today lec 1-nov

8/8/2019 Today Lec 1-Nov

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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..


Using Databases to Improve Business Performance and Decision Making



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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


DATA WAREHOUSES



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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..


WHAT IS A DATA WAREHOUSE?



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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..


DATA MART



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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..


Business Intelligence, Multidimensional Data Analysis, And Data Mining



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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..


Online Analytical Processing (OLAP)



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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..





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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.


DATA MINING



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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.


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.


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.


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.


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.


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.


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


DATA MINING



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DECISION SUPPORT (DSS)



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DECISION SUPPORT (DSS)


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