Structured vs. Unstructured Data: What's the Difference? - IBM

Structured data — typically categorized as quantitative data — is highly organized and easily decipherable by machine learning algorithms. Skiptocontent Structuredvs.UnstructuredData:What’stheDifference? Artificialintelligence Datascience Database 29June2021 6minread By: IBMCloudEducation,IBMCloudEducation SharethispageonTwitter SharethispageonFacebook SharethispageonLinkedIn E-mailthispage Alookintostructuredandunstructureddata,theirkeydifferencesandwhichformbestmeetsyourbusinessneeds. Alldataisnotcreatedequal.Somedataisstructured,butmostofitisunstructured.Structuredandunstructureddataissourced,collectedandscaledindifferentways,andeachoneresidesinadifferenttypeofdatabase. Inthisarticle,we’lltakeadeepdiveintobothtypessothatyoucangetthemostoutofyourdata. Whatisstructureddata? Structureddata—typicallycategorizedasquantitativedata—ishighlyorganizedandeasilydecipherablebymachinelearningalgorithms.DevelopedbyIBMin1974,structuredquerylanguage(SQL)istheprogramminglanguageusedtomanagestructureddata.Byusingarelational(SQL)database,businessuserscanquicklyinput,searchandmanipulatestructureddata. Prosandconsofstructureddata Examplesofstructureddataincludedates,names,addresses,creditcardnumbers,etc.Theirbenefitsaretiedtoeaseofuseandaccess,whileliabilitiesrevolvearounddatainflexibility: Pros Easilyusedbymachinelearning(ML)algorithms:ThespecificandorganizedarchitectureofstructureddataeasesmanipulationandqueryingofMLdata. Easilyusedbybusinessusers:Structureddatadoesnotrequireanin-depthunderstandingofdifferenttypesofdataandhowtheyfunction.Withabasicunderstandingofthetopicrelativetothedata,userscaneasilyaccessandinterpretthedata. Accessiblebymoretools:Sincestructureddatapredatesunstructureddata,therearemoretoolsavailableforusingandanalyzingstructureddata. Cons Limitedusage:Datawithapredefinedstructurecanonlybeusedforitsintendedpurpose,whichlimitsitsflexibilityandusability. Limitedstorageoptions:Structureddataisgenerallystoredindatastoragesystemswithrigidschemas(e.g.,“datawarehouses”).Therefore,changesindatarequirementsnecessitateanupdateofallstructureddata,whichleadstoamassiveexpenditureoftimeandresources. Structureddatatools OLAP:Performshigh-speed,multidimensionaldataanalysisfromunified,centralizeddatastores. SQLite:Implementsaself-contained,serverless,zero-configuration,transactionalrelationaldatabaseengine. MySQL:Embedsdataintomass-deployedsoftware,particularlymission-critical,heavy-loadproductionsystem. PostgreSQL:SupportsSQLandJSONqueryingaswellashigh-tierprogramminglanguages(C/C+,Java,Python,etc.). Usecasesforstructureddata Customerrelationshipmanagement(CRM):CRMsoftwarerunsstructureddatathroughanalyticaltoolstocreatedatasetsthatrevealcustomerbehaviorpatternsandtrends. Onlinebooking:Hotelandticketreservationdata(e.g.,dates,prices,destinations,etc.)fitsthe“rowsandcolumns”formatindicativeofthepre-defineddatamodel. Accounting:Accountingfirmsordepartmentsusestructureddatatoprocessandrecordfinancialtransactions. Whatisunstructureddata? Unstructureddata,typicallycategorizedasqualitativedata,cannotbeprocessedandanalyzedviaconventionaldatatoolsandmethods.Sinceunstructureddatadoesnothaveapredefineddatamodel,itisbestmanagedinnon-relational(NoSQL)databases.Anotherwaytomanageunstructureddataistousedatalakestopreserveitinrawform. Theimportanceofunstructureddataisrapidlyincreasing.Recentprojectionsindicatethatunstructureddataisover80%ofallenterprisedata,while95%ofbusinessesprioritizeunstructureddatamanagement. Prosandconsofunstructureddata Examplesofunstructureddataincludetext,mobileactivity,socialmediaposts,InternetofThings(IoT)sensordata,etc.Theirbenefitsinvolveadvantagesinformat,speedandstorage,whileliabilitiesrevolvearoundexpertiseandavailableresources: Pros Nativeformat:Unstructureddata,storedinitsnativeformat,remainsundefineduntilneeded.Itsadaptabilityincreasesfileformatsinthedatabase,whichwidensthedatapoolandenablesdatascientiststoprepareandanalyzeonlythedatatheyneed. Fastaccumulationrates:Sincethereisnoneedtopredefinethedata,itcanbecollectedquicklyandeasily. Datalakestorage:Allowsformassivestorageandpay-as-you-usepricing,whichcutscostsandeasesscalability. Cons Requiresexpertise:Duetoitsundefined/non-formattednature,datascienceexpertiseisrequiredtoprepareandanalyzeunstructureddata.Thisisbeneficialtodataanalystsbutalienatesunspecializedbusinessuserswhomaynotfullyunderstandspecializeddatatopicsorhowtoutilizetheirdata. Specializedtools:Specializedtoolsarerequiredtomanipulateunstructureddata,whichlimitsproductchoicesfordatamanagers. Unstructureddatatools