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8.1 2003 by Prentice Hall
Business intelligence is a term commonly associated with data
warehousing. In fact, many of the tool vendors position their products as
business intelligence software rather than data warehousing software. There
are other occasions where the two terms are used interchangeably. So,
exactly what is business intelligence?
Business intelligence usually refers to the information that is available for
The enterprise to make decisions on. A data warehousing (or data mart)
system is the backend, or the infrastructural, component for achieving
business intelligence.
Business intelligence also includes the insight gained from doing data
Mining analysis, as well as unstructured data (thus the need of content
Management systems). For our purposes here, we will discuss businessintelligence in the context of using a data warehouse infrastructure. ()
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
BI, Data Warehousing & Mining ()
DATA WAREHOUSE (DWH) AND BUSINESS INTELLIGENCE
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BusinessesBusinesses useuse theirtheir databasedatabase toto keepkeep tracktrack ofof basicbasic transactions,transactions,
suchsuch asas payingpaying suppliers,suppliers, processingprocessing orders,orders, keepingkeeping tracktrack ofof
customers,customers, andand payingpaying employeesemployees.. ButBut theythey alsoalso needneed databasedatabase toto
provideprovide informationinformation thatthat willwill helphelp thethe companycompany runrun thethe businessbusiness
moremore efficiently,efficiently, andand helphelp managersmanagers andand employeesemployees makemake betterbetter
decisionsdecisions.. IfIf aa companycompany wantswants toto knowknow whichwhich productproduct isis thethe mostmost
popularpopular oror whowho itsits mostmost profitableprofitable customercustomer is,is, thethe answeranswer lieslies inin thethe
datadata.. InIn aa largelarge company,company, withwith largelarge databasesdatabases oror largelarge systemssystems forfor
separateseparate functions,functions, suchsuch asas manufacturing,manufacturing, sales,sales, andand accounting,accounting,specialspecial capabilitiescapabilities andand toolstools areare requiredrequired forfor analyzinganalyzing vastvast
quantitiesquantities ofof datadata andand forfor accessingaccessing datadata fromfrom multiplemultiple systemssystems..
TheseThese capabilitiescapabilities includeinclude datadata warehousing,warehousing, datadata mining,mining, andand toolstools
forfor accessingaccessing internalinternal databasesdatabases throughthrough thethe webweb..
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
Using Databases to Improve Business Performance and Decision Making
DATA WAREHOUSE (DWH) AND BUSINESS INTELLIGENCE
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8.3 2003 by Prentice Hall
SupposeSuppose youyou wantedwanted concise,concise, reliablereliable informationinformation aboutabout currentcurrent
operations,operations, trends,trends, andand changeschanges acrossacross thethe entireentire companycompany.. IfIf youyou
workedworked inin aa largelarge company,company, obtainingobtaining thisthis mightmight bebe difficultdifficult becausebecause
datadata areare oftenoften maintainedmaintained inin separateseparate systems,systems, suchsuch asas sales,sales,
manufacturing,manufacturing, oror accountingaccounting.. SomeSome ofof thethe datadata youyou neededneeded mightmight
bebe foundfound inin thethe salessales systemssystems andand otherother piecespieces inin thethe manufacturingmanufacturing
systemssystems.. ManyMany ofof thesethese systemssystems areare olderolder legacylegacy systemssystems thatthat useuse
outdatedoutdated datadata managementmanagement technologiestechnologies oror filefile systemssystems wherewhere
informationinformation isis difficultdifficult forfor usersusers toto accessaccess.. YouYou mightmight havehave toto spendspend
anan inordinateinordinate amountamount ofof timetime locationlocation andand gatheringgathering thethe datadata youyou
needed,needed, oror youyou wouldwould bebe forcedforced toto makemake youryour decisiondecision basedbased onon
incompleteincomplete knowledgeknowledge.. IfIf youyou wantedwanted informationinformation aboutabout trends,trends, youyou
mightmight alsoalso havehave troubletrouble findingfinding datadata aboutabout pastpast eventsevents becausebecause
mostmost firmsfirms onlyonly makemake theirtheir currentcurrent datadata immediatelyimmediately availableavailable.. DataData
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
DATA WAREHOUSES
DATA WAREHOUSE (DWH) AND BUSINESS INTELLIGENCE
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8.4 2003 by Prentice Hall
AA datadata warehousewarehouse isis aa databasedatabase thatthat storesstores currentcurrent andand historicalhistorical
datadata ofof potentialpotential interestinterest toto decisiondecision makersmakers throughoutthroughout thethe
companycompany.. TheThe datadata originateoriginate inin manymany corecore operationaloperational transactiontransaction
systems,systems, suchsuch asas systemssystems forfor sales,sales, customercustomer accounts,accounts, andand
manufacturing,manufacturing, andand manymany includeinclude datadata fromfrom webweb sitesite transactionstransactions..
