What is Data Analytics? - Definition from WhatIs.com
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Data analytics (DA) is the process of examining data sets in order to find trends and draw conclusions about the information they contain. Home DataIntegration MarketingandCX dataanalytics(DA) Sharethisitemwithyournetwork: By CraigStedman, IndustryEditor Dataanalytics(DA)istheprocessofexaminingdatasetsinordertofindtrendsanddrawconclusionsabouttheinformationtheycontain.Increasingly,dataanalyticsisdonewiththeaidofspecializedsystemsandsoftware.Dataanalyticstechnologiesandtechniquesarewidelyusedincommercialindustriestoenableorganizationstomakemore-informedbusinessdecisions.Scientistsandresearchersalsouseanalyticstoolstoverifyordisprovescientificmodels,theoriesandhypotheses. Asaterm,dataanalyticspredominantlyreferstoanassortmentofapplications,frombasicbusinessintelligence(BI),reportingandonlineanalyticalprocessing(OLAP)tovariousformsofadvancedanalytics.Inthatsense,it'ssimilarinnaturetobusinessanalytics,anotherumbrellatermforapproachestoanalyzingdata.Thedifferenceisthatthelatterisorientedtobusinessuses,whiledataanalyticshasabroaderfocus.Theexpansiveviewofthetermisn'tuniversal,though:Insomecases,peopleusedataanalyticsspecificallytomeanadvancedanalytics,treatingBIasaseparatecategory. Dataanalyticsinitiativescanhelpbusinessesincreaserevenue,improveoperationalefficiency,optimizemarketingcampaignsandbolstercustomerserviceefforts.Analyticsalsoenableorganizationstorespondquicklytoemergingmarkettrendsandgainacompetitiveedgeoverbusinessrivals.Theultimategoalofdataanalytics,however,isboostingbusinessperformance.Dependingontheparticularapplication,thedatathat'sanalyzedcanconsistofeitherhistoricalrecordsornewinformationthathasbeenprocessedforreal-timeanalytics.Inaddition,itcancomefromamixofinternalsystemsandexternaldatasources. Typesofdataanalyticsapplications Atahighlevel,dataanalyticsmethodologiesincludeexploratorydataanalysis(EDA)andconfirmatorydataanalysis(CDA).EDAaimstofindpatternsandrelationshipsindata,whileCDAappliesstatisticaltechniquestodeterminewhetherhypothesesaboutadatasetaretrueorfalse.EDAisoftencomparedtodetectivework,whileCDAisakintotheworkofajudgeorjuryduringacourttrial--adistinctionfirstdrawnbystatisticianJohnW.Tukeyinhis1977bookExploratoryDataAnalysis. Dataanalyticscanalsobeseparatedintoquantitativedataanalysisandqualitativedataanalysis.Theformerinvolvestheanalysisofnumericaldatawithquantifiablevariables.Thesevariablescanbecomparedormeasuredstatistically.Thequalitativeapproachismoreinterpretive--itfocusesonunderstandingthecontentofnon-numericaldataliketext,images,audioandvideo,aswellascommonphrases,themesandpointsofview. Attheapplicationlevel,BIandreportingprovidebusinessexecutivesandcorporateworkerswithactionableinformationaboutkeyperformanceindicators,businessoperations,customersandmore.Inthepast,dataqueriesandreportstypicallywerecreatedforendusersbyBIdeveloperswhoworkedinIT.Now,moreorganizationsuseself-serviceBItoolsthatletexecutives,businessanalystsandoperationalworkersruntheirownadhocqueriesandbuildreportsthemselves. Advancedtypesofdataanalyticsincludedatamining,whichinvolvessortingthroughlargedatasetstoidentifytrends,patternsandrelationships.Anotherispredictiveanalytics,whichseekstopredictcustomerbehavior,equipmentfailuresandotherfuturebusinessscenariosandevents.Machinelearningcanalsobeusedfordataanalytics,byrunningautomatedalgorithmstochurnthroughdatasetsmorequicklythandatascientistscandoviaconventionalanalyticalmodeling.Bigdataanalyticsappliesdatamining,predictiveanalyticsandmachinelearningtoolstodatasetsthatcanincludeamixofstructured,unstructuredandsemistructureddata.Textminingprovidesameansofanalyzingdocuments,emailsandothertext-basedcontent. Dataanalyticsinitiativessupportawidevarietyofbusinessuses.Forexample,banksandcreditcardcompaniesanalyzewithdrawalandspendingpatternstopreventfraudandidentitytheft.E-commercecompaniesandmarketingservicesprovidersuseclickstreamanalysistoidentifywebsitevisitorswhoarelikelytobuyaparticularproductorservice--basedonnavigationandpage-viewingpatterns.Healthcareorganizationsminepatientdatatoevaluatetheeffectivenessoftreatmentsforcancerandotherdiseases. Mobilenetworkoperatorsexaminecustomerdatatoforecastchurn;thatenablesthemtotakestepstopreventcustomersfromdefectingtorivalvendors.Toboostcustomerrelationshipmanagementefforts,companiesengageinCRManalyticstosegmentcustomersformarketingcampaignsandequipcallcenterworkerswithup-to-dateinformationaboutcallers. Insidethedataanalyticsprocess