Data science is a fascinating blend of math, art, science...and code !

Data Science offers a distinctly different perspective than capabilities such as Business Intelligence. At Prescience we do not replace Business Intelligence functions with Data Science within an organization, but use the two capabilities as additive and complementary, each offering a necessary view of business operations and the operating environment.

We recognize that Data Science is a team sport  and we play with tools, data, and algorithms

Creating Enterprise AI/ML applications requires a variety of talents to work together seamlessly. Our interdisciplinary high-performance teams bring strong blended expertise in the foundations of data science – math, data, computing and business. This enables us to be specialists in advanced analytics enterprise grade applications.

At Prescience, when engineering a complete Data Science solution, we work with first understanding the data types, we then choose the analytic class and learning models and finally strategize the execution model to run the analytics.

Analytic goals are derived from business objectives, but the data type also influences the goals. We work with structured and unstructured data sets.

We apply different analytic techniques in multiple ways to
achieve various analytic goals. We are well versed with transforming, learning and predictive techniques.

Learning models characterize how the analytic is trained to perform judgments on new data based on historic observation.We work with both  unsupervised or supervised learning models.

Execution models describe how data is manipulated to perform an analytic function. We work with both batch and streaming execution models.