UsingSpatialAnalyticswithoutVisualisation
UseCase#1
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AlocalGovernmentOrganisationwantstoenableitscitizenstobeabletodiscoverwhatfacilitiesareneartheirproperty,suchaslibraries,publictransport,refusecollectiondayetc.andwhatishappeningnearthem,planningapplications,roadworksetc.Theywouldlikethispresentedasareportwitheverythinginoneplace.
UseCase#2
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Amotorinsurancecompanyhasacallcentrewhereitsclientscancallafteranaccident.Thecallcentrestafftakedetailsfromtheclientandprovidethegaragethatshouldhandleanyrepairs.
UseCase#3
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MortgageEvaluatorsareoftenchallengedtoaccuratelyassessthetruevalueofanewpropertytobemortgaged.Challengesarecomplexinassessinglocation,comparablesales,andpotentialrisk.Therecanbeanenormousamountofdatathatisrequiredtogiveatruereflectionofapropertiesvalue.
ProvidingALocationPerspectivetoData
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Organise
Analyse
Enrich
Cleanse
56 Via Po
Rome
Address:ViaPo5600198RomeRmItaly
GridReference(espg 4326)X:12.49717Y:41.91597
TouristAttractions:MausoleoDiLucilioPeto 102mVillaAlbani 271mIpogeoDiViaLivenza 309mViaSalaria 669mPortaPia 815m
PublicTransport:BusStopsPo-Simeto 75mPo-SimetoSouth 133mTartini 153mSalaria-Adda 161mSpontini 193m
ElectoralDivisionCameraCollegio: Roma-TriesteSenatoCollegio: RomaParioliTrieste
Banks:BancaMonteDeiPaschi 86mUnicreditSpa 224mUnicreditSpa 241mBancaIntermobiliare 248mIntensaSanpaoloSpa 279m
MetroStations:Metro-CastroPretorio 998m
ProvidingALocationPerspectivetoData
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Organise
Analyse
Enrich
Cleanse
Cleanse
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56ViaPo,Rome ViaPo5600198RomeRmItaly
ProvidingALocationPerspectivetoData
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Organise
Analyse
Enrich
Cleanse
Organise
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Street ViaPo
BuildingNumber 56
City Rome
Country Italy
Postalcode 00198
Region Rm
GridReference(espg 4326)X:12.49717Y:41.91597
ProvidingALocationPerspectivetoData
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Organise
Analyse
Enrich
Cleanse
Enrich
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GridReference(espg 4326)X:12.49717Y:41.91597
ElectoralDivisionCameraCollegio: Roma-TriesteSenatoCollegio: RomaParioliTrieste
ProvidingALocationPerspectivetoData
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Organise
Analyse
Enrich
Cleanse
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X:12.49717Y:41.91597
Analyse
UseCase#1Revisited
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AlocalGovernmentOrganisationwantstoenableitscitizenstobeabletodiscoverwhatfacilitiesareneartheirproperty,suchaslibraries,publictransport,refusecollectionetc.andwhatishappeningnearthem,planningapplications,roadworksetc.Theywouldlikethispresentedasareportwitheverythinginoneplace.
BasicallywhatwehavejustseenasimplewebformcompletedbytheuserinvokingadataflowusingAddressValidation,GeocodingandtheSpatialcapabilitiesofLIM.Providinganeasyselfserviceinformationportal.
Result:Aneasytouseselfserviceinformationportal.
UseCase#2Revisited
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Amotorinsurancecompanyhasacallcentrewhereitsclientscancallafteranaccident.Thecallcentrestafftakedetailsfromtheclientandprovidethegaragethatshouldhandleanyrepairs.
TheCallcentreoperatorwouldcaptureddatainascreenincludingthecustomersaddressandcarmake/model.Oncethedataisentereditwouldstartadataflowthatwouldvalidatetheaddressandgeocodeit.Thisgeocodewouldthenbecheckedagainstadatabaseofgaragewithinadefinedradiusoftheaddressthatcanhandlemake/modelofcar,meetspecificqualitycriteriaandarehighlyratedbyusers.
