Similar to its close relation DevOps, which has emerged to meet the needs of modern app development and deployment by unifying software development and software operations and automating and monitoring the stages of application development, DataOps continues to evolve in response to the explosion of data and its importance in fueling software development, BI, analytics, AI and
machine learning, and other use cases.
The notion of DataOps, which embraces data management processes and procedures to shorten the development cycle and increase the dependability of releases, is growing as more organizations take on innovation initiatives that depend on the free flow of data. This checklist will explore the concept of a platform-based approach to DataOps.
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