Business Analytics Framework
SAS Business AnalyticsFrameworkAndré LafrenièreTuesday, May 12, 2009Copyright 2009, SAS Institute Inc. All rights reserved.
Glb l ChllGlobalChallengeCopyright 2009, SAS Institute Inc. All rights reserved.
Copyright 2009, SAS Institute Inc. All rights reserved.
Copyright 2009, SAS Institute Inc. All rights reserved.
SAS Data IntegrationACCESSVALIDATEENHANCEDISTRIBUTEExploit Data AssetsEnsure Quality of DataClean, Augment andValidate DataPersist TrustworthyDataLeverage EnterpriseApplicationsMonitor and MaintainData QualityCombine and AnalyzeDataSynchronize MultipleSystemsSecurity, Privacy andComplianceReusable BusinessRulesAssimilate New DataTypesLeverage and ShareDataCOLLABORATECENTRALIZE and MANAGECopyright 2009, SAS Institute Inc. All rights reserved.
SAS Data IntegrationEnterprise ConnectivityData QualityETL (Extract, Transform, Load)Metadata ManagementData Migration & SynchronizationData FederationMaster Data ManagementCopyright 2009, SAS Institute Inc. All rights reserved.
Copyright 2009, SAS Institute Inc. All rights reserved.
DiscoveryQuestioning the Business“What happened?”“Where exactly is the problem?”“What if these trends continue?”“How many,y, how often,, where?”“What’s the best that can happen?”“Wh t will“Whatill hhappen next?”t?”“What actions are needed?”“Why is this happening?”Copyright 2009, SAS Institute Inc. All rights reserved.
DiscoveryReactive Decision Making“What happened?”“Where exactly is the problem?”“What if these trends continue?”“How many,y, how often,, where?”“What’s the best that can happen?”“Wh t will“Whatill hhappen next?”t?”“What actions are needed?”“Why is this happening?”Copyright 2009, SAS Institute Inc. All rights reserved.
DiscoveryProactive Decision Making“What happened?”“Where exactly is the problem?”“What if these trends continue?”“How many,y, how often,, where?”“What’s the best that can happen?”“Wh t will“Whatill hhappen next?”t?”“What actions are needed?”“Why is this happening?”Copyright 2009, SAS Institute Inc. All rights reserved.
SAS AnalyticsOBSERVE, DEFINEand MEASURETEST and LEARNINFORM and ACTExplore DataExperimentDeploy ResultsIdentify MetricsDevelop ModelCollaborate, Communicate,EmbedFormulate ProblemValidate ModelMonitor PerformanceVISUALIZEOPTIMIZE and MANAGECopyright 2009, SAS Institute Inc. All rights reserved.
SAS AnalyticsData VisualizationStatisticsData MiningForecasting & EconometricsQuality ImprovementOperations ResearchText AnalyticsModel Management and DeploymentCopyright 2009, SAS Institute Inc. All rights reserved.
Copyright 2009, SAS Institute Inc. All rights reserved.
SAS ReportingMEASUREMONITORANALYZEACTDefine MetricsAlertInteractDistributeEstablishstab s Parametersa a ete sFocusocus oon Keyey IssuesssuesExplorep o e / Investigateest gateCommunicateIdentify ThresholdsAccessUnderstandRelationshipsDeploy, Reallocate,RealignCOLLABORATEALIGN and MANAGECopyright 2009, SAS Institute Inc. All rights reserved.
SAS ReportingRtiDashboardsBusiness VisualizationWeb-based Reporting & AuthoringMicrosoft Office IntegrationQuery & AnalysisGuided AnalysisIntegrated AnalyticsCopyright 2009, SAS Institute Inc. All rights reserved.
Copyright 2009, SAS Institute Inc. All rights reserved.
Copyright 2009, SAS Institute Inc. All rights reserved.
SAS for BankingRiskCustomersFirmwide RiskCustomer Experience AnalyticsCredit Risk/Counterparty RiskCustomer Profitability & Relationship PricingMarket RiskAcquisition OnAcquisition,On-BoardingBoarding & RetentionAsset/Liability ManagementCross-Sell & Up-SellOperational RiskCollections OptimizationFraud/Financial CrimesMarketing OptimizationFinanceOperationsRegulatory CompliancePerformance Measurement & ReportingCapital Allocation & ManagementWorkforce Planning & ManagementLegal/Financial Consolidation & ReportingIT Performance ManagementCost & Profitability ManagementSustainability/Green InitiativesCopyright 2009, SAS Institute Inc. All rights reserved.
Credit Risk/Counterparty RiskCopyright 2009, SAS Institute Inc. All rights reserved.
Credit Risk/Counterparty RiskRegulatory ComplianceCopyright 2009, SAS Institute Inc. All rights reserved.Customer Profitability & Relationship PricingPerformance Measurement & Reporting
Copyright 2009, SAS Institute Inc. All rights reserved.
Customer Experience Analytics Market Risk Credit Risk/Counterparty Risk Firmwide Risk Collections Optimization Cross-Sell & Up-Sell Acquisition, On-Operational Risk Asset/Liability Management Fraud/Financial Crimes Marketing Optimization .
In-Database Analytics: Predictive Analytics, Oracle Exadata and Oracle Business Intelligence Charlie Berger Sr. Director Product Management, Data Mining and Advanced Analytics . 12 years ―stem celling analytics‖ into Oracle Designed advanced analytics into database kernel to leverage relational
Business Analytics software 3 visionary plans for enhancing their competitiveness, 83 percent answered "business intelligence and analytics."1 Business analytics can also increase the efficiency and effectiveness of core business processes and contribute to the creation of high-performing "analytics-driven" organizations.
Becoming an insight-driven organization: Analytics delivers concrete business value to health plans 4. Analytics drivers are business drivers. All analytics leaders we interviewed tie analytics to strategic business priorities. As a result, they see strong support from their leadership for their analytics enterprise objectives.
Analytics HOME Administration About Analytics 1 4 About Analytics This chapter introduces SonicWall Analytics. Analytics is designed to evaluate data collected by the firewall ecosystem, make policy decisions and take defensive actions using application- and user-based analytics.
A Hyperion Product Update What's New in Hyperion System 9 BI Essbase Analytics and Enterprise Analytics? Release summary Hyperion System 9 BI Essbase Analytics (Essbase Analytics) and Hyperion System 9 BI Enterprise Analytics (Enterprise Analytics) are analytic database engines within Hyperion System 9that allow our customers to develop and deploy custom applications.With .
Keywords: Business intelligence and analytics, big data analytics, Web 2.0 Introduction Business intelligence and analytics (BI&A) and the related field of big data analytics have become increasingly important in both the academic and the business communities over the past two decades. Industry studies have highlighted this significant development.
and examples. This courseware covers the importance of data analytics and visualization for decision-making in a business setting, the difference between data analytics, data science, and machine learning, and how to build an analytics framework and use analytics tools to uncover meaningful business insights. Key Learning Objectives
Analytics: Improving Insight and Business Value n Difficulty e Descriptive Analytics What happened? Reporting, dashboards Diagnostic Analytics Why did it happen? Ad hoc query, data mining Predictive Analytics What will happen? Statistics, planning Prescriptive Analytics What