TheThe datadata warehousewarehouse consolidatesconsolidates andand standardizesstandardizes informationinformation fromfrom
differentdifferent operationaloperational databasedatabase soso thatthat thethe informationinformation cancan bebe usedused
acrossacross thethe enterpriseenterprise forfor managementmanagement analysisanalysis andand decisiondecision
makingmaking.. TheThe datadata warehousewarehouse makesmakes thethe datadata availableavailable forfor anyoneanyone toto
accessaccess asas needed,needed, butbut itit cannotcannot bebe alteredaltered.. AA datadata warehousewarehouse
systemsystem alsoalso providesprovides aa rangerange ofof adad hochoc andand standardizedstandardized queryquerytools,tools, analyticalanalytical tools,tools, andand graphicalgraphical reportingreporting facilitiesfacilities.. ManyMany firmsfirms
useuse intranetintranet portalsportals toto makemake thethe datadata warehousewarehouse informationinformation widelywidely
availableavailable throughoutthroughout thethe firmfirm..
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
WHAT IS A DATA WAREHOUSE?
DATA WAREHOUSE (DWH) AND BUSINESS INTELLIGENCE
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CompaniesCompanies oftenoften buildbuild enterpriseenterprise--widewide datadata warehouses,warehouses,
wherewhere aa centralcentral datadata warehousewarehouse servesserves thethe entireentire
organization,organization, oror theythey createcreate smaller,smaller, decentralizeddecentralized
warehouseswarehouses calledcalled datadata martsmarts.. AA datadata martmart isis aa subsetsubset ofofaa datadata warehousewarehouse inin whichwhich aa summarizedsummarized oror highlyhighly
focusedfocused portionportion ofof thethe organizationsorganizations datadata isis placedplaced inin aa
separateseparate databasedatabase forfor aa specificspecific populationpopulation ofof usersusers.. ForFor
example,example, aa companycompany mightmight developdevelop marketingmarketing andand salessales
datadata martsmarts toto dealdeal withwith customercustomer informationinformation.. AA datadatamartmart typicallytypically focusesfocuses onon aa singlesingle subjectsubject areaarea oror lineline ofof
business,business, soso itit usuallyusually cancan bebe constructedconstructed moremore rapidlyrapidly
andand atat lowerlower costcost thanthan anan enterpriseenterprise--widewide datadata
warehousewarehouse..
