This resource provides an overview of key concepts in data analytics. The information is presented for educational purposes.
Descriptive analytics focuses on summarizing historical data to understand what has happened.
Key insight: This type of analysis helps identify patterns and trends from past information.
Diagnostic analytics examines data to understand why certain events occurred.
Key insight: This approach helps identify root causes and relationships between different factors.
Predictive analytics uses statistical models to forecast future outcomes based on historical data.
Key insight: These models can estimate the likelihood of future events and trends.
Prescriptive analytics suggests actions to achieve desired outcomes based on predictive insights.
Key insight: This type of analysis provides recommendations for optimal decision-making.
| Analytics Type | Primary Focus | Common Applications |
|---|---|---|
| Descriptive | What happened | Reporting, dashboards |
| Diagnostic | Why it happened | Root cause analysis |
| Predictive | What will happen | Forecasting, risk assessment |
| Prescriptive | What should be done | Optimization, recommendations |
Predictive analytics is particularly valuable because it enables proactive decision-making based on future expectations rather than just past performance.