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DataOps
DataOps takes the practices and values of DevOps and extends it to data analytics workflows and goals. It applies the focus on collaboration and shared responsibility and shifts it to the engineers and admins that collect, store, analyze, secure, and deliver data.
DataOps is a series of principles and practices that promises to bring together the conflicting goals of the different data tribes in the organization, data science, BI, line of business, operations, and IT. What has been a growing body of best practices is now becoming the basis for a new category of data access, blending, and deployment platforms that may solve data conflicts in your organization.
https://towardsdatascience.com/introduction-to-datasecops-77ad9103d973
https://cloud.google.com/architecture/data-lifecycle-cloud-platform
https://github.com/datacoon/awesome-dataops
https://www.devopsschool.com/blog/top-20-dataops-tools-and-its-ranking/