MongoDB:Usesflexibledocumentstoprocessdataforcross-platformapplicationsandservices. DynamoDB:Deliverssingle-digitmillisecondperformanceatanyscaleviabuilt-insecurity,in-memorycachingandbackupandrestore. Hadoop:Providesdistributedprocessingoflargedatasetsusingsimpleprogrammingmodelsandnoformattingrequirements. Azure:EnablesagilecloudcomputingforcreatingandmanagingappsthroughMicrosoft’sdatacenters. Usecasesforunstructureddata Datamining:Enablesbusinessestouseunstructureddatatoidentifyconsumerbehavior,productsentiment,andpurchasingpatternstobetteraccommodatetheircustomerbase. Predictivedataanalytics:Alertbusinessesofimportantactivityaheadoftimesotheycanproperlyplanandaccordinglyadjusttosignificantmarketshifts. Chatbots:Performtextanalysistoroutecustomerquestionstotheappropriateanswersources. Whatarethekeydifferencesbetweenstructuredandunstructureddata? Whilestructured(quantitative)datagivesa“birds-eyeview”ofcustomers,unstructured(qualitative)dataprovidesadeeperunderstandingofcustomerbehaviorandintent.Let’sexploresomeofthekeyareasofdifferenceandtheirimplications: Sources:StructureddataissourcedfromGPSsensors,onlineforms,networklogs,webserverlogs,OLTPsystems,etc.,whereasunstructureddatasourcesincludeemailmessages,word-processingdocuments,PDFfiles,etc. Forms:Structureddataconsistsofnumbersandvalues,whereasunstructureddataconsistsofsensors,textfiles,audioandvideofiles,etc. Models:Structureddatahasapredefineddatamodelandisformattedtoasetdatastructurebeforebeingplacedindatastorage(e.g.,schema-on-write),whereasunstructureddataisstoredinitsnativeformatandnotprocesseduntilitisused(e.g.,schema-on-read). Storage:Structureddataisstoredintabularformats(e.g.,excelsheetsorSQLdatabases)thatrequirelessstoragespace.Itcanbestoredindatawarehouses,whichmakesithighlyscalable.Unstructureddata,ontheotherhand,isstoredasmediafilesorNoSQLdatabases,whichrequiremorespace.Itcanbestoredindatalakeswhichmakesitdifficulttoscale. Uses:Structureddataisusedinmachinelearning(ML)anddrivesitsalgorithms,whereasunstructureddataisusedinnaturallanguageprocessing(NLP)andtextmining. Whatissemi-structureddata? Semi-structureddata(e.g.,JSON,CSV,XML)isthe“bridge”betweenstructuredandunstructureddata.Itdoesnothaveapredefineddatamodelandismorecomplexthanstructureddata,yeteasiertostorethanunstructureddata. Semi-structureddatauses“metadata”(e.g.,tagsandsemanticmarkers)toidentifyspecificdatacharacteristicsandscaledataintorecordsandpresetfields.Metadataultimatelyenablessemi-structureddatatobebettercataloged,searchedandanalyzedthanunstructureddata. Exampleofmetadatausage:Anonlinearticledisplaysaheadline,asnippet,afeaturedimage,imagealt-text,slug,etc.,whichhelpsdifferentiateonepieceofwebcontentfromsimilarpieces. Exampleofsemi-structureddatavs.structureddata:Atab-delimitedfilecontainingcustomerdataversusadatabasecontainingCRMtables. Exampleofsemi-structureddatavs.unstructureddata:Atab-delimitedfileversusalistofcommentsfromacustomer’sInstagram. Thefutureofdata Recentdevelopmentsinartificialintelligence(AI)andmachinelearning(ML)aredrivingthefuturewaveofdata,whichisenhancingbusinessintelligenceandadvancingindustrialinnovation.Inparticular,thedataformatsandmodelscoveredinthisarticlearehelpingbusinessuserstodothefollowing: Analyzedigitalcommunicationsforcompliance:Patternrecognitionandemailthreadinganalysissoftwarethatcansearchemailandchatdataforpotentialnoncompliance. Trackhigh-volumecustomerconversationsinsocialmedia:Textanalyticsandsentimentanalysisthatenablesmonitoringofmarketingcampaignresultsandidentifyingonlinethreats. Gainnewmarketingintelligence:MLanalyticstoolsthatcanquicklycovermassiveamountsofdatatohelpbusinessesanalyzecustomerbehavior. Furthermore,smartandefficientusageofdataformatsandmodelscanhelpyouwiththefollowing: Understandcustomerneedsatadeeperleveltobetterservethem Createmorefocusedandtargetedmarketingcampaigns Trackcurrentmetricsandcreatenewones Createbetterproductopportunitiesandofferings Reduceoperationalcosts StructuredandunstructureddataandIBM Whetheryouareaseasoneddataexpertoranovicebusinessowner,beingabletohandleallformsofdataisconducivetoyoursuccess.Byleveragingstructured,semi-structuredandunstructureddataoptions,youcanperformoptimaldatamanagementthatwillultimatelybenefityourmission. Tobetterunderstanddatastorageoptionsforwhateverkindofdatabestservesyou,checkoutIBMCloudDatabases. IBMCloudEducation IBMCloudEducation FollowIBMCloud Bethefirsttohearaboutnews,productupdates,andinnovationfromIBMCloud. 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