Data Analysis Techniques
==2024-12-23=!=
Discipline is the bridge between goals and accomplishments.
Theory
list from [[]] and !outgoing([[]])It is important to know about Data Analysis, Data Analytics and Difference between Data Analysis and Data Analytics.
Categories of Data Analysis Techniques
- Descriptive Analysis: What happened?
- Diagnostic Analytics: Why did it happen?
- Predictive Analysis: What is likely to happen?
- Prescriptive Analysis: What should we do about it?
Descriptive Analysis
- Categorizes and summarizes raw data to uncover patterns.
- Examples:
- Categorizing customers by purchasing patterns.
- Analyzing census data.
- Key Measures:
Diagnostic Analytics
- Examines causes and effects to determine why something happened.
- Examples:
- Social media campaign analysis.
- Techniques:
- Purpose:
- Refines strategies based on past performance.
Predictive Analysis
- Predicts future outcomes based on past data.
- Examples:
- Predicting consumer behavior during tax season.
- Tools:
- Key Considerations:
- Predictions are based on probabilities, not guarantees.
Prescriptive Analysis
- Identifies the best course of action by analyzing parameters.
- Examples:
- Healthcare management: Prioritizing treatments.
- Risk management: Mitigating potential risks.
- Techniques:
The end is where we start again!