Data Kitchen: 7 Steps to Implement DataOps

Data analytics teams challenged by inflexibility and poor quality have found that DataOps
can address these and many other obstacles. DataOps includes tools and process
improvements that enable faster, more responsive data analytics while maintaining a high
level of quality and reliability. Data analytic teams can implement DataOps in seven simple
steps: (1) Add data and logic tests, (2) Use a version control system, (3) Branch and merge,(4) Use multiple environments, (5) Reuse and containerize, (6) Parameterize your processing and (7) Work Without Fear™.