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WaysOfStructuringTheUnstructuredData • TableofContents • OverviewonUNSTRUCTUREDDATA • Examplesshowingchallengesinanalyzingunstructureddata: • ApproachforDATAANALYSIS: • ContentAnalysis: • SentimentAnalysis: • FrameAnalysis: • DiscourseAnalysis: • VisualContentAnalysis: • Conclusion: OverviewonUNSTRUCTUREDDATA Oneofthebiggestchallengesasadataanalysttodayisanalyzingand structuringBigData.Asweknowabout80%ofBigDataisunstructured. Whenwesayunstructureddata,itmeansdatathatcannotbeeasilyformatted tobestoredinatablelikeSQLoranExcelsheet. Someexamplesofunstructureddataareimages,audio,video,andtext messagespostedonsocialmedia.Everyday,1000tera bytesofdatais stored onlinefromaroundtheworld. Forexample,approximately500terabytesofdataaresubmittedadayto Facebookalone.
Examplesshowingchallengesinanalyzing unstructureddata: • Thisdataisverylargeandevenifweconsideronlytextualdata,itisvery difficulttoanalyze,becauseasentenceexpressedbyapersoncanhave differentmeaningsdependingonthecircumstances. • Let'slookatsomeexamples: • Sentence:“Ineedsomespace.” • Context1:Inacrowdedroom,thissentencemightmeanthatsomeone physicallyneedsmoreroomtomovearound. • Context2:Inaromanticrelationship,thissentencemightmeanthatone personwantssomepersonalspaceortimealonetothinkorrelax. • Context3:Inaconversationaboutcomputerstorage,thissentencecould meansomeoneneedsadditionalstoragespaceontheirdevice. • Sentence:“It’scoldin here.” • Context1:Ifsomeonesaysthiswhileshiveringinaroomwiththeair conditioning setverylow,theymean thetemperatureisuncomfortablycold. • Context2:Ifthesamesentenceissaidwhenit’swinteroutside,itmight simplymeanthattheroomisatatypicalindoortemperature. • Context3:Inadiscussionaboutart,someonemightsaythistodescribethe colortoneoratmosphereofapainting,nottheactualtemperature. • Theseexamplesillustratehowthesamesentencecantakeondifferent meaningsdependingonthesituationorcontextinwhichit’sused.
ApproachestoDataAnalysis: • Asweseeitmakesverychallengingtoanalyzeunstructureddata.Letussee somewayswhichcanbeusedtoachievethis: • ContentAnalysis: • Contentanalysisisamethodusedtocarefullyexaminewrittenandrecorded communication.Initially,itwasaboutcountingandmeasuringthingsinthetext, likewordsandthemes. • Sometypesofcontentanalysis are • WordCount:Countthenumberofoccurrencesofagivenwordinthe sentenceunderanalysis. • ConceptualContent Analysis:Inthismethod, welooksforspecificconcept orthemes. • RelationalAnalysis:Inthismethodweneedlooksformeaningful connectionsbetweensentencesandidea. • ReferentialAnalysis:Thismethodconsidersthingslikebackground information,emphasis,and silenceinthe texttounderstanditscomplexityand meaning. • SentimentAnalysis: • SentimentAnalysisisthefieldofCRMthatusesNLPandMachineLearning, togivecomputersanabilitytounderstandtheemotionsexpressedinthetext messageorpostwrittenbyauser. • FrameAnalysis: • Frameanalysisisamethodtoexamineagivenscenariobasedonitsframe.It looksattheperspectiveorcontextinwhichsocialinformationispresentedto shapepublicopinionorunderstanding.
Forexample,seethepictureabove,whichshowshowanimagecanbe associatedwithtwooppositesidesofemotion. DiscourseAnalysis: Discourseanalysisgoesbeyondandabovewordsandsentenceanalysis.It doesnotrelyonjustfindingmeaningofawordandorcountythefrequencyof thewordinasentence,butinsteaditgoesdeeper.Itisaqualitativeanalysis methodthatlooksatthesubjectandit’sunderlyingmeaningofalanguagein writtenorspokenform,withinthecontextinwhichitoccurs. Thismethodusesalanguage’sSocial,Cultural,PoliticalandHistorical backgroundtointerpretameaningofasentence. VisualContentAnalysis: Whilethetextistheprimaryfocusofmostcontentanalysis,visualcontent analysisinvolvesanalyzingimages,videos,andothervisualelementsto extractmeaning,themes,orpatterns.
Conclusion: Inconclusion,wecansaythatonegivensentencecandrawdifferent conclusionsbasedonthecircumstances,therelationshipbetweenthe speakers,andthesubjectofdiscussionandculture.Henceasimplewayof interpretingasentenceandbuildingcodearounditisnotenough. Weneedtowriteadvancedalgorithmstousealloftheabovewaysof analyzingunstructureddataanditeratingthroughitgivingit arefinementevery time,this canbedonebydataanalyst. BuildingAImodelusingmachinelearningisnotataskwhichcanbedonein weeks,itrequirestechnicalexpertiseaswellaslotofefforttobuildalgorithms, preparepre-traineddata,trainmachines,analyzeoutputofalgorithm,re-tune algorithmifneededandrepeat.