Data Warehousing and Data Mining for Telecommunications (Artech House Computer Science Library)

283 Pages·1997·2.21 MB·English

by  Rob Mattison

Data Warehousing and
Data Mining for
Telecommunications
Chapter7 Screenshotsreprintedwithpermissionfrom MicrosoftCorporation,One Mi-
crosoftWay,Redmond, WA98052-6399
Chapter8 Screenshotsof PowerPlayreprintedwithpermissionfrom Cognos Corpora-
tion,OneBurlington BusinessCenter,67So.Bedford Street,Suite200W,Burlington,
MA01803-5164,Tel:[phone],http://www.cognos.com
Chapter9 Screenshotsreprintedwithpermissionfrom SPSS Inc.,444N. Michigan
Avenue,Chicago,IL60611-3962,Tel:[phone],Fax:[phone],
http://www.spss.com
Chapter10 Screenshotsof ModelMAX reprintedwithpermission from AdvancedSoft-
wareApplications. ModelMAX isaregisteredtrademarkof AdvancedSoftware Applica-
tions,333BaldwinRoad, Pittsburgh,PA15205,Tel: [phone],Fax:
412-429-0709,e-mail:[email protected]
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©1985–1997MapInfoCorporation. Allrightsreserved.MapMarkerisaregisteredtrade-
markandMapInfoProfessional andStreetWorksaretrademarksofMapInfo Corpora-
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AppendixA Screenshotsreprintedwithpermission from CNET-FranceTelecom and
SLP InfoWare Inc.
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Data Warehousing and
Data Mining for
Telecommunications
Rob Mattison
Artech House
Boston • London
Libraryof CongressCataloging-in-Publication Data
Mattison, Rob.
Data warehousinganddataminingfor telecommunications/Rob Mattison.
p. cm.—(Artech ComputerScienceLibrary)
Includesbibliographicalreferencesandindex.
ISBN0-89006-952-2(alk. paper)
1. Telecommunications—Management. 2.DatabaseManagement. 3.Data
mining I.Title. II.Series
HE7661.M38 1997
384’.0285’574—dc21 97-22863
CIP
British LibraryCataloguingin PublicationData
Mattison, Rob M.
Data warehousingand dataminingfor telecommunications—(Artech Computer
ScienceLibrary)
1.Decision supportsystems 2.Telecommunications 3.Digitalcommunications
I.Title
384’.0285
ISBN0-89006-952-2
CoverandtextdesignbyDarrell Judd.Illustrationsby BrigitteKilger-Mattison.
CoverimagesfromSeagate SoftwareandSLP InfoWare.
© 1997ARTECH HOUSE,INC.
685 Canton Street
Norwood, MA02062
Allrightsreserved. Printedandbound intheUnitedStatesof America.Nopartof this
book maybereproducedor utilizedinany form or byany means,electronic or mechani-
cal,includingphotocopying,recording,orbyanyinformation storageand retrievalsys-
tem,withoutpermission inwriting from thepublisher.
Alltermsmentionedinthisbook thatareknown to betrademarksor servicemarkshave
beenappropriatelycapitalized.ArtechHouse cannot attestto theaccuracyof thisinforma-
tion.Useof aterminthisbook shouldnotberegardedasaffecting thevalidityof any
trademarkor servicemark.
InternationalStandardBookNumber: 0-89006-952-2
LibraryofCongressCatalog CardNumber:97-22863
10987654321
I would like to dedicate thisbookto my darlinggrandchildren,
JonathanYesulis,RaquelKuykendall,andAnthonyandNicoleCirrincione,
and to allof theotherchildrenwhowillbe leftto pick upthepieces
afterwemoveon.
Contents
Foreword xiii 1.6 Future directions 8
1.7 Telecommunicationsand
technologicalinnovation 9
Preface xvii
1.7.1 Peg counts 9
1.7.2 Business drives technological
innovation 9
Chapter 1
1.8 The threestrategicoptions 10
Everything’supto date in
1.9 Customerintimacy—from“network
KansasCity 1
isking”to “customer isking” 10
1.1 The currentindustrycomposition 3 1.9.1 Marketingas the drivingforce 11
1.2 Whyistelecommunicationsso 1.10 Operational efficiency—beingthe
BIG? 4 low-costproviderof choice 11
1.3 Telecommunications:themajor 1.11 Technicalproficiency—beingthe
drivingeconomic forceof the21st bestatwhatyou do 12
century 5
1.12 Conclusion 12
1.4 Knowledge managementenablement—
thebiggestfactorof all 6
Chapter 2
1.5 The ultimateenvironment 7
1.5.1 Failedexcursionsintothe Whywarehousingand
new frontiers 7 how to get started 13
vii
viii Data WarehousingandDataMiningforTelecommunications
2.1 Background of datawarehousing 14 3.1.1 Knowledgemanagement
2.1.1 Thehistoryofthe data principles 27
warehousing phenomenon 14 3.1.2 Theorganizational footprintand
2.1.2 Data warehousing—in a whatittells usaboutknowledge
nutshell 16 transformationprocesses 29
2.1.3 Whatis a datawarehouse? 17
3.2 Efficiencyoptimization—optimize
2.2 Datamining 18 thesilo or optimizethewhole 32
2.2.1 Whyshould oneseriouslyconsider 3.2.1 Whichtypeofwarehouseisbetter,
using theseapproaches? 20 or which is the right one? 34
3.2.2 Thewarehouse alternative 37
2.3 Whyaretheseapproachesso
3.2.3 A third alternative 37
exceptionallyvaluableto
telecommunicationsfirms? 20 3.3 The corporate globalwarehouse
2.3.1 Data intensity 20 model 38
