PREDICTIVE ANALYTICS

Predictive Analytics

Concepts and Applications   

 

INTRODUCTION

HOW DOES PREDICTIVE ANALYTICS WORK?

TYPES OF PREDICTIVE MODELS

Type                              Description

Classification                Group new data to segment where it belongs

Clustering                      Divides data into homogeneous groups

Outlier detection           Finds anomalies in data. Helps in fraud detection

Forecasting                    Obtain metric value from new data based on historical data insights

Time series                    Predicts trends by combining multiple data points at regular time intervals

SOME APPLICATIONS OF PREDICTIVE ANALYTIC

CHALLENGES OF PREDICTIVE ANALYTICS

WAY FORWARD

• Data volume from various sources is increasing at a rapid rate providing valuable resource for model building
• Increased advancement of AI and ML has positive impact on accuracy of models
• Rise of explainable AI helps in transparency and exploitability
• Real time predictive analytics analyzes data as it is generated, thus helps in making instant decision in the face of changing marketing conditions