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
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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)
A data warehousing is defined as a technique for collecting and managing data from varied sources to provide meaningful business insights. It is electronic storage of a large amount of information by a business which is designed for query and analysis instead of transaction processing.
What is a data warehouse used for?
Data warehouses are used for analytical purposes and business reporting. Data warehouses typically store historical data by integrating copies of transaction data from disparate sources. Data warehouses can also use real-time data feeds for reports that use the most current, integrated information.
What are the main components of data warehouse?
The data warehouse architecture is based on a relational database management system server that functions as the central repository for informational data. Operational data and processing is completely separated from data warehouse processing. This central information repository is surrounded by a number of key components designed to make the entire environment functional, manageable and accessible by both the operational systems that source data into the warehouse and by end-user query and analysis tools. Read the full article for more details.
What is a data warehouse with an example?
A data warehouse essentially combines information from several sources into one comprehensive database. For example, in the business world, a data warehouse might incorporate customer information from a company’s point-of-sale systems (the cash registers), its website, its mailing lists and its comment cards.
Is Hadoop a data warehouse?
Hadoop is not an IDW. Hadoop is not a database. A data warehouse is usually implemented in a single RDBMS which acts as a centre store, whereas Hadoop and HDFS span across multiple machines to handle large volumes of data that does not fit into the memory.
What is the main purpose of a data warehouse?
A data warehouse is a federated repository for all the data collected by an enterprise’s various operational systems, be they physical or logical. Data warehousing emphasizes the capture of data from diverse sources for access and analysis rather than for transaction processing.
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