DataOps becomes more broadly adopted, it is clear that the practice must be tailored to the unique needs of an organization. At Hitachi Vantara we believe DataOps must evolve to address issues such as data governance, security and access control in an automated, scalable fashion. The early adopters of DataOps have not solved these issues because while they operate with huge data volumes at high speeds, the organizations are much simpler and smaller. In addition, the underlying infrastructure supporting DataOps must be built to evolve to achieve operational agility. Again, at the early adopters, agility is achieved through a strong DataOps culture and by throwing huge engineering teams to build custom systems to achieve needed levels of automation in both applications and infrastructure. See our companion papers for a detailed discussion of how DataOps will work for the enterprise.

But part of the evolution will be cultural and that’s what we want to talk about in this paper. We see the following cultural dimensions as crucial to successful adoption of DataOps:

  • Collaboration
  • Automation and a metadata mindset
  • Data as a shared asset
  • End-to-end design thinking
  • Enlightened and guided empowerment
  • Silo paranoia
  • Push down decision-making

Many of these areas overlap and support each other. The end result for DataOps, as it was for DevOps, will be an organization that is more unified and works together at a much faster clock speed. To read more, please download this whitepaper…

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