Benefits & Challenges Of DataOps In Data Science

The one thing that is common between development projects and data projects is that they both hold a lot of promise. But, at the time of rolling out production, the latter is delivered late and once that is done, they tend to underperform. One of the main reasons for their potential underperformance is that there is a lack of collaboration between departments, and at the same time, a cultural imbalance as well. To counter these, DataOps brings automation and cultural shift to an organization's data project, which is similar to what DevOps offers the software world. DataOps is more like a mindset than a job title. It encourages collaboration, automation, and constant innovation related to data inside a data-driven environment. Just as software that is developed outside its live environme