As the IT world thrust forward in the dive to uncover the value of its valuable data by investing in new technologies, DataOps hand in the opportunity to improvise the data operations and analytics in a variety of ways.

DataOps or data operations combines DevOps, Agile development, and lean manufacturing to create business value from Big Data with a focus to improve communication, integration, and automation of data workflows within cross-functional teams. This set of practices, processes, and technologies involves cleaning raw data, converting the raw data into refined data, and transforming them into actionable business insights. DataOps uses Statistical Process Control - A lean manufacturing method to monitor and control the data analytics pipeline and helps with real-time data to drive business decisions.

With Data Scientists, Data Engineers, and Data professionals as the key players, DataOps can benefit organizations with real-time data analytics, identify valuable data, improve data quality and improve team collaboration.

Addressing the pain points of speed, output, quality, governance, and reliability in the complex data landscape, can the lack of trust in data help the data teams to generate actionable business insights?

- MADHAVI DESAI