IDC defines DataOps as “a practice that enhances collaboration between data consumers and data creators — either of which can be humans or machines.”
Built on the theory of DevOps, DataOps goes much further, since it is more than just merging two engineering-related disciplines. Instead, “DataOps encompasses everyone from the beginning of the data supply chain where data originates (from IoT devices to enterprise applications to massive third-party repositories such as the Open Data Initiative) to all the people who model and blend data all the way to those who put it to use in applications and analytics,” according to The Cultural Impact of DataOps: Collaboration, Automation and the War on Silos, a Hitachi Vantara whitepaper.
Like so many new methodologies, successful DataOps adoption requires cultural change. Here are 3 key areas where IT can lead the charge.
Collaboration. Due to the number of departments and individuals involved in developing and adopting a DataOps strategy, collaboration is key. IT must put the tools in place to help this to happen. This includes implementing self-service tools as well as communication solutions that enable business executives to reach out to data stakeholders, data quality experts, and data scientists for help. In doing so, IT fosters collaboration while also reducing management time and costs.
Normalize group ‘ownership’ of data. Any successful DataOps strategy and culture must incorporate the use of metadata. With metadata, users get more out of their data with less upfront work — it eliminates the need to sort through endless spreadsheets for similar or complementary data. In addition, data from one part of an organization can be easily shared and leveraged with another since there’s no disparity on tagging or naming conventions. In addition, it is essential to let everyone who touches data — the end user, the IT person and the data scientist — to have a piece of ownership. Instead of one person owning data, it belongs to everyone. When teams adopt this approach it removes barriers to data sharing, in turn boosting innovation.
Data democracy. Companies must be willing to utilize push-down decision making. At its most basic definition, this concept means that, as data use becomes more widespread, users are given permission and tools to make their own data-based decisions versus deferring to those previously charged with managing data. This step in particular requires significant cultural change. While it might be a hard sell for some, it’s a step worth taking, even if organizations need to extensively communicate and educate users before it takes hold. When everyone is involved in decision-making, new ideas and solutions can bubble up to the surface, and there’s less time wasted on getting approvals. This is where innovation lives—and the benefits of innovation include new revenue streams, staying relevant, and freeing up resources to impact the bottom line.
Simply put, the risk-reward ratio for making these changes is significant. When companies embrace new processes around DataOps, they become more unified — and innovation soars.
Want to learn more about how your organization can evolve and build a new culture that supports and enhances DataOps? Click here to learn more.