Data Operations (DataOps) - Definition

DataOps stands for “Data Operations” and unites DevOps teams with data experts and data scientists to develop tools, processes and organizational structures for data-oriented companies.

It is a process-oriented methodology that optimizes the design, development and maintenance processes of data-based applications. Similar to DevOps, it extends the concept of continuous delivery to the lifecycle of data and integrates data specialists into DevOps teams. DataOps is an automated, process-based methodology that improves the quality of data analysis and reduces processing time. Using agile principles, it increases development efficiency and promotes transparent collaboration. The benefits of DataOps include faster development of data products, more efficient implementation of data projects and integration of data into the corporate culture.

Overall, DataOps emphasizes the continuous delivery of analytical insights and harmonizes well with microservices architectures. It is not limited to machine learning, but supports any data-oriented work in the company.

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