What is DataOps?
Most businesses collect data but are unable to use it to generate business value or deliver insights in a timely fashion. Data volume and data types continue to grow, as do the different types of data citizens—ranging from business users to data scientists. As a result, data management and delivery often become critical bottlenecks. EnterDataOps.
DataOps (data operations) refers to practices that bring speed and agility to end-to-end data pipelines process, from collection to delivery. Theterm DataOpsand related concepts are at early stages of awareness and adoption, so many working definitions exist today. Research leaders, like Gartner and MIT, have focused their definitions around improving communication between data stakeholders and implementing automation within data flows and lifecycles to enhance delivery practices. Others are simply describing it as “DevOps for data.”
IBM defines DataOps as the orchestration of people, process, and technology to deliver trusted,high-quality datato data citizens fast. The practice is focused on enabling collaboration across an organization to drive agility, speed, and new data initiatives at scale.Using the power ofautomation,DataOps is designed to solve challenges associated with inefficiencies in accessing, preparing, integrating and making data available.
It is equally important to know what it is not.DataOps is not: a product; a single event or step; a specific team or person. As a rule of thumb, DataOps methodologyor practices you implement should consider interaction between these aspects:
DataOps supports highly productive teams with automation technology to deliver huge efficiency gains in project outputs and time. However, to experience the benefits, the internal culture needs to evolve to truly be data-driven. With more business segments requiring and wanting to manage data to drive contextual insights, the time is right to 1) increase the quality and speed of data flowing to the organization and 2) get commitment from leadership to support and sustain a data-driven vision across the business.
This type of transformational change begins by understanding the true goals of the business.
