Business Intelligence and Analytics
Advanced AnalyticsAffinity-Based RecommendationsAgile AnalyticsAnalytical DatabaseAnalytics ArchitectureAnalytics SuiteAnalytics-as-a-Service (AaaS)Application AnalyticsApplication Lifecycle Management (ALM)Behavioral SegmentationBig Data SecurityBusiness Intelligence ArchitectureBusiness Process Modeling (BPM)Call AttributionCloud AnalyticsCloud AutomationCollaborative FilteringColumnar DatabaseConnection StringContextual DataContinuous Intelligence (CI)Conversion AttributionCRM OnboardingCross-Channel TrackingData ActivationData BlendingData CleaningData DiscoveryData ExplorationData GovernanceData IntelligenceData MartData MiningData ModelingData PreparationData ScienceData StewardshipData StorytellingData Warehouse ArchitectureDatabase SecurityDeep LearningDescriptive AnalyticsDevOps Continuous IntegrationEdge AnalyticsEmbedded ReportingEntity Relationship Diagram (ERD)Financial Data ManagementFirmographicsGeo AnalyticsHealthcare AnalyticsHealthcare InformaticsIn-Memory BIInfused AnalyticsInteractive VisualizationKPI DashboardKPI TrackingLocation AnalyticsManaged CloudMarketing Acceleration PlatformMarketing AnalyticsMarketing Qualified LeadMobile AnalyticsMPP DatabaseNatural Language UnderstandingNet Promoter Score (NPS)Next Best Action MarketingOmnichannel RetailingOperational IntelligenceOperational ReportingPredictive Data AnalyticsPredictive MaintenancePredictive SegmentationPrescriptive AnalyticsProduct AnalyticsR AnalyticsReal Time DashboardReal-Time AnalyticsRelational DatabaseReporting PerformanceRetail AnalyticsRetention MarketingSelf-Service Business IntelligenceSQL for Data AnalysisTalent AnalyticsText MiningUnified Data ManagementUnstructured DataVisual Data AnalysisVisual Workflow
A/B TestingActive BuyerAffinity MarketingAffinity-Based RecommendationsAudience BuyingBaby BoomersBack to Back Focus GroupsBrand IdentityClickstream BehaviorCluster AnalysisCRM OnboardingCustomer Cohort AnalysisCustomer Experience Management (CEM)Customer JourneyLifestyle ResearchLifetime ValueRaceRevenue Per VisitorTarget AudienceUser IDUser-Generated Content (UGC)
Display & Native Advertising
Ad MediationAd ViewabilityAutomated bid strategyBehavioral AdvertisingContextual targetingConversion TrackingCost per acquisition (CPA)Display Advertising TrafficImpressionsInteractive Mobile AdsLocation-based Advertising (LBA)Native AdsPath Length ReportPlayable AdsProgrammatic Media BuyingRewarded Video AdsSmart ListsUser IDVideo Companion ImpressionsVideo PublisherView RateView-through conversion windowYield Management
Contact FormEmail AutomationEmail ListExperience Optimization (EXO)Headline TestingSalesforce PardotWelcome Email
Market Research & Traffic Analysis
A.C. Nielsen Retail IndexA/B TestingAd Concept TestingAd Hoc ResearchAdobe AnalyticsAffinity MarketingBack to Back Focus GroupsCluster AnalysisCore Based Statistical Area (CBSA)Cross-Device MarketingData CollectionData MiningDirect ChannelDisplay ChannelEmail ChannelEngagement RateEye TrackingHomogeneous GroupsHypothesis TestingIndexLifestyle ResearchLikert ScaleMarket EffectivenessMarket SegmentationMarket ShareMonthly Unique VisitorsNet Promoter Score (NPS)Neural NetworkNiche MarketingNielsen RatingsObservation BiasObservation ResearchOrganic ChannelPaid Search ChannelPath Length ReportPrimary ResearchQualitative ResearchRaceReferral ChannelSocial Media ChannelWebsite Survey
MarTech and AdTech
Acme DataAdobe TargetAmazon CloudFrontAmazon RedshiftAnalanceAnswerMinerAppDynamicsBaremetricsBomboraBootstrapBrightcoveCisco CMX EngageDasherooDundas BIFivetranFunnelGoogle BigQueryGoogle Data StudioGoogle Marketing PlatformGoogle OptimizeHoneywell Operational IntelligenceIBM Cognos AnalyticsIBM InfoSphere Data ArchitectInspectletJenkinsKissflowKNIME Analytics PlatformLiveRampLookerMarketing Technology StackMarketoMicrosoft Power BIMicrosoft SQL Server ReportingNutanixOptimizelyPendoPowerCenter InformaticaQlikViewSalesforce PardotSAP Crystal ReportsSocialbakersSQLiteStriimTableauTobii DynavoxTrade DeskTrifactaUserExperiorVisual Website Optimizer (VWO)Wolfram MathematicaWooCommerceYellowfin BIYieldify
