DataOps—a combination of tools and methods that applies Agile development, DevOps, and lean manufacturing practices to data science—is aimed at enabling data organizations to accelerate the development of new analytics, deploy with confidence, and reduce data errors.
The DataOps methodology is gaining traction, said Chris Bergh, CEO and head chef at DataKitchen, who noted it has arisen out of a recognition that data and analytics projects and initiatives are not working, both in terms of meeting business requirements and in terms of timeliness.
According to Bergh, it is not that organizations don't have the right tools, data, or people with the right skills. They have all of that, but, he said, there is a people-and-process challenge, and for that reason, the operational side is the focus now to enable faster cycle times with higher quality.
The DataOps Cookbook, available as a free download, is aimed at helping to describe the challenge and help people focus on this area as a problem that can be solved, said Bergh.
In particular, as people are getting deeper into understanding the issues involved, the second version of the book has added more information on collaboration and self-serve analytics, and how teams—which may be distributed across geographies with different leadership—can work together, said Bergh. There is also a new emphasis in the book on the idea of a data architecture that is focused on DataOps.
In addition to its exploration of data-analytics development and operations, the DataOps Cookbook is an actual cookbook with recipes that are sure to add cheer to your holiday feasts – try the Chile Mole.