OutlineOutline Introduction Data Where house Usage Evolution of Technology What is Data Mining ? Data Mining Application Data Mining in Use Data Mining Process Works with Data Where house

IntroductionIntroduction

Nowadays there is also a great amount of applications and services that are available through Internet as they are seeking, chats, sales, etc.

Knowledge discovery is a concept that describes the process of searching on large volumes of data for patterns that can be considered knowledge about the data.

Three kinds of data warehouse applications Information processing:-

Supports querying, basic statistical analysis, and reporting using cross tabs, tables, charts and graphs.

Analytical processing:-Multidimensional analysis of data

warehouse data supports basic OLAP operations, slice-dice, drilling, pivoting.

Data mining:-Knowledge discovery from hidden patterns

supports associations, constructing analytical models, performing classification and prediction, and presenting the mining results using visualization Tools.

Data Where house UsageData Where house Usage

1960s:Data collection, database creation, IMS and

network DBMS. 1970s:

Relational data model, relational DBMS implementation.

1980s: RDBMS, advanced data models (extended-

relational database ), Application-oriented DBMS (spatial, scientific,

engineering, etc.). 1990s:

Data mining, data warehousing and Web databases.

2000s:Data mining and its applications Web technology

(XML, dataintegration) and global information systems.

Evolution of TechnologyEvolution of Technology

Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential.

Data mining is a knowledge discovery process in large and complex data sets, refers to extracting or “mining” knowledge from large amounts of data.

What is Data Mining..??What is Data Mining..??

What is Data Mining..??What is Data Mining..??

Web Mining Social data mining Preserving Privacy Data Mining (PPDM)

Data Mining ApplicationData Mining Application

Usually, web mining is categorized as web content mining and web usage mining.

Both usage and content attributes of a site is

described. Some techniques based on clustering and association rules are proposed.

Web MiningWeb Mining

Social data mining is a new and challenging aspect of data mining.

Social data mining includes communities, searching for multimedia data (images, video, digital photos, audio recordings etc) .

It also search personalization search methods for social activities (find friends), text mining for blogs or other forums.

Social Data MiningSocial Data Mining

More recently, stated that “privacy is about self-possession, autonomy, and integrity.”

Another view is corporate privacy – the release of information about a collection of data rather than an individual data item.

For example:-I may not be concerned about someone knowing my birth date, mother’s name, or social security number.

Preserving Privacy Data Mining (PPDM)Preserving Privacy Data Mining (PPDM)

The US Government uses Data Mining to track fraud

A Supermarket becomes an information broker

Basketball teams use it to track game strategy

Cross Selling Target Marketing Holding on to Good Customers Weeding out Bad Customers

Data Mining in UseData Mining in Use

Problem definition

Creating a database for Data Mining

Exploring the Database

Preparation for creating a Data Mining Model

Evaluating the Data Mining Model

Building a Data Mining Model

Deploying the Data Mining Model

Data Mining ProcessData Mining Process

Data Warehousing provides the Enterprise with a memory.

Data Mining provides the Enterprise with intelligence.

Works with Data Where HouseWorks with Data Where House