DataOps-based architecture
DataOps is a mature data management framework with best practices and principles adopted from software engineering and manufacturing frameworks such as Agile, DevOps, and statistical process control. In DataOps, these successful best practices are applied in the context of data management to achieve fast, high-quality, and cost-efficient data delivery. DataOps continuously monitors data post-deployment to keep an eye on its pulse to check its health. In my view, a DataOps discipline is a necessary framework that drastically accelerates a Data Fabric architecture. DataOps was introduced in Chapter 4, Introducing DataOps.
What’s the difference between DataOps and data engineering?
These terms are often used interchangeably; however, they are not the same thing. The assumption made when referring to DataOps is that it refers to daily data operations within a business. DataOps is a data management discipline with established principles that achieve...
