Data-driven transformation is a mandate for today’s CIOs and CDOs, and it’s likely to remain so for a long time. Modern data architectures, together with new services powered by AI and advanced data science and data analytics techniques, are making it possible to fully use analytics throughout the organization and drive data literacy.
Although new infrastructure – such as cloud data warehouses and lakes – and new technologies such as data streaming enable businesses to significantly increase data availability, that’s not the only piece of the puzzle. You still have to address the people component - and the processes to make data always available and analytics-ready.
Your processes have to change – to deliver greater agility, faster time to value, and real-time data for users in every area of your organization. Fortunately, DataOps is here to help.
Gartner defines DataOps as “a collaborative data management practice focused on improving the communication, integration, and automation of data flows between data management and consumers across an organization.” 1
It’s a methodology that encompasses the adoption of modern integration technologies, the processes that transform data from a raw to ready state, and the teams that work with data. The goal is to bring both sides of the data-delivery equation into alignment. The data manager’s requirements for control, transparency, and auditability. And the business user’s need for real-time, analytics-ready data – to ultimately extract the most value for the enterprise.
Data-driven transformation requires an agile approach across the entire data supply chain, from your infrastructure to your processes and people. DataOps helps you bring all those elements together, accelerating cycle times and improving performance with the potential to transform your organization in a number of ways:
This executive brief explains how DataOps can change processes to be more agile, valuable, and deliver real-time data for users in every part of an organization.
“Business executives at mainstream corporations are quickly grasping a central premise that executives of data-driven companies have well understood: The speed with which the enterprise can get value from its data matters – a lot. Accelerating that timeframe . . . should be a core focus of any Chief Data Officer.”
“DataOps will teach us how to build a nervous system of data that brings awareness and power to every part of our organizations”
“Data-driven transformation can help from a new revenue and business standpoint, but it doesn’t work unless you’ve got your internal workings streamlined as well.”