Data Warehousing & Data Mining Slides

7/29/2019 Data Warehousing & Data Mining Slides

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GROUP NO - 6


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Introduction

Data Warehousing and Data Mining :

WHAT and WHY ?


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What is a Data Warehouse?

A single, complete andconsistent store of dataobtained from a variety of

different sources madeavailable to end users inwhat they can understandand use in a businesscontext.


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Data Warehousing --It is a process

Technique for assembling andmanaging data from varioussources for the purpose of

answering business questions.Thus making decisions that werenot previously possible

A decision support database

maintained separately from theorganizations operationaldatabase


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A Producer wants to know

Which are ourlowest/highest margin

customers ?

Who are my customersand what products

are they buying?

Which customers

are most likely to goto the competition ?

What impact willnew products/services

have on revenue

and margins?

What product prom-

-otions have the biggestimpact on revenue?

What is the mosteffective distribution

channel?


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What are the userssaying...

Data should be integratedacross the enterprise

Summary data has a realvalue to the organization

Historical data holds the key

to understand data over time


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Problems

I cant find the data I need Data is scattered over the network

Many versions, subtle differences

I cant get the data I need

Need an expert to get the data

I cant understand the data I found

Available data poorly documented

I cant use the data I found

Results are unexpected

Data needs to be transformedfrom one form to other


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What is Data Warehousing ?

A process of transformingdata into information andmaking it available tousers in a timely enoughmanner to make adifference.

Data

Information


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Evolution

60s: Batch reports hard to find and analyze information

inflexible and expensive, reprogram every new request

70s: Terminal-based DSS and EIS (executive

information systems) still inflexible, not integrated with desktop tools

80s: Desktop data access and analysis tools query tools, spreadsheets, GUIs

easier to use, but only access operational databases

90s: Data warehousing with integrated OLAPengines and tools


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Very Large Data Bases

Terabytes -- 10^12 bytes:

Petabytes -- 10^15 bytes:

Exabytes -- 10^18 bytes:

Zettabytes -- 10^21 bytes:

Zottabytes -- 10^24 bytes:

Walmart -- 24 Terabytes

Geographic Information

SystemsNational Medical Records

Weather images

Intelligence Agency Videos


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Data Warehouse

A data warehouse is a

subject-oriented

integrated

time-varying

non-volatile

Collection of data that is used primarily in

organizational decision making.


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Explorers, Farmers andTourists

Farmers: Harvest informationfrom known access paths.

Explorers: Seek out the unknownand previously unsuspectedrewards hiding in the detailed data.

Tourists: Browse informationharvested by farmers .


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Data Warehouse forDecision Support

Putting Information technology to help the

knowledge worker make faster and better

decisionsWhich of my customers are most likely to go to

the competition?

What product promotions have the biggest

impact on revenue?

How did the share price of software companies

correlate with profits over last 10 years?


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Decision Support

Used to manage and control business

Data is historical or point-in-time

Optimized for inquiry rather than update

Use of the system is loosely defined and

can be ad-hoc

Used by managers and end-users to

understand the business and make

judgements


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Data Mining works withWarehouse Data

Data Warehousing provides theEnterprise with a memory.

Data Mining provides the Enterprise withintelligence.


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Problems

Given a database of 100,000 names, which persons are theleast likely to default on their credit cards?

Which types of transactions are likely to be fraudulent giventhe demographics and transactional history of a particularcustomer?

If I raise the price of my product by Rs. 2, what is the effecton my ROI?

If I offer only 2,500 airline miles as an incentive to purchaserather than 5,000, how many lost responses will result?

If I emphasize ease-of-use of the product as opposed to itstechnical capabilities, what will be the net effect on myrevenues?

Which of my customers are likely to be the most loyal?

Data Mining helps extract such information


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Areas of Application

Industry Application

Finance Credit Card Analysis

Insurance Claims, Fraud AnalysisTelecommunication Call record analysis

Transport Logistics management

Consumer goods promotion analysis

Data Service providers Value added data

Utilities Power usage analysis


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Data Mining in Use

The US Government uses Data Mining totrack fraud

Basketball teams use it to track game

strategy Warranty Claims Routing

Holding on to Good Customers

Weeding out Bad Customers


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What makes data miningpossible?

Advances in the following areas aremaking data mining deployable:

data warehousing

better and more data (i.e., operational,behavioral, and demographic)

the emergence of easily deployed datamining tools and

the advent of new data mining techniques.

-- Gartner Group


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Difference between data

Mining and Data Warehousing

Data Mining- Data Warehousing-

Data mining is theprocess of findingpatterns in a given

data set.

Data warehousing can besaid to be the processof centralizing oraggregating data from

multiple sources into onecommon repository.


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Difference between Data

Mining and Data WarehousingData Mining Data Warehousing

Men bought diapers on

Thursdays and Saturdays,they also had a strongtendency to buy beer. Thegrocery store could haveused this valuableinformation to increasetheir profits. This is datamining in actionextracting meaningful data

from a huge data set.

Facebook basically

gathers all of your datayour friends, your likes,who you stalk, etc andthen stores that data into

one central repository.


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Datamining Data warehousing


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Data mining Data warehousing

Documents

Data Warehousing & Data Mining Slides