Connecting the Business to Data Science with ModelOps

The inner workings of data science--much like that of multi-parameter, opaque machine learning models--have traditionally been an enigma to the average business user. While the latter simply desires accurate predictions to do his or her job better, how exactly cognitive computing aids this objective, and if it actually is doing so, has rarely been clear to these professionals. Will all the media fervor and enterprise spending on statistical applications of Artificial Intelligence, it's no longer acceptable for organizations to continue investing in data science without some assurance of the impact, positive or otherwise, their initiatives are producing. According to Datatron CEO Harish Doddi, "Over the last few years, so many organizations have invested in AI talent. 'What is the ROI of these models?' is the question that's coming from the business."