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
DATA MART
DATA WAREHOUSE (DWH) AND BUSINESS INTELLIGENCE
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8.6 2003 by Prentice Hall
OnceOnce datadata havehave beenbeen capturedcaptured andand organizedorganized inin datadata warehousewarehouse andand
datadata marts,marts, theythey areare availableavailable forfor furtherfurther analysisanalysis.. AA seriesseries ofof toolstools
enablesenables usersusers toto analyzeanalyze thesethese datadata toto seesee newnew patterns,patterns,
relationships,relationships, andand insightsinsights thatthat areare usefuluseful forfor guidingguiding decisiondecision
makingmaking.. TheseThese toolstools forfor consolidating,consolidating, analyzing,analyzing, andand providingproviding
accessaccess toto vastvast amountsamounts ofof datadata toto helphelp usersusers makemake betterbetter businessbusinessdecisiondecision areare oftenoften referredreferred toto businessbusiness intelligenceintelligence (BI)(BI).. PrincipalPrincipal
toolstools forfor businessbusiness intelligenceintelligence includeinclude softwaresoftware forfor databasedatabase queryquery
andand reporting,reporting, toolstools forfor multidimensionalmultidimensional datadata analysisanalysis (online(online
analyticalanalytical processing),processing), andand datadata miningmining.. WhenWhen wewe thinkthink ofof
intelligenceintelligence asas appliedapplied toto humans,humans, wewe typicallytypically thinkthink ofof peoplespeoples
abilityability toto combinecombine learnedlearned knowledgeknowledge withwith newnew informationinformation andandchangechange behaviorsbehaviors inin suchsuch aa wayway thatthat theythey succeedsucceed atat theirtheir tasktask oror adaptadapt toto aa
newnew situationsituation.. Likewise,Likewise, businessbusiness intelligenceintelligence providesprovides firmsfirms withwith thethe
capabilitycapability toto aa massmass informationinformation:: developdevelop knowledgeknowledge aboutabout customers,customers,
competitors,competitors, andand internalinternal operationsoperations:: andand changechange decisiondecision--makingmaking behaviorbehavior
toto achieveachieve higherhigher profitabilityprofitability andand otherother businessbusiness goalsgoals..
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
Business Intelligence, Multidimensional Data Analysis, And Data Mining
DATA WAREHOUSE (DWH) AND BUSINESS INTELLIGENCE
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8.7 2003 by Prentice Hall
SupposeSuppose youryour companycompany sellssells fourfour differentdifferent productsproducts--nuts,nuts, bolts,bolts,
washers,washers, AndAnd screwsscrews-- inin thethe East,East, West,West, andand CentralCentral regionsregions.. IfIf youyou
wantedwanted toto askask aa fairlyfairly straightstraight forwardforward question,question, suchsuch asas howhow manymany
washerswashers soldsold duringduring thethe pastpast quarter,quarter, youyou couldcould easilyeasily findfind thethe
answeranswer byby queryingquerying youryour salessales databasedatabase.. butbut whatwhat ifif youyou wantedwanted toto
knowknow howhow manymany washerswashers soldsold inin eacheach ofof youryour salessales regionsregions andandcomparecompare actualactual resultsresults withwith projectedprojected sales?sales? ToTo obtainobtain thethe answer,answer,
youyou wouldwould needneed onlineonline analyticalanalytical processingprocessing (OLAP)(OLAP)..
OLAPOLAP supportssupports multidimensionalmultidimensional datadata analysis,analysis, enablingenabling usersusers toto
viewview thethe samesame datadata inin differentdifferent waysways usingusing multiplemultiple dimensionsdimensions..
EachEach aspectaspect ofof informationinformation--product,product, pricing,pricing, cost,cost, region,region, oror timetimeperiodperiod--representsrepresents aa differentdifferent dimensiondimension.. So,So, aa productproduct managermanager
couldcould useuse aa multidimensionalmultidimensional datadata analysisanalysis toolstools toto learnlearn howhow manymany
washerswashers werewere soldsold inin thethe EastEast inin June,June, howhow thatthat comparescompares withwith thethe
previousprevious monthmonth andand thethe previousprevious June,June, andand howhow itit comparescompares withwith
thethe salessales forecastforecast..
