The Power Of Predictive Analytics. [Video]

Predictive Analytics is the use of data, statistical algorithms, and machine learning techniques to forecast future events, behaviors, or outcomes. It involves analyzing historical data to identify patterns and correlations, which are then used to make predictions about future trends and events.

Types of Predictive Analytics:

1. Descriptive Analytics (what happened)
2. Diagnostic Analytics (why it happened)
3. Predictive Analytics (what will happen)
4. Prescriptive Analytics (what should happen)

Applications of Predictive Analytics:

1. Customer Relationship Management (CRM)
2. Risk Management
3. Fraud Detection
4. Marketing Optimization
5. Supply Chain Optimization
6. Healthcare Outcomes
7. Financial Forecasting
8. Energy Demand Forecasting
9. Traffic Management
10. Sports Performance Prediction

Benefits of Predictive Analytics:

1. Improved decision-making
2. Enhanced customer experiences
3. Reduced risk
4. Increased efficiency
5. Competitive advantage
6. Improved forecasting accuracy
7. Identification of new business opportunities
8. Optimization of resources
9. Enhanced innovation
10. Data-driven insights

Common Techniques Used:

1. Regression Analysis
2. Decision Trees
3. Random Forest
4. Neural Networks
5. Clustering
6. Time Series Analysis
7. Text Analytics
8. Machine Learning
9. Deep Learning
10. Ensemble Methods

Predictive Analytics has the potential to transform industries by enabling proactive decision-making, improving outcomes, and driving innovation.