Data Science

Use of the term "data science" is increasingly common, as is "big data." But what does it mean? Is there something unique about it?

In our definition, it is a systematic process that builds and organizes knowledge either to solve problems, mitigate crisis, control risk, increase revenue or reduce cost.

Data science might therefore imply a focus involving data and, by extension, statistics, or the systematic study of the organization, properties, and analysis of data.

Data Science use cases

Churn Prevention

Identify customers likely to leave, take preventative action

Customer Segmentation

Create meaningful customer groups for more relevant interactions.

Price Optimization

Calculate how demand varies at different price levels, then combine that data with information on costs and inventory levels to recommend prices that will improve profits.

Predictive maintenance

Predictive equipment failure, plan cost-effective maintenance.

Risk Management

Understand risk to manage it.

Up-and Cross-Selling

Convince customers to buy more.

Demand Forecasting

Know what volumes to expect to improve planning.

Fraud Detection

Identify fraudulent activity quickly, and ent it.

Product Propensity

Predict what your customers will buy, before even they know it.