metrics, other metrics, “might be a form of data availability service index, or data on how quickly newly created data is made available for consumption by your aggregate metrics. A data quality index is another popular metric used in data pipelines.” 

Driver Value Proposition

“The driver value proposition is about using data and analytics to innovate — to create new products and services, generate new revenue streams or enter new markets.”  Gartner explains that this is the proposition that causes intractable challenges relating to data governance and the promotion of new discoveries into production.”

For more information,  read the complete Gartner report here.

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