Cloud Computing Study Guide - 06
Study Guide
Beginner → Exam Ready
By Levi J.
2026 Edition
Analytics and Business Intelligence
Analytics Techniques
The Core Goal
Analytics techniques are methods used to answer essential business questions to understand successes,
failures, and product take actions.
Analytics Maturity Model
The relationship between the value provided by an analytics technique and its implementation difficulty.
Types of Analytics
1. Descriptive Analytics
Definition:
Uses historical data to answer "what has happened to the business."
How It Works:
It relies on Key Performance Indicators (KPIs), which are summaries of large datasets used to track the
success or failure of key activities.
Why We Use It:
It is the easiest approach and is typically the very first technique organizations implement when moving to
data-driven decisions.
Page 1 of 8
, Cloud Computing Study Guide - 06
Examples:
Monthly sales reports
Customer counts
Revenue totals
2. Diagnostic Analytics
Definition:
Uses historical data to understand why different events have happened.
How It Works:
It goes one step beyond descriptive analytics by discovering the root cause behind events.
This is the Riskiest Technique
Common Techniques:
Anomaly detection (finding outliers)
Data mining
Correlation analysis
Examples:
Why did sales drop in March?
What caused the increase in customer complaints?
3. Predictive Analytics
Definition:
Uses statistical models and machine learning to predict future outcomes based on historical data.
How It Works:
It analyzes patterns in historical data to make predictions about future events.
Examples:
Predicting customer churn
Forecasting sales
Risk assessment
Page 2 of 8
Study Guide
Beginner → Exam Ready
By Levi J.
2026 Edition
Analytics and Business Intelligence
Analytics Techniques
The Core Goal
Analytics techniques are methods used to answer essential business questions to understand successes,
failures, and product take actions.
Analytics Maturity Model
The relationship between the value provided by an analytics technique and its implementation difficulty.
Types of Analytics
1. Descriptive Analytics
Definition:
Uses historical data to answer "what has happened to the business."
How It Works:
It relies on Key Performance Indicators (KPIs), which are summaries of large datasets used to track the
success or failure of key activities.
Why We Use It:
It is the easiest approach and is typically the very first technique organizations implement when moving to
data-driven decisions.
Page 1 of 8
, Cloud Computing Study Guide - 06
Examples:
Monthly sales reports
Customer counts
Revenue totals
2. Diagnostic Analytics
Definition:
Uses historical data to understand why different events have happened.
How It Works:
It goes one step beyond descriptive analytics by discovering the root cause behind events.
This is the Riskiest Technique
Common Techniques:
Anomaly detection (finding outliers)
Data mining
Correlation analysis
Examples:
Why did sales drop in March?
What caused the increase in customer complaints?
3. Predictive Analytics
Definition:
Uses statistical models and machine learning to predict future outcomes based on historical data.
How It Works:
It analyzes patterns in historical data to make predictions about future events.
Examples:
Predicting customer churn
Forecasting sales
Risk assessment
Page 2 of 8