Mobile App Intelligence
Ad MediationAd ViewabilityAd WhalesAdjustApp Churn RateApp DemographicsApp MonetizationApp RatingApp Store TrafficApplication Lifecycle Management (ALM)AR (Augmented Reality) AdvertisingAverage Revenue Per Paying User (ARPPU)Cross PromotionDaily Active Users (DAU)Dynamic TestingIn-App AdvertisingIn-App BiddingInstant MessagingInteractive Mobile AdsK-FactorLocation-based Advertising (LBA)Mobile Ad FraudMobile AttributionMonthly Active Users (MAU)Playable AdsPush NotificationRewarded Video AdsSDK MediationSearch TermsServer Side MediationYield Management
Paid Search Advertising
Ad deliveryAd extensionsAd MediationAd strengthAd ViewabilityAutomated bid strategyAverage Order Value (AOV)Combined audiencesConversion AttributionConversion TrackingCost per acquisition (CPA)Floodlight TagHeadline TestingImpressionsKeyword ResearchLocation-based Advertising (LBA)Path Length ReportQuality scoreReturn on investment (ROI)SitelinksSmart BiddingSmart ListsUser IDView-through conversion windowYield Management
Social Media Sensing
Ad ViewabilityCommunity ManagerCountry ReachImpressionsInstant MessagingLocation-based Advertising (LBA)MicrobloggingNet Media CostPinterestPlayable AdsReachReputation ManagementRewarded Video AdsRich PinsSnapchatSocial Media ConversionsSocial Media ListeningUser-Generated Content (UGC)Video Companion Impressions
Technology and Innovation
Artificial IntelligenceBig DataBlockchainData WarehouseDeep LearningDisruptive InnovationInternet of ThingsMarketing Technology StackPredictive Data AnalyticsPredictive SegmentationPrescriptive AnalyticsR AnalyticsVoice Assistants
TV Ad Measurement and Insights
Ad ViewabilityAd-supported streaming video on demand (ASVOD)Addressable TVAdvanced TVAutomatic content recognition (ACR)Broadcast Addressable TVHousehold DataLocation-based Advertising (LBA)Multichannel Video Programming Distributor (MVPD)Nielsen RatingsOver-the-top (OTT)Skinny BundleSubscription video on demand (SVOD)Targeting Rating Point (TRP)Television advertisementTelevision Viewer Rating (TVR)TV NetworkUpfrontsVideo on demand (VOD)
Data cleansing or data cleaning is the process of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty or coarse data.
What is the process of data cleaning?
Data cleaning, also called data cleansing, is the process of ensuring that your data is correct, consistent and useable by identifying any errors or corruptions in the data, correcting or deleting them, or manually processing them as needed to prevent the error from happening again.
Why is data cleaning important?
Data cleansing is also important because it improves your data quality and in doing so, increases overall productivity. When you clean your data, all outdated or incorrect information is gone – leaving you with the highest quality information.
What is data cleaning in statistics?
‘Cleaning’ refers to the process of removing invalid data points from a dataset. Many statistical analyses try to find a pattern in a data series, based on a hypothesis or assumption about the nature of the data. In the process, we ignore these particular data points, and conduct our analysis on the remaining data.
What is data cleansing in ETL?
In data warehouses, data cleaning is a major part of the so-called ETL process. We also discuss current tool support for data cleaning. 1 Introduction. Data cleaning, also called data cleansing or scrubbing, deals with detecting and removing errors and inconsistencies from data in order to improve the quality of data.
Why does data cleaning play a vital role in analysis?
Regardless of the type of analysis or data visualizations you need, data cleaning is a vital step to ensure that the answers you generate are accurate. When collecting data from several streams and with manual input from users, information can carry mistakes, be incorrectly inputted, or have gaps. See the full article for more details.
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