Data mining involves using computational techniques to discover patterns in large data sets. It is part of the broader knowledge discovery in databases (KDD) process. The presentation discusses data mining tasks like classification, clustering, association rule mining, and summarization. It also covers the advantages of data mining for marketing, finance, manufacturing and governments, as well as the disadvantages of privacy and security issues. In conclusion, data mining can benefit businesses and society by discovering patterns in data, but privacy and security concerns must be addressed.

1. PRESENTATION ON
DATA MINING
MONSUR AHMED SHAFIQ
ID:151-15-5439
SEC: G

2. Data Mining
Data mining is the computational process of discovering
patterns in large data sets.
Data mining is the analysis step of the "knowledge discovery
in databases" process, or KDD

3. Knowledge Discovery in Databases
The term Knowledge Discovery in Databases refers to the
broad process of finding knowledge in data.

4. Data mining task
1. Classification
Classification maps data into predefined groups or classes.
Represented by methods such as decision trees, etc.
2. Clustering
Clustering is similar to classification .Except that the groups are
not predefined.
3. Association Rule
Association refers to uncovering relationship among data.
4. Summarization
Summarization of general characteristics or features of target class
of data.

5. Advantages and Disadvantages of
Data Mining
Advantages :
1.Marketing
2.Finance
3.Manufacturing
4.Governments
Disadvantages:
1.Privacy Issues
2.Security issues

6. Conclusion
Discovering interesting patterns from large amounts of
data.
Data mining brings a lot of benefits to businesses,
society, governments as well as the individual.
However, privacy, security, and misuse of information
are the big problems if they are not addressed and
resolved properly.