GROUP MEMBERSNAMES ROLL-NO

WASIM RAZA BSCS-13-F-293

SHAHRUKH IDREES BSCS-13-F-281

KALSOOM AKHLAQ BSCS-13-F-252

SANILA SAJID BSCS-13-F-274

RABIYA FATIMA BSCS-13-F-255

HAFSA QURESHI BSCS-13-F-248

What is data mining?

Data mining is also called knowledge discovery and data mining (KDD)

extraction of useful patterns from data sources, e.g., databases, texts, web, image.

Patterns must be:valid, novel, potentially useful,

understandable

Why data mining now?

The data is abundant. The data is being warehoused. The computing power is affordable. The competitive pressure is strong. Data mining tools have become

available

DATAWARE HOUSING

The electronic storage of a large amount of information by a business. Warehoused data must be

stored in a manner that is

secure, reliable, easy to

retrieve and easy to manage.

DATABASE

A database is a collection of information that is organized so that it can

easily be accessed, managed,

and updated.

DIFF B/W DWH & DATA MINING

Process to compiling & organizing data into same database.

Engineering phase but no business users are involve.

Process of designing, how to data stored to improve reporting.

Process to extracting meaningful data from database.

Business users but with the assistance of engineer.

Statical analysis, analyst use technical to query and sort through Terabytes of data looking for patterns.

DIFF B/W DB & DATA MINING

It involves day-to-day processing.

It is used to run the business.

It provides primitive and highly detailed data.

It is based on Entity Relationship Model.

It contains current data.

extraction of previously unknown and interesting

information from raw data.

Due to the exponential growth of data, especially in areas such as business.

convert this large wealth of data in to business intelligence.

Data mining applications Marketing, customer profiling and

retention, identifying potential customers, market segmentation.

Fraud detection identifying credit card fraud, intrusion detection

Scientific data analysis Text and web mining Any application that involves a large

amount of data …

ADVANTAGES OF DATA MINING Marking/Retailing: Data mining can aid

direct marketers by providing them with useful and accurate trends about their customers’ purchasing behavior.

Banking/Crediting: Data mining can assist financial institutions in areas such as credit

reporting and loan information. 

ADVANTAGEOUS OF DATA MINING (cont…) Law enforcement: Data mining can aid

law enforcers in identifying criminal suspects as well as apprehending these criminals by examining trends in location, crime type, habit, and other patterns of behaviors.

Researchers: Data mining can assist researchers by speeding up their data analyzing process; thus, allowing them more time to work on other projects. 

DIS-ADVANTAGEOUS OF DATA MINING Privacy Issues: For example, according to

Washing Post, in 1998, CVS had sold their patient’s prescription purchases to a different company ….

Security issues: Although companies have a lot of personal information about us available online, they do not have sufficient security systems in place to protect that information. 

DIS-ADVANTAGEOUS OF DATA MINING (cont….) Misuse of information: Some of the

company will answer your phone based on your purchase history. If you have spent a lot of money or buyinga lot of product from one company, your call will be answered really soon. So you should not think that your call is really being answer in the order in which it was receive.

DATA MINING TECHNIQUES

Classification:Classification is learning rules that can be applied to

new data and will typically include following steps: preprocessing of data, designing modeling, learning/feature selection and Evaluation/validation.

Association: Association is looking for relationships between

variables.

Clustering:

Clustering is identifying similar groups from unstructured data.

DATA MINING TECHNIQUES(CONT…) Sequential pattern mining:

A sequential rule: A B, says that event A will be immediately followed by event B with a certain confidence.

Deviation detection: discovering the most significant changes in data.

Regressions:

 Regression is finding functions with minimal error to model data .

REFERENCES http://www.differencebetween.com/differ

ence-between-dbms-and-vs-data-mining/

www.sims.berkeley.edu/how-much-info http://www.programmerinterview.com/

index.php/database-sql/data-mining-vs-warehousing/

ANY QUESTION…..?