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
Online Analytical Processing (OLAP)
DATA WAREHOUSE (DWH) AND BUSINESS INTELLIGENCE
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OLAPOLAP enablesenables usersusers toto obtainobtain onlineonline answersanswers toto adad hochoc questionsquestions
suchsuch asas thesethese inin aa fairlyfairly rapidrapid amountamount ofof time,time, EvenEven whenwhen thethe datadata
areare storedstored inin veryvery largelarge database,database, suchsuch asas salessales figuresfigures forfor multiplemultiple
yearsyears.. AA multidimensionalmultidimensional modelmodel thatthat couldcould bebe createscreates toto representrepresent
products,products, regions,regions, actualactual sales,sales, andand projectedprojected salessales.. AA matrixmatrix ofof
actualactual salessales cancan bebe stackedstacked onon toptop ofof aa matrixmatrix ofof projectedprojected salessales toto
formform aa cubecube withwith bebe facesfaces.. IfIf youyou rotaterotate thethe cubecube 9090 degreesdegrees oneone
way,way, thethe faceface showingshowing willwill sixsix productsproducts versusversus actualactual andand projectedprojected
salessales.. IfIf youyou rotaterotate 180180 degreesdegrees fromfrom thethe regionalregional view,view, youyou willwill seesee
projectedprojected salessales andand productproduct versusversus regionregion.. CubesCubes cancan bebe nestednestedwithinwithin cubescubes toto buildbuild complexcomplex viewsviews ofof datadata.. aa companycompany wouldwould useuse
eithereither aa specializedspecialized multidimensionalmultidimensional databasedatabase oror aa toolstools thatthat
createscreates multidimensionalmultidimensional viewsviews ofof datadata inin relationalrelational databasesdatabases..
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
Online Analytical Processing (OLAP)
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Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
Online Analytical Processing (OLAP)
DATA WAREHOUSE (DWH) AND BUSINESS INTELLIGENCE
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Multidimensional Data Analysis
OnOn--line analytical processing (OLAP)line analytical processing (OLAP)
Multidimensional data analysisMultidimensional data analysis
Supports manipulation and analysis ofSupports manipulation and analysis of
large volumes of data from multiplelarge volumes of data from multiple
dimensions/perspectivesdimensions/perspectives
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 7 Managing Data ResourcesChapter 7 Managing Data Resources
DATABASE TRENDS
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Multidimensional Data Model
Figure 7-15
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 7 Managing Data ResourcesChapter 7 Managing Data Resources
DATABASE TRENDS
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OLAP, or multidimensional analysis, supports much moreOLAP, or multidimensional analysis, supports much morecomplex requests for information, such as, Compare sales ofcomplex requests for information, such as, Compare sales ofproducts 403 relative to plan by quarter and sales region for theproducts 403 relative to plan by quarter and sales region for thepast two years. With OLAP and querypast two years. With OLAP and query--oriented data analysis,oriented data analysis,
users need to have a good idea about the information for whichusers need to have a good idea about the information for whichthey are looking. Data mining is more discoveries driven. Datathey are looking. Data mining is more discoveries driven. Datamining provides insights into corporate data that cannot bemining provides insights into corporate data that cannot beobtained with OLAP by finding hidden patterns andobtained with OLAP by finding hidden patterns andrelationships in large databases and inferring rules from themrelationships in large databases and inferring rules from themto predict future behavior. The patterns and rules are used toto predict future behavior. The patterns and rules are used toguide decision making and forecast the effect of thoseguide decision making and forecast the effect of those
decisions.decisions. The types of information obtainable from data mining includeThe types of information obtainable from data mining includeassociations, sequences, classifications, clusters, andassociations, sequences, classifications, clusters, andforecasts.forecasts.
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
DATA MINING
DATA WAREHOUSE (DWH) AND BUSINESS INTELLIGENCE
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1)1) Associations:Associations:
Associations are occurrences liked to singleAssociations are occurrences liked to single
event. For instance, a study of supermarketevent. For instance, a study of supermarket
purchasing patterns might reveal that, whenpurchasing patterns might reveal that, when
corn chips are purchased, a cola drink iscorn chips are purchased, a cola drink is
purchased 65 percent of the time, but when therepurchased 65 percent of the time, but when there
is a promotion; cola is purchased 85 percent ofis a promotion; cola is purchased 85 percent ofthe time. This information helps managers makethe time. This information helps managers make
better decisions because they have learned thebetter decisions because they have learned the
profitability of a promotion.profitability of a promotion.