Dataanalyticsapplicationsinvolvemorethanjustanalyzingdata,particularlyonadvancedanalyticsprojects.Muchoftherequiredworktakesplaceupfront,incollecting,integratingandpreparingdataandthendeveloping,testingandrevisinganalyticalmodelstoensurethattheyproduceaccurateresults.Inadditiontodatascientistsandotherdataanalysts,analyticsteamsoftenincludedataengineers,whocreatedatapipelinesandhelppreparedatasetsforanalysis. Theanalyticsprocessstartswithdatacollection.Datascientistsidentifytheinformationtheyneedforaparticularanalyticsapplication,andthenworkontheirownorwithdataengineersandtheITstafftoassembleitforuse.Datafromdifferentsourcesystemsmayneedtobecombinedviadataintegrationroutines,transformedintoacommonformatandloadedintoananalyticssystem,suchasaHadoopcluster,NoSQLdatabaseordatawarehouse. Inothercases,thecollectionprocessmayconsistofpullingarelevantsubsetoutofastreamofdatathatflowsinto,forexample,Hadoop.Thedataisthenmovedtoaseparatepartitioninthesystemsoitcanbeanalyzedwithoutaffectingtheoveralldataset. Oncethedatathat'sneededisinplace,thenextstepistofindandfixdataqualityproblemsthatcouldaffecttheaccuracyofanalyticsapplications.Thatincludesrunningdataprofilinganddatacleansingtaskstoensuretheinformationinadatasetisconsistentandthaterrorsandduplicateentriesareeliminated.Additionaldatapreparationworkisdonetomanipulateandorganizethedatafortheplannedanalyticsuse.Datagovernancepoliciesarethenappliedtoensurethatthedatafollowscorporatestandardsandisbeingusedproperly. Fromhere,adatascientistbuildsananalyticalmodel,usingpredictivemodelingtoolsorotheranalyticssoftwareandprogramminglanguagessuchasPython,Scala,RandSQL.Typically,themodelisinitiallyrunagainstapartialdatasettotestitsaccuracy;it'sthenrevisedandtestedagainasneeded.Thisprocessisknownas"training"themodeluntilitfunctionsasintended.Finally,themodelisruninproductionmodeagainstthefulldataset,somethingthatcanbedoneoncetoaddressaspecificinformationneedoronanongoingbasisasthedataisupdated. Insomecases,analyticsapplicationscanbesettoautomaticallytriggerbusinessactions.Anexampleisstocktradesbyafinancialservicesfirm.Otherwise,thelaststepinthedataanalyticsprocessiscommunicatingtheresultsgeneratedbyanalyticalmodelstobusinessexecutivesandotherendusers.Chartsandotherinfographicscanbedesignedtomakefindingseasiertounderstand.DatavisualizationsoftenareincorporatedintoBIdashboardapplicationsthatdisplaydataonasinglescreenandcanbeupdatedinrealtimeasnewinformationbecomesavailable. Dataanalyticsvs.datascience Asautomationgrows,datascientistswillfocusmoreonbusinessneeds,strategicoversightanddeeplearning.Dataanalystswhoworkinbusinessintelligencewillfocusmoreonmodelcreationandotherroutinetasks.Ingeneral,datascientistsconcentrateeffortsonproducingbroadinsights,whiledataanalystsfocusonansweringspecificquestions.Intermsoftechnicalskills,futuredatascientistswillneedtofocusmoreonthemachinelearningoperationsprocess,alsocalledMLOps. ThiswaslastupdatedinSeptember2020 ContinueReadingAboutdataanalytics(DA) Ultimateguidetobusinessintelligenceintheenterprise Thedatascienceprocess:6keystepsonanalyticsapplications Buildingastrongdataanalyticsplatformarchitecture 6topbusinessbenefitsofreal-timedataanalytics RelatedTerms datapoint Adatapointisadiscreteunitofinformation.Inageneralsense,anysinglefactisadatapoint.Thetermdatapointis... See complete definition GPScoordinates GPScoordinatesareauniqueidentifierofaprecisegeographiclocationontheearth,usuallyexpressedinalphanumeric... 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