Algorithmic approaches to extract patterns, insights, and value from data, in a business decision-making context.
The end-to-end pipeline of Data > Modeling > Decisioning > Deployment, when integrated and applied in specific business decision context, can deliver clear and measurable impact both on revenue and cost. Our objective in delivering data science is just that – ensuring measurable business value.
How can Data Science help you?
New age algorithms to derive value from complex and big data – e.g. real-time bidding, IoT sensor data based maintenance, recommender systems.
Leverage structured and unstructured data to predict future events – e.g. trends, pricing decisions, fraud risk, customer attrition etc.
Drive superior operations and planning through demand forecasting, cost planning, granular sales, shipment forecasting etc.
Text Analytics & NLP
Draw meaningful insights from text data – e.g. conversation themes, topics, sentiment, sales leads, customer satisfaction etc.
Achieve optimal revenue, margin or cost in a given decision framework – e.g. maximize marketing reach, resource optimization, inventory management.
Most data science problems can be divided into three sequential phases – problem definition & data discovery, model estimation & validation, insights & business application. We have broad frameworks to systematically approach a wide variety of data science problems to ensure business value.
- phase 1
- Problem Definition
- Data Preparation
- Data Discovery
- phase 2
- Feature Engineering
- Model Development
- Model Validation
- phase 3
- Insights & Inferences
- KPI Dashboards
- Production & Monitoring
Real-Time Bidding Models Power 200 MM Digital Ads Every Day
Predicting Emerging Flavors And Ingredients Across 2 Million F&B Products In 75 Countries