Result:Quickturnaroundoffindinganappropriategarage,reducedtrainingneedsforcallcentre.
BigData
PitneyBowes| 19December10,2018
SpectrumBigDataComponentsSupportMapReduce,HiveUDFandSpark-basedimplementations.
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SpectrumTM forBigDataEnablingbigdataframeworkswithdataqualityandgeospatialtechnologywithcoreSDKs
AdvancedMatching
UniversalAddressing
DataNormalization
UniversalName
GlobalGeocoding
LocationIntelligence
EnterpriseRouting
Geo-enrichmentModule
SpectrumSpatialforBigDataSpectrumDataQualityforBigData
SpectrumSpatialModulesforBigDataSupportMapReduce,HiveUDFandSpark-basedimplementations.
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Module Features
SpectrumGeocoding for Big Data
• Global forward geocoding• Global reverse geocoding• 145 countries at street
level of better• 245 total countries
supported at variety of accuracy levels
SpectrumLocationIntelligence for Big Data
• Find the nearest• Point and polygon• Spatial join• Distance to point, shape,
line
Spectrum Routing for Big Data
• Global route generation,isochrones, isodistance
• Walk time/drive time• Point-to-point
calculations
SpectrumTM forBigDataEnablingbigdataframeworkswithdataqualityandgeospatialtechnology
AdvancedMatching
UniversalAddress-ing
DataNormaliz-ation
UniversalName
GlobalGeo-coding
LocationIntelligence
EnterpriseRouting
Geo-enrichmentModule
SpectrumSpatialforBigData
SpectrumSpatialModulesforBigDataSupportMapReduce,HiveUDFandSpark-basedimplementations.
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Module Features
SpectrumAddress Matching
• Match key generator• Interflow/intraflow
match• Transactional match• Best of breed• Duplicate
synchronization
Spectrum Data Normalization
• Table lookup• Advance transformer• Open parser
Spectrum Universal Name
• Global name parser • Name/nickname/alias
dictionary
Spectrum Universal Addressing
• Global addressing support for 240 countries
SpectrumTM forBigDataEnablingbigdataframeworkswithdataqualityandgeospatialtechnology
AdvancedMatching
UniversalAddressing
DataNormalization
UniversalName
GlobalGeo-coding
LocationIntelligence
EnterpriseRouting
Geo-enrichmentModule
SpectrumDataQualityforBigData
UseCase#3Revisited
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MortgageEvaluatorsareoftenchallengedtoaccuratelyassessthetruevalueofanewpropertytobemortgaged.Challengesarecomplexinassessinglocation,comparablesales,andpotentialrisk.Therecanbeanenormousamountofdatathatisrequiredtogiveatruereflectionofapropertiesvalue.
PBprovidesamassive,indexeddatastore,storednativelyinHadoopthatcontainsover7,000attributesabouteverypropertyintheUnitedStates.That’s875Billionattributes.Additionally,weprovidenativetoHadoopprocessestoappendothersourcesofpropertyattributedataintoourdatastoretocreateadeepandrichviewofeverypropertyintheUnitedStates.Weproviderobustquerycapabilitiestooperationalizethedatastoreintomanypartsofthemortgageprocess.Result:ByprovidingdeeperunderstandingofthetruevalueofeverypropertyintheUnitedStates,weenablemortgageoriginatorstomoreaccuratelyassessthetruevalueofanypropertythattheyunderwrite.Bydeliveringrobustqueryingtoolslinkedtoourpropertydatastore,weenableourclientstoleverageacommonsourceofdeeptruthaboutthemortgagescarriedbyourFinancialServicesclients.
Data
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Choose from a robust selection of global datasets to further enrich your Big Data discoveries.