2.3.2 Analysis dependency 21 3.3.1 Developinga trulyusable global
2.3.3 Competitive climate 21 architecturemodel 40
2.3.4 Technologicalchange at a very 3.3.2 An alternative foundation:
highrate 21 the valuechain 42
2.3.5 Historicalprecedent 22 3.3.3 Thekeytovaluechain
delivery 45
2.4 Organizingtheprocess 22
2.4.1 Aninventoryofthe existing 3.4 Overallstrategyfor development
computer systemsandother (one pieceatatime,fitting intothe
technologicalinfrastructure 22 overallarchitecture) 45
2.4.2 A roadmapand an approachfor 3.4.1 Thegrowing warehouse
how todeploy data warehouses example 47
in general 23 3.4.2 Ownership ofknowledge
2.4.3 A roadmapforunderstandinghow issues 49
todiagnose anddevelop a plan for
identifyingthe bestthings toput
Chapter 4
intothe warehouse and which data
mining toolstouse 23 The telecommunications
valuechain 51
4.1 The knowledgeroadmap
Chapter 3
solution 52
Theknowledge management viewof
4.2 Stepsintheprocessof deriving a
businessandwarehousing 25
business’valuechain 52
3.1 The knowledgemanagement 4.3 Telecommunicationsfunctions
revolution 26 and systems 53
Contents ix
4.3.1 Creation (newproduct develop- 4.5.1 Aligningthevaluechain and
mentand exploitation) 54 the organization—large
4.3.2 Acquisition(acquiringthe “right” megacorporation 68
todobusiness) 54 4.5.2 Aligningthevaluechain with the
4.3.3 Networkinfrastructureplanning informationsystems 71
and development(creatingthe 4.5.3 Kingpin systems:the beginningof
“phone system”) 55 computersystemsalignment 72
4.3.4 Networkinfrastructure 4.5.4 Alignment problemsand their
maintenance(maintaining the symptoms 74
“phone system”) 56 4.5.5 Datawarehousing as an
4.3.5 Provisioning (settingup customer alternative 76
services) 57 4.5.6 Datawarehousing as a migration
4.3.6 Activation(activatingcustomer path 77
services) 57 4.5.7 Thefully aligned model—
4.3.7 Service orderprocessing 58 a summary 77
4.3.8 Billing (tracking serviceand
invoicing thecustomer) 58
Chapter 5
4.3.9 Marketing(identifyingprospects/
channels,advertising) 59 Building the warehouse—
4.3.10 Customerservice(keepingthe one step ata time 79
customer happy) 59 5.1 Challengestoinfrastructure
4.3.11 Sales (establishingandmaintaining design 80
customer relationships) 61
5.2 The functional componentsof a
4.3.12 Financeand accounting 61 warehouse environment 84
4.3.13 Credit management 61
5.2.1 Acquisition 85
4.3.14 Operations (networkand
5.2.2 Storage 87
business) 62
5.2.3 Access 88
4.3.15 A comprehensivevaluechain 62
5.2.4 Theoperational
4.4 Organizational structureand the infrastructure 89
valuechain 63 5.2.5 Thephysical infrastructure 89
4.4.1 Typical organizational structure:
5.3 The step-by-step, cost-justified
medium-sized cellular firm 64 approach 89
4.4.2 Typical organizational structure:
5.3.1 Whatis a valueproposition? 90
large telecommunications
5.3.2 Gatheringvalue propositions 90
firms 66
5.4 Howdoyoubuilda warehouse? 92
4.5 Allocatingthebusinessunitsto the
valuechainand theknowledge
managementprocess 66
x DataWarehousingandDataMiningforTelecommunications
Chapter 6 7.1 Operational efficiency—an
overview 109
Valuepropositions in
7.2 Salesmonitoringandcontrol 110
telecommunications 95
7.3 Auniversalproblem 111
6.1 Miningtoolsandvaluedelivery 96
7.4 UsingMicrosoftQueryandExcelto
6.1.1 Operationalmonitoring and
do salestracking 111
control 96
7.4.1 Thesales database 112
6.1.2 Discoveryand exploration 97
7.5 Managing morecomplicated
6.2 Value propositions byfunctional
needs 115
area 98
7.6 Alternativemethodsof
6.2.1 Marketingvaluepropositions
accessingdata 115
(historical/cross-silo/
discovery) 99
6.2.2 Credit valuepropositions 99 Chapter 8
6.2.3 Customerservicevalue
Salesand productmanagement:
propositions—(real-timeand
advanced operationalmonitoring
historical/cross-silo/
usingCOGNOSPowerPlay 117
operationalmonitoring) 100
8.1 Monitoring complexbusiness
6.2.4 Sales valuepropositions 101
organizations 118
6.2.5 Networkplanningvalue
8.1.1 Determining the differentlevelsat
propositions 101
whichtoreport 119
6.2.6 Networkmaintenance value
8.1.2 Preparing the data foruse 121
propositions 103
6.2.7 Creation 103 8.2 Exploringsalesandproduct
6.2.8 Activationandprovisioning and performance 121
serviceorderprocessing 104 8.3 Additional PowerPlayfeatures 124
6.2.9 Billing (historical/single-silo/ 8.3.1 Alerts 125
discoveryand monitoring) 104 8.3.2 Schedulers 126
6.2.10 Operations 104
8.4 Summary 127
6.3 Conclusions 105
6.3.1 Knowledge management
Chapter 9
approach 105
Customer intimacy:
an introduction usingSPSS 129
Chapter 7
9.1 An introduction to analytical
Simplesalesanalysis: mining 130
anintroduction to operational moni-
9.2 Statisticalanalysis—optionsand
toring usingMicrosoftQuery 107
objectives 131
9.3 Descriptiveapproaches 133