What is Data Analytics and its Future Scope in 2023

Data analytics is the process of exploring and analyzing large datasets to find hidden patterns, unseen trends, discover correlations, ... 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Companiesaroundtheglobegeneratevastvolumesofdatadaily,intheformoflogfiles,webservers,transactionaldata,andvariouscustomer-relateddata.Inadditiontothis,socialmediawebsitesalsogenerateenormousamountsofdata.  Companiesideallyneedtousealloftheirgenerateddatatoderivevalueoutofitandmakeimpactfulbusinessdecisions.Dataanalyticsisusedtodrivethispurpose.  Dataanalyticsistheprocessofexploringandanalyzinglargedatasetstofindhiddenpatterns,unseentrends,discovercorrelations,andderivevaluableinsightstomakebusinesspredictions.Itimprovesthespeedandefficiencyofyourbusiness.  Businessesusemanymoderntoolsandtechnologiestoperformdataanalytics.Thisisdataanalyticsforbeginners,inanutshell.  WaystoUseDataAnalytics Nowthatyouhavelookedatwhatdataanalyticsis,let’sunderstandhowwecanusedataanalytics.  Fig:WaystouseDataAnalytics  1.ImprovedDecisionMaking:DataAnalyticseliminatesguessworkandmanualtasks. Beitchoosingtherightcontent,planningmarketingcampaigns,ordevelopingproducts.Organizationscanusetheinsightstheygainfromdataanalyticstomakeinformeddecisions.Thus,leadingtobetteroutcomesandcustomersatisfaction. 2.BetterCustomerService:Dataanalyticsallowsyoutotailorcustomerserviceaccordingtotheirneeds.Italsoprovidespersonalizationandbuildsstrongerrelationshipswithcustomers.Analyzeddatacanrevealinformationaboutcustomers’interests,concerns,andmore.Ithelpsyougivebetterrecommendationsforproductsandservices. 3.EfficientOperations:Withthehelpofdataanalytics,youcanstreamlineyourprocesses,savemoney,andboostproduction.Withanimprovedunderstandingofwhatyouraudiencewants,youspendlessertimecreatingadsandcontentthataren’tinlinewithyouraudience’sinterests. 4.EffectiveMarketing:Dataanalyticsgivesyouvaluableinsightsintohowyourcampaignsareperforming.Thishelpsinfine-tuningthemforoptimaloutcomes.Additionally,youcanalsofindpotentialcustomerswhoaremostlikelytointeractwithacampaignandconvertintoleads. Let’snowdiveintothevariousstepsinvolvedindataanalytics.  StepsInvolvedinDataAnalytics Nextsteptounderstandingwhatdataanalyticsistolearnhowdataisanalyzedinorganizations.Thereareafewstepsthatareinvolvedinthedataanalyticslifecycle.Let’shavealookatitwiththehelpofananalogy.  Imagineyouarerunningane-commercebusinessandyourcompanyhasnearlyamillionincustomerbase.Youraimistofigureoutcertainproblemsrelatedtoyourbusiness,andsubsequentlycomeupwithdata-drivensolutionstogrowyourbusiness. Belowarethestepsthatyoucantaketosolveyourproblems. Fig:DataAnalyticsprocesssteps  1.Understandtheproblem:Understandingthebusinessproblems,definingtheorganizationalgoals,andplanningalucrativesolutionisthefirststepintheanalyticsprocess.E-commercecompaniesoftenencounterissuessuchaspredictingthereturnofitems,givingrelevantproductrecommendations,cancellationoforders,identifyingfrauds,optimizingvehiclerouting,etc. 2.DataCollection:Next,youneedtocollecttransactionalbusinessdataandcustomer-relatedinformationfromthepastfewyearstoaddresstheproblemsyourbusinessisfacing.Thedatacanhaveinformationaboutthetotalunitsthatweresoldforaproduct,thesales,andprofitthatweremade,andalsowhenwastheorderplaced.Pastdataplaysacrucialroleinshapingthefutureofabusiness. 3.DataCleaning:Now,allthedatayoucollectwilloftenbedisorderly,messy,andcontainunwantedmissingvalues.Suchdataisnotsuitableorrelevantforperformingdataanalysis.Hence,youneedtocleanthedatatoremoveunwanted,redundant,andmissingvaluestomakeitreadyforanalysis. 