Predictive analytics fundamentals
In this lesson we will learn what predictive analytics is, why it has become one of the most important tools in the modern business world, and how to build a conceptual and practical foundation for working with predictive models.
1 What is predictive analytics and its business applications
Predictive Analytics is a branch of data science that focuses on using historical data, statistical algorithms and machine-learning techniques to identify the probability of future outcomes. Unlike descriptive analytics, which explains what happened in the past, predictive analytics asks: What is expected to happen in the future?
A precise definition
Predictive analytics is the process of using data, statistical algorithms and ML techniques to identify the probability of future outcomes based on historical data. The goal is to bridge the gap between "what happened" and "what will happen next".
Key business applications
Retail and sales
- ▸ Forecasting product demand and seasonality
- ▸ Optimal inventory management and preventing surplus
- ▸ Predicting customer churn (Churn)
- ▸ Personalized product recommendations
Finance and insurance
- ▸ Predicting credit risk and customer scoring
- ▸ Real-time fraud detection
- ▸ Forecasting stock and asset prices
- ▸ Risk management and investment portfolios
Health and medicine
- ▸ Predicting diseases and health risks
- ▸ Optimizing hospital-bed allocation
- ▸ Predicting response to drug treatments
- ▸ Medical image analysis and diagnostics