Scoring-as-a-Service To Operationalize Algorithms For Real-time

If you are using data science for only one-time, ad-hoc analysis, then you are doing it wrong. There is no doubt that companies can benefit greatly from this type of one-time data science exercise and most start here. However, much more value is created when data science can be applied in real-time scenarios and in an ongoing manner. We can't just build a machine learning (ML) model and share the insights, we have to go to the next step and operationalize it, making it part of the fabric of our business processes and affecting outcomes in real-time. For example, what becomes possible when we can score human movement in real-time--like a system that can tell you that someone is currently running or moving at 30 MPH when they shouldn't be or just fell down on the floor.