What is DataOps?
DataOps, short for data operations, is the process of building high-quality, trusted data solutions in an agile fashion to reduce the time between identifying the need for data and delivering it.
DataOps can help enterprises reduce the time it takes to find the data needed and make it available.
Many organizations are unaware of the data they already have and how useful it can be – where it lies, its quality, how it’s governed, and its trustworthiness. However, making this data useful can be complicated, time consuming, and labor intensive.
A strong DataOps strategy can reduce turnaround times from identification to providing trustworthy data through automation, improved communication, and Agile iteration.
However, there are a few key challenges to DataOps that include the need for cross-organizational teams with widely varying skills, dynamically changing data requirements, and a need for constant monitoring of proper data usage by the business. Most importantly, DataOps must be paired with strong data governance, data management, and observability practices.
A well-defined DataOps strategy clearly identifies the objectives, the organizational structure and skills needed, the data governance mechanisms to comply with regulations, privacy, and security, and technology choices to develop a strong automation platform.
