Decision Science is the art of utilizing insights and predictions derived from our data science applications and applying them to real-world scenarios that your business might face. Let’s dive into the specifics.
IntelliTide data science; put to work.
The popular Cross Industry Standard for Data Mining (CRISP-DM) advocates the following phases for a typical analytical project.
Problem Objectives
Data Study
Data Preparation and Feature Engineering
Analysis & Modelling
Evaluation
Reporting & Deployments
Most data science companies perform one or two of these phases at the most, leaving the rest for you to figure out. Intellitide on the other hand, excels in executing all these steps – making us a one-stop-shop for all your data processing needs.
Actionable insight is achieved through two steps:
Sorting and Improving Data Quality
These processes have to be perfectly executed in order to get reasonable insight. We have our best minds at work on these steps, and the result is data that is usable and organized — ripe for processing.
Application of Suitable Algorithms and Statistical Models
Our PhDs and Data Architects use years of expertise to apply suitable algorithms and statistical models to the data, giving insight that we use in our decision science processes.
