# Unit 1: Introduction to Data Mining

Welcome to your simplified notes for Unit 1.

## Table of Contents

1. [[01_Introduction_to_Data_Mining|Introduction & DIKW Pyramid]]
   - What is Data Mining?
   - The DIKW Pyramid (Data, Information, Knowledge, Wisdom)
2. [[02_Data_Mining_Process|The Data Mining Process]]
   - Steps from Goal Definition to Deployment
   - Issues in Data Mining (Privacy, Scalability)
3. [[03_Data_Mining_Techniques|Techniques & Functionalities]]
   - Predictive vs Descriptive Mining
   - Classification, Regression, Clustering, Association Rules
4. [[04_Data_Preprocessing|Data Preprocessing]]
   - Why do we need it?
   - Cleaning, Integration, Reduction, Transformation
5. [[05_Data_Processing_Methods|Data Processing Methods]]
   - Manual vs Electronic
   - Batch, Real-time, Online Processing
6. [[06_Data_Discretization|Data Discretization]]
   - Binning, Histograms
   - Concept Hierarchy