KDD PROCESS

1. KDD Process
By
G.Rajesh Chandra

2. Knowledge Discovery (KDD) Process
– Data mining—core of
knowledge discovery
process
Pattern Evaluation
Data Mining
Task-relevant Data
Data Warehouse
Data Cleaning
Data Integration
Databases
December 26, 2013
Selection

3. DATA CLEANING
• Remove Noise and Inconsistent Data

4. DATA INTEGRATION
• Where multiple data sources may be combined

5. DATA SELECTION
• Where data relevant to the analysis task are
retrieved from the data base

6. DATA TRANSFORMATION
• Where data are transformed and consolidated
into forms appropriate for mining by
performing summary or aggregation operation

7. Data Mining
• An essential Process where intelligent
methods are applied to extract data patterns

8. PATTERN EVALUATION
• To identify the truly interesting patterns
representing knowledge based on
interestingness measures

9. KNOWLEDGE REPRESENTATION
• Where visualization and knowledge
representation techniques are used to present
mined knowledge to users

10. WHAT KINDS OF DATA CAN BE MINED
•
•
•
•
DATABASE DATA
Data warehouses
Transactional data
Other Kinds of Data

11. DATABASE DATA
•
•
•
•
DBMS
Relational Database Examples
Attributes
Tuples

12. Data warehouses

13. Data Cube

14. Transactional Data
• A Transactional data must be unique

15. Other Kinds of Data
•
•
•
•
•
•
•
•
Time Related Data
Sequence Data(Historical Records,Stock Exchange)
Data streams( Video Surveillance, Sensor Data)
Spatial Data(maps)
Hyper Text and Multimedia Data(Text,Video,Audio)
Graph and Networked Data
Engineering Design Data(auto CAD)
Web