Becoming data-driven is hard. Data teams are caught between the competing demands of data consumers, data providers, and supporting teams. The need to manage complex toolchains and data, as well as collaborate with other organizations, roles, locations, and data centers, saps the data team’s time. In fact, most data teams spend more time fixing errors and addressing operational issues than innovating and providing business value.
In data analytics, DataOps provides the path forward. DataOps draws on the principles of Agile, DevOps, and Lean manufacturing to transform data processes.
Because DataOps impacts your end-to-end analytics life cycle, implementing DataOps can feel overwhelming. A DataOps Maturity Model can be an incredibly useful tool to help organizations understand where they are today and how to get where they need to go.
Sponsored by DataKitchen
Individual, Student, and Team memberships available.