Tracking the Back-steps of BI Evolution
- 1. LookingInsideThe ‘Intelligent’Matter Comprisingmyriadsoffunctions–somecommon, somecustomisedtobusinessneeds,BIisthepandora boxofmultipletechnologyfunctionscomingtogether toprovideanenhanceddataexperience. EvolutionofDefinition FirsteverdefinitionofBI:Theprocessofgathering informationforsucceedinginbusiness. PPresentdaydefinition:Asetofmethodologies,processes, architectures,andtechnologiesthattransformrawdatainto meaningfulandusefulinformationwhichenablesmore effectivestrategic,tactical,andoperationalinsightsand decision-making. ALowdownonSomeTerminologies DataDiscovery:Atermusedtodescribetheactofdiscoveringopportunitiesthatarehiddeninthedata heldincompanybusinesssystems. DataMining:Theprocessofanalysinglargebatchesofdatatofindpatternsandinstancesofstatistical significance. DataDataWarehouse:Alargestoreofdataaccumulatedfromawiderangeofsourceswithinacompanyand usedtoguidemanagementdecisions. DataMart:Asubsetoraccesslayerofadatawarehousethatisusedtoprovideuserswithdata. Dashboard:Agraphicalsummaryofvariouspiecesofimportantinformation,typicallyusedtogivean overviewofabusiness. DataLakes:Astoragerepositorythatholdsavastamountofrawdatainitsnativeformatuntilitis needed. EETL:ItstandsforExtract,TransformandLoad. ‘Extract’functionreadsdatafromaspecifiedsourcedatabaseandextractsadesiredsubsetofdata. ‘Transform’functionworkswiththeacquireddata–usingrulesorlookuptablesorcreating combinationswithotherdata–toconvertittothedesiredstate. ‘Load’functionisusedtowritetheresultingdata(eitherallthesubsetorjustthechanges)toatarget database,whichmayormaynotpreviouslyexist. OOLAP:OnlineAnalyticalProcessingiscomputerprocessingthatenablesausertoeasilyandselectively extractandviewdatafromdifferentpointsofview. OLTP:OnlineTransactionProcessingisaclassofsoftwareprogramscapableofsupporting transaction-orientedapplicationsontheinternet. ODBC:OpenDatabaseConnectivityisanopenstandardapplicationprogramminginterface(API)for accessingadatabase. SomeCommonFunctionsofBI BusinessPerformanceManagement Benchmarking TextMining PredictiveAnalytics PrescriptiveAnalytics Reporting OnlineAnalyticalProcessing Analytics DataMining ProcessMining ComplexEventProcessing DataEngineersareworkingforimprovingtheelementsofcontextualinsights–embedded, suggestiveBI,andcognitivecomputing;actionableinsights,andestablishingacontinuousfeedback loopforimprovement. HowItAllStarted… Englishsocialreformerandstatistician,FlorenceNightingale pioneeredtheuseofappliedstatisticsandcreatedvisualways ofdisplayingdataaroundthecauseofmortalityinthearmyin theEast. 1855 Businessescontinuedcollectinginformationabouttheir businessenvironment,marketconditions,competitors etc.onpapers. Early 1900 Computerscameintoexistencein1940sandIBM came upwithfirstharddrivein1956–anew,though tedious-to-managemediumtostoredata. Mid 1900 TheEurekaMoment-HansPeterLuhn,acomputerscientist atIBM pennedanarticleentitled,“ABusinessIntelligence System”whereinhedescribedtheaspectsofBIpotential. HewaslatertermedastheFatherofBI. 1958 LeverageofdatabaseproductsgotamajorupliftwithScientist EdgarCoddpublishingapaperon“RelationalDatabase Model”.Thefirstdatabasemanagementsystemcreatedwas knownasDSS,orDecisionSupportSystem. 1970s ScientistBillInmonandauthor/techarchitectRalphKimbal broughtintheageofstructureddatastorageintheformofdata warehouses.FoundationalterminologiesofBI,Extract,Transform, Load(ETL)andOLAP(OnlineAnalyticalProcessing)tookshape. 1980s Theterm‘businessintelligence’or‘BI’wasdevisedbyindustry analystHowardDresnerin1989. 