Presentation on DW

7/23/2019 Presentation on DW

1/21

SEMINAR REPORT

ON

DATA WAREHOUSE

SAM HIGGINBOTTOM INSTITUTE OF AGRICULTURE,

TECHNOLOGY & SCIENCES (DEEMED TO BE UNIVERSITY

Department of Computer Science and I.T

Submitted By:

Ayush Barnawa !"#BT

Submitted T(:

Mudita Shri)asta)a


2/21

CONTENTS

HISTOR*

OB+E$TI,ES

E,O-UTION IN OR.ANI/ATIONA- USE

AR$HITE$TURE

O-TP

O-AP

BENE0ITS O0 DATA WAREHOUSE

STRATE.I$ USE

-IMITATIONS


3/21

HISTOR*

The concept of data warehousing dates back to the late

1980s when IBM researchers Barry Devlin and aulMurphy developed the !business data warehouse"#

Bill In$on% &ather 'f Data (arehouse#

)ccording to In$on*s Definition+

It is a collection of integrated% sub,ect-oriented databases

designed to support the D.. function% where each unit ofdata is non-volatile and relevant to so$e $o$ent in ti$e#


4/21

DATA WAREHOUSE

) single% co$plete and consistent store of

data obtained fro$ a variety of differentsources $ade available to end users in a what

they can understand and use in a business

conte/t#

) sub,ect-oriented% integrated% ti$e-variant%

non-updatable collection of data used in

support of $anage$ent decision-$aking

processes


5/21

DATA WAREHOUSIN. IS1

elational or Multidi$ensional Database Manage$ent .yste$

designed to support Manage$ent Decision Making#

Techniue for )sse$bling and Managing Data fro$ various sources

for the purpose of answering Business uestions#

) sub,ect-oriented% integrated% ti$e-variant% non-updatable

collection of data used in support of $anage$ent decision-$aking

processes#

2o$$on )ccessing syste$s include ueries% analysis and reporting

The final result% however% is ho$ogeneous data% which can be $ore

easily $anipulated#


6/21

SUB+E$T ORIENTED

DATA WAREHOUSE

'rgani3ed around $a,or sub,ects% such as custo$er%

product% sales#

&ocusing on the $odeling and analysis of data for decisio

$akers% not on daily operations or transaction processing#

rovide a si$ple and concise view around particular

sub,ect issues by e/cluding data that are not useful in the

decision support process#


7/21

INTE.RATED DATA WAREHOUSE

2onstructed by integrating $ultiple% heterogeneousdata sources#

elational databases% flat files% on-line transaction records#

Data cleaning and Data Integration techniues are

applied#

4nsures 2onsistency in na$ing conventions% encoding

structures% attribute structures% etc# a$ong different data sources#

4#g#% 5otel price+ currency% ta/% breakfast covered% etc#

(hen data is $oved to the warehouse% it is converted#


8/21

TIME ,ARIANT DATA WAREHOUSE

The ti$e hori3on for the data warehouse is significantly

longer than that of operational syste$s#

'perational database+ current value data#

Data warehouse data+ provide infor$ation fro$ a historical

perspective 6e#g#% past 7-10 years

4very key structure in the Data (arehouse#

2ontains an ele$ent of ti$e% e/plicitly or i$plicitly#

But the key of operational data $ay or $ay not contain "ti$e

ele$ent#


9/21

NON 2 ,O-ATI-E

DATA WAREHOUSE

hysically separate store of Data transfor$ed fro$ the

'perational 4nviron$ent#

'perational update of data does not occur in the data

warehouse environ$ent#

Does not reuire transaction processing% recovery% and concurrencycontrol $echanis$s#

euires only two operations in Data )ccessing#

Initial loading of Data#

)ccess of Data#


10/21

E,O-UTION

IN

OR.ANI/ATIONA- USE

Data% Data 4verywhere yet% I can*t find the data I need

Data is .cattered over the :etwork

Many versions% .ubtle differences

I can*t understand the data I found )vailable Data poorly docu$ented

I can*t use the data I found

esults are ;ne/pected

Data needs to be transfor$ed fro$ one for$ to 'ther


11/21

WH* DATA WAREHOUSIN. 3

Which are ourlowest/highest margin

customers ?

Which are ourlowest/highest margin

customers ?

Who are my customeand what productsare they buying?

Who are my customeand what productsare they buying?

What is the mosteectie distribution

channel?

What is the mosteectie distribution

channel?

What product prom!!otions hae the biggest

impact on reenue?

What product prom!!otions hae the biggest

impact on reenue?

What impact willnew products/serices

hae on reenueand margins?

What impact willnew products/serices

hae on reenueand margins?

Which customare most li"ely to the competit

Which customare most li"ely tto the competiti


12/21

Client Client

Warehouse

SourceSource Source

Query & Analysis

Integration

Metadata

AR$HITE$TURE


13/21

O-TP

O-TP4 ON-INE TRANSA$TION PRO$ESSIN.

.pecial data organi3ation% access $ethods andi$ple$entation $ethods are needed to support data

warehouse ueries 6typically $ultidi$ensional ueries#

'


14/21

O-TP ,s DWO-TP DW

)pplication 'riented .ub,ect 'riented

;sed to run business ;sed to )naly3e Business

Detailed Data .u$$ari3ed and efined

2urrent ;p-date Data .napshot Data

Isolated Data Integrated Data

&ew ecords )ccessed at a Ti$e6tens B Database .i3e 6100>B ?&ew Terabytes

Transaction throughput is perfor$anceMetric#

@uery throughput is the perfor$anceMetric#

Thousands of users 5undreds of ;sers


15/21

META DATA"Data about Data# It*s I$portant for Designing% 2onstructing%

etrieving% and controlling the (arehouse Data#

TE$HNI$A- META DATA

Include where the data co$e fro$% how the data were changed% how the data are

organi3ed% how the data are stored% who owns the data% who is responsible for the

data and how to contact the$% who can access the data % and the date of last update#

BUSINESS META DATA

Include what data are available% where the data are% what the data $ean% how to

access the data% predefined reports and ueries% and how current the data are#


16/21

O-AP'nline )nalytical rocessing - coined by 4& 2odd in 199

paper contracted by )rbor .oftware#

'nline analytical processing refers to such end user

activities as D.. $odelling using spreadsheets and

graphics that are done online#

'


17/21

O-AP IS 0ASMI

&).T

):)


18/21

BENE0ITS O0 DW

rovides business users with a "custo$er-centric view of the

co$pany*s 5eterogeneous data by helping to integrate data fro$

sales% service% $anufacturing and distribution% and other custo$er-

related Business syste$s#

rovides added value to the co$pany*s custo$ers by allowing the$

to access better infor$ation when Data (arehousing is coupled with

Internet technology#

2onsolidates data about individual custo$ers and provides arepository of all custo$er contacts for seg$entation $odeling%

custo$er retention planning% and cross sales analysis#

eports on trends across $ultidivisional% $ultinational operating

units% including trends or relationships in areas such as

$erchandising% production planning etc#


19/21

STRATE.I$ USE


20/21

-IMITATIONSData warehouses are not the opti$al environ$ent for

unstructured data#

'ver their life% data warehouses can have high Maintenance

costs#

Data warehouses can get outdated relatively uickly# There i

cost of delivering subopti$al infor$ation to the organi3ation

There is often a fine line between data warehouses andoperational syste$s# Duplicate% e/pensive functionality $ay

developed# 'r% functionality $ay be developed in the data

warehouse that% in retrospect% should have been developed in

the operational syste$s and vice versa#


21/21

THANKYOU

!!!

Documents

Presentation on DW