4.DataExplorationandAnalysis:Afteryougathertherightdata,thenextvitalstepistoexecuteexploratorydataanalysis.Youcanusedatavisualizationandbusinessintelligencetools,dataminingtechniques,andpredictivemodelingtoanalyze,visualize,andpredictfutureoutcomesfromthisdata.Applyingthesemethodscantellyoutheimpactandrelationshipofacertainfeatureascomparedtoothervariables.  Belowaretheresultsyoucangetfromtheanalysis: Youcanidentifywhenacustomerpurchasesthenextproduct. Youcanunderstandhowlongittooktodelivertheproduct.  Yougetabetterinsightintothekindofitemsacustomerlooksfor,productreturns,etc.  Youwillbeabletopredictthesalesandprofitforthenextquarter.  Youcanminimizeordercancellationbydispatchingonlyrelevantproducts. You’llbeabletofigureouttheshortestroutetodelivertheproduct,etc. 5.Interprettheresults:Thefinalstepistointerprettheresultsandvalidateiftheoutcomesmeetyourexpectations.Youcanfindouthiddenpatternsandfuturetrends.Thiswillhelpyougaininsightsthatwillsupportyouwithappropriatedata-drivendecisionmaking. LookingforwardtoacareerinDataAnalytics?CheckouttheDataAnalyticsTrainingandgetcertifiedtoday.   DataAnalyticsTools Nowthatwelookedatthedifferentstepsinvolvedindataanalytics,let’sseethetoolsinvolvedindataanalytics,toperformtheabovesteps.Inthisblog,wewilldiscuss7dataanalyticstools,includingacoupleofprogramminglanguagesthatcanhelpyouperformanalyticsbetter.                                           Fig:DataAnalyticsforBeginners-Toolsused 1.Python:Pythonisanobject-orientedopen-sourceprogramminglanguage.Itsupportsarangeoflibrariesfordatamanipulation,datavisualization,anddatamodeling.  2.R:Risanopen-sourceprogramminglanguagemajorlyusedfornumericalandstatisticalanalysis.Itprovidesarangeoflibrariesfordataanalysisandvisualization. 3.Tableau:Itisasimplifieddatavisualizationandanalyticstool.Thishelpsyoucreateavarietyofvisualizationstopresentthedatainteractively,buildreports,anddashboardstoshowcaseinsightsandtrends.  4.PowerBI:PowerBIisabusinessintelligencetoolthathasaneasy‘draganddropfunctionality.Itsupportsmultipledatasourceswithfeaturesthatvisuallyappealtodata.PowerBIsupportsfeaturesthathelpyouaskquestionstoyourdataandgetimmediateinsights. 5.QlikView:QlikViewoffersinteractiveanalyticswithin-memorystoragetechnologytoanalyzevastvolumesofdataandusedatadiscoveriestosupportdecisionmaking.Itprovidessocialdatadiscoveryandinteractiveguidedanalytics.Itcanmanipulatecolossaldatasetsinstantlywithaccuracy.  6.ApacheSpark:ApacheSparkisanopen-sourcedataanalyticsenginethatprocessesdatainreal-timeandcarriesoutsophisticatedanalyticsusingSQLqueriesandmachinelearningalgorithms.  7.SAS:SASisastatisticalanalysissoftwarethatcanhelpyouperformanalytics,visualizedata,writeSQLqueries,performstatisticalanalysis,andbuildmachinelearningmodelstomakefuturepredictions.  Nowthatyouhaveseenthedataanalyticstools,let’sjumpaheadandseetheapplicationsofdataanalytics. Getbroadexposuretokeytechnologiesandskillsusedindataanalyticsanddatascience,includingstatisticswiththeDataAnalyticsCertificationProgram. DataAnalyticsApplications                                          Fig:Variousapplicationsofdataanalytics Dataanalyticsisusedinalmosteverysectorofbusiness,let’sdiscussafewofthem: 1.Retail:Dataanalyticshelpsretailersunderstandtheircustomerneedsandbuyinghabitstopredicttrends,recommendnewproducts,andboosttheirbusiness. Theyoptimizethesupplychain,andretailoperationsateverystepofthecustomerjourney. 2.Healthcare:Healthcareindustriesanalyzepatientdatatoprovidelifesavingdiagnosesandtreatmentoptions.Dataanalyticshelpindiscoveringnewdrugdevelopmentmethodsaswell.  3.Manufacturing:Usingdataanalytics,manufacturingsectorscandiscovernewcost-savingopportunities.Theycansolvecomplexsupplychainissues,laborconstraints,andequipmentbreakdowns. 