Telecommunication companies generate huge volumes of data from their operational systems. They use data mining methods and business intelligence technology to handle business problems by analyzing call detail, customer, and network data. The main applications of data mining in telecommunications include fraud detection, network fault isolation, and improving market effectiveness. Data mining helps telecom companies detect fraud, gain customer insights, retain customers, determine profitable products and services, and identify factors influencing customer call patterns.

1. Data Mining in
TELECOMMUNICATION
industry's

2. Data Mining in TELECOMMUNICATION industry’s
Data Mining

3. Data Mining in TELECOMMUNICATION industry’s
Telecommunication
Telecommunication companies today are operating in highly
competitive and challenging environment. Huge volume of data is
generated from various operational systems and these are used for
solving many business problems that required urgent handling.
These data include call detail data, customer data and network
data. Data Mining methods and business intelligence technology are
widely used for handling the business problems in this industry. The
main application areas of BI and Data Mining in telecommunication
industry include fraud detection, network fault isolation and
improving market effectiveness.

4. Data Mining in TELECOMMUNICATION industry’s
Data Mining in
Telecommunications
• To detect frauds
• To gain knowledge about the customers
• Retain Customers
• What products and services yield highest
amount of profit?
• What are the factors that influence customers
to call more at certain times?

5. Data Mining in TELECOMMUNICATION industry’s
Customer Segmentation &
Profiling
Customer Segmentation:
• To describe the process of dividing customers into homogeneous groups on the basis
of shared or common attributes (habits, tastes, etc.)
Difficulties:
• Relevance and quality of data
• Intuition
• Continuous process
• Over-segmentation
Customer Profiling:
• Describing customers by their attributes, such as age, gender, income and lifestyles
Parameters:
• Geographic ,Cultural and ethnic ,Economic conditions ,Age and Gender ,Attitudes and
beliefs ,Lifestyle ,Knowledge and Awareness

6. Data Mining in TELECOMMUNICATION industry’s
Types of Telecommunication
Data
• Call-Detail Data
• Network Data
• Customer Data
Call-Detail Data:
• average call duration
• average call originated/generated
• call period
• call to/from different area code
Network Data:
• Complex configuration of equipment's
• Error Generation
• To support Network Management functions
Customer Data:
• Database of information of Customers
• Name ,Age ,Address ,Telephone type ,Subscription Type ,Payment History

7. Data Mining in TELECOMMUNICATION industry’s
Data Preparation and Clustering
Data preparation
• To be prepared in the required format
Tasks:
• Discovering and Repairing inconsistent data format
• Deleting unwanted data fields
• Combining data
• Mapping of values
• Normalization of the variables
Clustering:
• Grouping of Similar things
Cluster Analysis:
• Organization of objects into groups, according to similarities among them.

8. Data Mining in TELECOMUNICATION industry’s
Applications
Marketing/Customer Profiling Fraud Detection Network Fault Isolation

9. Early adopter of Data mining technology
To detect frauds
Helps to know the Customer
Serve them Better
Yield more profit
Reduced much of Human based analysis-
Essential for Telecommunication companies
Data Mining in TELECOMMUNICATION industry’s
Conclusion

10. Data Mining in TELECOMMUNICATION industry’s
Future Trends
Additional themes on data mining
New Methods for Complex types of Data
Invisible Data mining(mining as a built in function)
Reduction in Human work
Advanced methods in Data mining

11. THANK YOU
Data Mining in
TELECOMMUNICATION
industry's
By: Pragya Ratan Sagar