1989 Thiswasaneraoflesseningcomplexityandcompletereliance onITforBIoperations.Attemptsweremadetosimplifythe reportingandinsightsvisualisationprocess. 1990s Thiswasaneraofcompetitiveandexponentialupgradesand hence,ofBI2.0.Real-timedataprocessingforinsightgeneration andprovisionofdataaccesswasexpandedbeyondITpurview. TheshiftfromIT-ledtoIT-enabledstartedtakingshape. Early 2000 Withbigdatagettingbiggerandbigger,emergenceofcloud applicationsmanagedthecomplexitywhichwouldhave otherwiseimpairedBIfunctionalities.Journeytowardsrealising aself-servicemodelforBIisnowinprogress. 2005- Now Thelistislongandwillbevariedfor differentbusinessesdependingupon theindustrysegment,scope,etc. ALookatThe BurgeoningBIImpact • Betterplanningfortargetedmarketingcampaigns • Impactanalysisofexistingcampaigns • Improvedtrialconfigurationfacilitatinginnovation • Easyspottingofbottlenecks • Regularinsightsintochangingconsumerpreferences •• Betteroperationalefficiency • Anedgeovercompetition • Revenueenhancementwithstrategicinsights • Real-timeintelligenceforinformeddecision-making TheDriversofChange • Collaborative/CooperativeBI • EstablishmentofData-DrivenCulture • EmbeddedAnalyticsinBI • PredictiveAnalyticsBI • CloudBI MarketPredictions Self-ServiceAnalyticsandBIuserswillproducemore analysisthandatascientistswill,by2019.1 75%ofprebuiltreportswillbereplacedwithoraugmented byautomatedinsightsdeliveredona‘mostneeded’basisby theyear2021.2 GlobalBusinessIntelligence(BI)marketisexpectedtoreachGlobalBusinessIntelligence(BI)marketisexpectedtoreach $29.48billionby2022withaCAGRof11.1%.3 90%ofbusinessintelligenceplatformswillfeature natural-languagegenerationandartificialintelligenceby 2020.4 UnstructuredDatasegmentisexpectedtodominatetheUnstructuredDatasegmentisexpectedtodominatethe globalbusinessintelligencemarketwithhigherCAGRowing toincreasingadoptionofdataanalyticsandgrowingmarket forIoTdevices.3 Thenewestdisruptioninthemarketisaugmentedanalytics (AA)drivenbyartificialintelligence(AI).5 TheFuture Kaleidoscope ThenextlevelisallaboutdemocratizingBIandmakingit moreaccessibleandsimplertounderstandevenforpeople withlimitedtonotechnicalorstatisticalknowledge. EnhancementsintheEnhancementsinthedataqualitywiththeprovisionof bringingdatatogetherfromdisparateapplicationsordata silosandcompilingitinausablesystemwithoutaffecting thevalidityoftheoriginalsourcedata. Advancementsinmachinelearninganddataanalysisare enablingthisprocessofcreatingSelf-ServiceBusiness Intelligence(SSBI). AIAIwillreducetheinterface-learningbarrierandprovision moreopenaccesstotechnologyandinsightsevenby non-technicalusers. TheBIandanalyticsmarketisinthe finalstagesofamultiyearshiftfrom IT-led,system-of-recordreportingto business-led,self-serviceanalytics. Asaresult,themodernbusiness intelligenceandanalytics(BI&A) platformhasemergedtomeetnew organizationalrequirementsfororganizationalrequirementsfor accessibility,agilityanddeeper analyticalinsight.6 Sources https://www.gartner.com/en/newsroom/press-releases/2018-01-25-gartner-says-self-service-analytics-an d-bi-users-will-produce-more-analysis-than-data-scientists-will-by-2019 https://www.gartner.com/doc/reprints?id=1-4UCCMN1&ct=180329&st=sb https://www.reuters.com/brandfeatures/venture-capital/article?id=5619 https://www.gartner.com/doc/3611117/magic-quadrant-business-intelligence-analytics https://www.betterbuys.com/bi/7-business-intelligence-software-market-trends/https://www.betterbuys.com/bi/7-business-intelligence-software-market-trends/ https://www.datameer.com/blog/gartner-validates-evolution-of-business-intelligence-and-analytics/ TRACINGBACKTHESTEPSOF BIEVOLUTIONThejourneyfrom datatoactionableinsights