Where DevOps is automation, technology, and delivery focused; DataOps is more customer focused. I like these descriptions from Wikipedia for DevOps and DataOps;
- DevOps is a set of practices that combines software development (Dev) and IT operations (Ops). It aims to shorten the systems development life cycle and provide continuous delivery with high software quality. https://en.wikipedia.org/wiki/DevOps
- DataOps is an automated, process-oriented methodology, used by analytic and data teams, to improve the quality and reduce the cycle time of data analytics. While DataOps began as a set of best practices, it has now matured to become a new and independent approach to data analytics. DataOps applies to the entire data lifecycle from data preparation to reporting, and recognizes the interconnected nature of the data analytics team and information technology operations. https://en.wikipedia.org/wiki/DataOps
- Where is the data? How do we get at it?
- How do we best move it? How often? What are the security or privacy issues?
- What needs to be cleansed or transformed? Is the data at the correct granularity?
- Do we already have any related data to improve the intelligence? Is this a new build or do we use / alter an existing pipeline?
- What models or analytics do we apply?
- How do we best visualize the data?