Alisha Korpal

Nivia Jain

Sharuti Jain

Data Mining ?

Huge amounts of data Electronic record of our decisions

Choices in the supermarket Financial records

Data vs. Information

Data : Collection of raw data ,

facts and figures.

Information: processed form of data

Data Mining Extracting or “mining” knowledge from large amounts of

data Data – driven discovery and modeling of hidden patterns

in large volumes of data Extraction of interesting (non trivial, implicit, previously

and potentially useful) information or patterns from data

in large databases.

Data Mining Process Defining the problem Preparing data Exploring data Building Models Exploring and validating Models Deploying and Updating models

Data Mining Process

Defining the Problem What are you looking for?

What types of relationships are you trying to find?

Do you want to make predictions from the data mining model, or just look for interesting patterns and associations?

Contd…

Which attribute of the dataset do you want to try to predict?

How are the columns related? If there are multiple tables, how are the tables related?

Does the problem you are trying to solve reflect the policies or processes of the business?

Preparing Data

Exploring Data

You must understand the data in order to make appropriate decisions when you create the mining models. Exploration techniques include calculating the minimum and maximum values, calculating mean and standard deviations, and looking at the distribution of the data. 

Models

Building Models Exploring and Validating Models Deploying and Updating Models

Evolution of Data Mining Data collection -1960s

Data access - 1980s Data Warehousing & decision support -1990s Data Mining -Emerging Today

Evolutionary Step

Business Question Enabling Technologies

Characteristics

Data Collection(1960s)

"What was my total revenue in the last five years?"

Computers, tapes, disks Retrospective, static data delivery

Data Access(1980s)

"What were unit sales in New England last March?"

Relational databases (RDBMS), Structured Query Language (SQL), ODBC

Retrospective, dynamic data delivery at record level

Data Warehousing &Decision Support(1990s)

"What were unit sales in New England last March? Drill down to Boston."

On-line analytic processing (OLAP), multidimensional databases, data warehouses

Retrospective, dynamic data delivery at multiple levels

Data Mining(Emerging Today)

"What’s likely to happen to Boston unit sales next month? Why?"

Advanced algorithms, multiprocessor computers, massive databases

Prospective, proactive information delivery

Data mining Vs OLAP

On-line Analytical Processing Provides you with a very good

view of what is happening, but can not predict what will happen in the future or why it is happening

Scope of Data Mining

Automated prediction of trends and behaviors Automated discovery of previously unknown

patterns

Applications

Science: Chemistry, Physics, Medicine Biochemical analysis Remote sensors on a satellite Medical images analysis

Applications Financial Industry, Banks, Businesses, E

commerce Stock and investment analysis Risk management Sales forecasting

Applications

Database analysis and decision support Market analysis and management

Target marketing, customer relation management, market basket analysis, cross selling

Applications

Risk analysis and management Forecasting, customer retention, improved underwriting Fraud detection and management

References: http://www.data-miners.com/resources/SUGI29-Survival.

pdf http://docs.google.com/viewer?

a=v&q=cache:VRsb5lbwpGoJ:www.sdsc.edu/us/training/workshops/2006cihass/docs/2006cihass_DataMiningIntro.ppt+applications+of+data+mining+ppt&hl=en&gl=in&pid=bl&srcid=ADGEESg5iQeaEGa0RoHJpbQyDDbVKPNJwOS3Zg71DTIgFf8PhSbzZ39oAdQNwPb8wvwJAbwFwp-HcAwhGF-9C6TiHM3pv7vQm7Xf8umeBDY_oG6VtzK8eVwqAo95evUgkcvWwDO5YwKT&sig=AHIEtbQ1bj7uPnVGzCNysOs5V7_5apQk0A&pli=1

References:

http://www.thearling.com/text/dmwhite/dmwhite.htm http://www.anderson.ucla.edu/faculty/jason.frand/

teacher/technologies/palace/datamining.htm http://msdn.microsoft.com/en-us/library/ms174949.aspx

Result of Data Mining

What may happen in future Classifying people or things into groups by recognizing

patterns Clustering people or things into groups based on their

attributes Sequencing what events are likely to lead to later events

Data Mining is not

“Blind” applications of algorithms Going to find relations where none exist Presenting data in different ways A difficult to understand technology requiring an

advanced degree in computer science