The document traces the evolution of business intelligence (BI) from its origins in the 1850s to current and future developments. Some key points: - BI first involved collecting business data by hand, with early computerized systems emerging in the 1940s-50s. The term "business intelligence" was coined in 1989. - Modern BI is defined as a set of processes and technologies that transform raw data into useful information to enable effective decision-making. - Current areas of focus include self-service analytics, predictive analytics, cloud BI, and making BI more accessible to non-technical users through advances in machine learning and artificial intelligence.

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