How DataOps Transforms Data Supply Chain Roles

BrandPost By Karen J. Bannan
Aug 17, 2020
Data Center ManagementIT Leadership

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Credit: istock

The data supply chain encompasses a wide range of resources and personnel. Data is created, integrated, stored, and analyzed via analytics and other applications and services across the enterprise. Data is touched and tapped by end users, data experts, and IT staffers who deal with cloud and data management.

Today, these three groups – end users, data experts, and IT staffers– frequently encounter data bottlenecks across the data supply chain. It’s not uncommon for everyone involved to waste time searching for the right data and to worry about its integrity, quality, and access once they find it.

But there’s a new paradigm emerging that will change the way end users, data experts, and IT professionals think about and interact with data. It will also change each of these roles on many levels.

Dubbed DataOps, the new methodology is enterprise data management in the age of artificial intelligence (AI). Part technical and part cultural, DataOps impacts every role in the data supply chain – often with significant benefits for everyone involved.

Big Changes Ahead

Most organizations have data in silos. Using DataOps, however, silos are broken down and the associated complexity is reduced. This means that data experts such as data scientists, data engineers, and data architects will need to collaborate and communicate more with each other. They will also need to communicate more frequently with other data constituents, says Lothar Schubert, head of Lumada product marketing for Hitachi Vantara. This in turn changes the associated job descriptions and day-to-day functions. “The roles will continue to exist, but stakeholders will collaborate more frequently and much more closely,” he says.

In addition, both data experts and IT staffers will need to collaborate with each other and cede some control as well, Schubert says. When DataOps is implemented, everyone gets to work together, but the roles they have are transformed. This includes changes such as:

  • Data ownership. As silos are broken down, the idea of one person, department, or function owning data disappears. This idea may be difficult to accept, but it must happen to enable broad use of data.
  • An evolution of skills. Data engineering, data quality, data profiling, data science and skills, and processes for data management will all still be necessary, but they will be applicable on a wider range of data that lives outside of silos. This will require data experts and IT to apply their skills differently and learn new skills, too.
  • New responsibilities. As a recent Hitachi Vantara white paper points out, “DataOps will not eliminate the roles people currently have in the data ecosystem, but it will change how they’re operating.” Self-service will flourish, making it possible for data consumers to augment and enrich data when they need it, on their own. Meanwhile, data experts and IT staffers, who take on the added role of data stewards, will focus more on data quality and metadata. IT staffers will also be responsible for an accelerated cycle of platform evolution and data supply chain deployment.

To learn more about how DataOps will transform your organization and what you need to know to get started, read Hitachi Vantara’s recent whitepaper, How DataOps Transforms the Data Supply Chain. Visit our site to learn how to put your data to work and connect what’s now to what’s next.