Understanding Data Analytics

This resource provides an overview of key concepts in data analytics. The information is presented for educational purposes.

Table of Contents

Descriptive Analytics

Descriptive analytics

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

Diagnostic

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

Predictive

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

Prescriptive

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 Types Comparison

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

Most Valuable Analytics Approach

Predictive analytics is particularly valuable because it enables proactive decision-making based on future expectations rather than just past performance.