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
DATA MINING
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2)2) Sequence:Sequence:
In sequences, events are linked over time. WeIn sequences, events are linked over time. We
might find, for example, that if a house ismight find, for example, that if a house is
purchased, a new refrigerator will be purchasedpurchased, a new refrigerator will be purchased
within two weeks 65 percent of the time, and anwithin two weeks 65 percent of the time, and an
oven will be bought within one month of theoven will be bought within one month of the
home purchase 45 percent of the time.home purchase 45 percent of the time.
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
DATA MINING
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3)3) Classification:Classification:Classification recognizes patterns that describe theClassification recognizes patterns that describe the
group to which an item belongs by examining existinggroup to which an item belongs by examining existing
items that have been classified and by inferring a set ofitems that have been classified and by inferring a set ofrules. For example, business such as credit card orrules. For example, business such as credit card or
telephone companies worry about the loss of steadytelephone companies worry about the loss of steady
customers. Classification helps discover thecustomers. Classification helps discover the
characteristics of customers who are likely to leave andcharacteristics of customers who are likely to leave andcan provide a model to help managers predict who thosecan provide a model to help managers predict who those
customers are so that the managers can devise specialcustomers are so that the managers can devise special
campaigns to retain such customers.campaigns to retain such customers.
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
DATA MINING
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4)4) Clustering:Clustering: Clustering works in a manner similar to classificationClustering works in a manner similar to classification
when no groups have yet been defined. A datawhen no groups have yet been defined. A data
mining tool can discover different groupings withinmining tool can discover different groupings withindata, such as finding affinity groups for bank cardsdata, such as finding affinity groups for bank cardsor partitioning a database into groups of customersor partitioning a database into groups of customersbased on demographics and types of personalbased on demographics and types of personalinvestments.investments.
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
DATA MINING
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5)5) Forecasting:Forecasting: Although these applications involve predictions,Although these applications involve predictions,
forecasting uses predictions in a different way. Itforecasting uses predictions in a different way. It
uses a series of existing values to forecast whatuses a series of existing values to forecast whatother values will be. For example, forecasting mightother values will be. For example, forecasting mightfind patterns in data to help managers estimate thefind patterns in data to help managers estimate thefuture value of continuous variables, such as salesfuture value of continuous variables, such as salesfigures.figures.
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
DATA MINING
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Example:Example: For example, Virgin Mobile Australia uses a dataFor example, Virgin Mobile Australia uses a data
warehouse and data mining to increase customerwarehouse and data mining to increase customer
loyalty and roll out new services. The dataloyalty and roll out new services. The datawarehouse consolidates data from its enterprisewarehouse consolidates data from its enterprisesystem, customer relationship management system,system, customer relationship management system,and customer billing systems in a massive database.and customer billing systems in a massive database.Data mining has enable management to determineData mining has enable management to determinethe demographic profile of new customers and relatethe demographic profile of new customers and relate
it to the handsets they purchased. It has also helpedit to the handsets they purchased. It has also helpedmanagement evaluate the performance of each storemanagement evaluate the performance of each storeand pointand point--ofof--sale campaigns, consumer reactions tosale campaigns, consumer reactions tonew products and services, customer attrition rates,new products and services, customer attrition rates,and the revenue generated by each customer.and the revenue generated by each customer.
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
DATA MINING
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DSSDSS
Emphasizes change, flexibility, rapidEmphasizes change, flexibility, rapidresponse, models, assumptions, ad hocresponse, models, assumptions, ad hocqueries, and display graphicsqueries, and display graphics
Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
DATA MINING
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Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
DECISION SUPPORT (DSS)
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Essentials of Management Information SystemsEssentials of Management Information SystemsChapter 8 Telecommunications and NetworksChapter 8 Telecommunications and Networks
DECISION SUPPORT (DSS)
DATA WAREHOUSE (DWH) AND BUSINESS INTELLIGENCE