4.Bankingsector: Bankingandfinancialinstitutionsuseanalyticstofindoutprobableloandefaultersandcustomerchurnoutrate.Italsohelpsindetectingfraudulenttransactionsimmediately. 5.Logistics:Logisticscompaniesusedataanalyticstodevelopnewbusinessmodelsandoptimizeroutes.This,inturn, ensuresthatthedeliveryreachesontimeinacost-efficientmanner. Thosewereafewoftheapplicationsinvolvingdataanalytics.Tomakethingssimpler,thisblogwillalsofocusonacasestudyfromWalmart.Hereyoucanobservehowdataanalyticsisappliedtogrowabusinessandserveitscustomersbetter. WalmartCaseStudy TheAmericanmultinationalretailcompany-Walmarthasover11,500storesin27countriesworldwide.Italsohase-commercewebsitesin10differentcountries.Walmartboastsmorethan5,900retailunits.TheseunitsoperateoutsidetheUnitedStates,with55bannersin26countries.Ithasmorethan700,000associatesservingmorethan100millioncustomerseveryweek.Inshort,it’saprettyhugecompany. Withallthesebignumbers,youcanimaginetheexponentialamountofdataWalmartgenerates.Walmartcollectsover2.5petabytesofdatafrom1millioncustomerseveryhour.Yes,youreadthatright.Nowtomakesenseofallthisinformation,Walmarthascreated‘DataCafé’–astate-of-the-artanalyticshub. InDataCafe,over200streamsofinternalandexternaldata,including40petabytesofrecenttransactionaldata,canbemodeled,manipulated,andvisualized.  Walmartalsoconstantlyanalysesover100millionkeywordstoknowwhatpeopleneareachstorearesayingonsocialmedia.Thisgivesthemabetterunderstandingoftheircustomerbehavioronwhattheylikeanddislike. Thisglobalchainusesmoderntoolsandtechnologiestoderivebusinessinsightsandimprovecustomersatisfaction.SomeofthesetechnologiesincludePython,SAS,andNoSQLdatabasessuchasCassandraandHadoop. Usingallthesetechnologiesanddataanalysistechniques,Walmartcanbettermanageitssupplychain,optimizeproductassortment,personalizetheshoppingexperience,andgiverelevantproductrecommendations.  Dataanalyticsforbeginnersshouldnotmerelybetheoretical,butalsobepractical.Dataanalyticsisalotmorepracticalthantheoretical.Hence,herewewillhavealookatademoondataanalyticsforbeginnersexclusively.  FREECourse:IntroductiontoDataAnalyticsLearnDataAnalyticsConcepts,Tools&SkillsStartLearning DemoonDataAnalyticsforBeginners Companiesperformdataanalyticstopredictsalesandprofit.Inthisdemo,we’llpredictsalesbasedontheadvertisingexpenditureusingtheLinearRegressionmodelinR.TheadvertisingexpenditurehasbeenmadeviadifferentmediumssuchasTelevision,Radio,andNewspaper.  Belowisthedatasetforourdemo: WewillbeusingtheRprogramminglanguageforthispurpose.  Risopen-sourcesoftwarethatcanbedownloadedfromtheRCranwebsite. Itiseasytolearnandimplement.  TheRlanguageisbuiltspecificallyforperformingstatisticalanalysis,datamanipulation,anddataminingusingpackageslikeplyr,dplyr,tidyr,andlubridate.  Rsupportsdatavisualizationwiththehelpofpackagessuchasggplot2,googleVis,Rcolorbrewer,leaflet,andggmap.  TheRsoftwarecanalsobeusedinawiderangeofanalyticalmodelingincludingclassicalstatisticaltests,linear/non-linearmodeling,dataclustering,time-seriesanalysis,andmore. So,let’sgetcoding!  First,letusinstallallthenecessarypackagesthatweneedforthisdemo. install.packages("dplyr") library(dplyr) install.packages("broom") library(broom) install.packages("caTools") library(caTools)#InstallthecaToolspackagewhichwillhelpusbuildourlinearregressionmodel  install.packages("ggplot2")#Installtheggplot2packagewhichwe’llusefordatavisualization library(ggplot2) Thenextstepistoloadthedataset.  Forthis,youcanusetheread.csvfunctionandprovidethepathlocationwhereyourdataislocated,followedbythedatasetnameandtheextension.Youcanassigntheloadeddatasettoavariable. ads