About Data Mining

2. • Why Data Mining?
• Why Data Mining?
• Data Mining: On What Kinds of Data?
• Goals of Data Mining
• Data Mining Models And Tasks
• Steps involved in Data Mining
• How data mining works?
• Data Mining vs. Data Warehousing
• Applications Of Data Mining
• Data Mining Solution Companies
• Advantages & Disadvantages of Data Mining
Agenda

3. What Is Data Mining
Data Mining is the process of analysing
data to find previously unknown trends,
patterns, and associations to make decisions.
Generally, data mining is accomplished through
automated means against extremely large data
sets, such as a data warehouse.

4. The explosive growth in data collection
The storing of data in data warehouses
The availability of increased access to data
from Web navigation and intranet
 We have to find a more effective way to use
these data in decision support process than
just using traditional querry languages
Why Data Mining

5. • Relational database
• data warehouse
• transactional database
• Data streams and sensor data
• Object-relational databases
• Multimedia database
• Text databases
• The World-Wide Web
Data Mining: On What Kinds of Data?

6. • Prediction e.g. Sales volume, earthquakes
• Identification e.g. Existence of genes, System
intrusions
• Classification of different categories e.g.
Discount seeking shoppers or loyal regular
shoppers in supermarket.
• Optimization of limited resources such as time,
space, money or materials and maximization of
output such as sales or profits.
Goals of Data Mining

7. Data Mining Models And Tasks

8.  Descriptive Modelling : it detects the
similarities between the collected data
and the reasons behind them. This is very
important in constructing the final
conclusion from the data set.
 Predictive Modelling : is used to analyse
the past data and predict the future
behaviour. Past data give some kind of
hint about the future.

9. Steps involved in Data Mining

10. • Collecting data (from Users)
• Storing data (Database: Data Warehousing)
• Business rules and analytics (Organizing data)
• Visualization (Data Mining Software)
• To find Unknown trends, Patterns
• Then, anything involving data you want to use
to improve profit.
How data mining works?

11. Data Mining is the
process of analysing
data to find previously
unknown trends,
patterns, and
associations to make
decisions.
A large store of data
accumulated from a
wide range of sources
within a company and
used for storage and
analysis.
Data Mining vs. Data Warehousing

12. Advantages of Data Mining
• Marketing/Retail
• Finance/Banking
• Manufacturing
• Governments
Advantages of Data Mining

13. Disadvantages of Data Mining
• Privacy Issues
• Security Issues
• Misuse of Information/Inaccurate Information
Disadvantages of Data Mining

14. Applications Of Data Mining
Industry Applications
Finance Credit card Analysis
Insurance Claims, Fraud Analysis
Telecommunication Call Record Analysis
Transport Logistics Management
Consumer Goods Promotion Analysis
Scientific Research Image, Video, Speech
Utilities Power Usage Analysis

15.  Usefulness
 Return on Investment (ROI)
 Accuracy
 Space/Time
Data Mining Metrics

16. Accenture
 IBM
 Tata Consultancy services
 Infosys
 Google
Data Mining Solution Companies

17.  Data mining brings a lot of benefits to
business, society, governments as well as
individual.
 In marketing, they have capability to increase
the profits and reduce the cost of products.
 Discovering interesting patterns from large
amount of data.
Conclusion & References

18. By Vinayak M. Kathar