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Evaluating Big Data Predictive Analytics Platforms
 

Evaluating Big Data Predictive Analytics Platforms

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Mike Gualtieri, Principal Analyst, Forrester Research, presents at the Big Analytics Roadshow, 2012 in New York City on December 12, 2012 ...

Mike Gualtieri, Principal Analyst, Forrester Research, presents at the Big Analytics Roadshow, 2012 in New York City on December 12, 2012

Presentation title: Evaluating Big Data Predictive Analytics Platforms

Abstract: Great. You have Big Data. Now what? You have to analyze it to find game-changing predictive models that you can use to make smart decisions, reduce risk, or deliver breakthrough customer experiences. Big Data Predictive Analytics solutions are software and/or hardware solutions that allow firms to discover, evaluate, optimize, and deploy predictive models by analyzing big data sources. In this session, Forrester Principal Analyst Mike Gualtieri will discuss the key criteria you should use to evaluate Big Data Predictive Analytics platforms to meet your specific needs.

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    Evaluating Big Data Predictive Analytics Platforms Evaluating Big Data Predictive Analytics Platforms Presentation Transcript

    • Evaluating Big Data PredictiveAnalytics SolutionsMike Gualtieri, Principal AnalystDecember 12, 2013.New York, NYTwitter: @mgualtieri
    • Outlook
    • The right data and right talent are the key to predictive analytics success Source: August 8, 2012, “The State Of Customer Analytics 2012” Forrester report© 2012 Forrester Research, Inc. Reproduction Prohibited 3
    • Business intelligence means customer intelligence No. 1 priority for 2011 No. 5 priority for 2009 Source: May 27, 2011, “Forrsights: The Software Market In Transformation, 2011 And Beyond” Forrester report© 2012 Forrester Research, Inc. Reproduction Prohibited 4
    • 54% Budget decision-makers plan to increase spending in 2012 on real-time analytics & Big Data solutions.Sources: iStockphoto (www.istockphoto.com), Forrsights Budgets And Priorities Tracker Survey, Q4 2012
    • 7BMore people using more technology means more bigdata.
    • What exactlyis Big Data?
    • It’s allrelative.
    • #BigData 9
    • “Big Data is the frontier of a firm’s ability to store, process, and access (SPA) all of the data it needs tooperate, make decisions, reduce risks, and serve customers.”DEFINITION
    • FrontierBig Data is about pushing limits. Exponential growthin data means the frontier is vast.
    • Think SPACan you store, process, and access (SPA) all of thedata you need?
    • Big Data management is about three key activities: •Can you capture and store Store your data? •Can you cleanse, enrich, Process and analyze your data? •Can you retrieve, search, Access integrate, and visualize your data?© 2012 Forrester Research, Inc. Reproduction Prohibited 14
    • Think SPA when youthink Big Data.
    • #Predictive 16
    • “Predictive analytics solutions allowfirms to discover, evaluate, optimize, and deploy predictive models by analyzing data sources to improve business outcomes.”DEFINITION
    • What do great predictive analytics use cases have in common? Evidence-based methods don’t exist or are sub-optimal. Relevant data is available. The environment changes with moderate frequency. The business outcome is significant.© 2012 Forrester Research, Inc. Reproduction Prohibited 18
    • Predictive analytics is a continuous process • The right data to establish a cause Causative and effect data • Enough data to be significant • Understand business outcome Data • Create hypothesis about data analysts mining algorithms that will create predictive rules • Data preparation Modeling • Discovery (visualization, machine tools learning algos) • Evaluation and optimization • Data to feed model Model • Model execution (embedded, deployment callable service)© 2012 Forrester Research, Inc. Reproduction Prohibited 19
    • Big Data predictive analytics solutions must address the full lifecycle Understand data Monitor Prepare data Business goal Deploy Model Evaluate© 2012 Forrester Research, Inc. Reproduction Prohibited 20
    • Big Data comes in many forms • Data described by a schema Structured • Relational database, XML, text delimited flat file, system events • Free-form text Unstructured • Email, documents, tweets, blog text comments, Facebook status, genome • Audio, images, video Binary • Surveillance cameras, geological survey maps, Siri voice© 2012 Forrester Research, Inc. Reproduction Prohibited 21
    • The Forrester Wave evaluates currentsolution, strategy, and market presence. Forrester Wave™: Business Rules Platforms, Broadest Feature Sets, Q1 ’08
    • Current offering (y axis)ArchitectureDataDiscoveryEvaluation & OptimizationDeploymentToolsStandards, integration, solutions, and extensibility
    • Strategy (x – axis)Licensing & pricingCommitmentProduct roadmap
    • Market Presence (size of bubble)Company financialsGlobal presence and install basePartnerships
    • ChurnCan you prevent Melissa from switching to acompetitive mobile plan?
    • Million Song DatasetHow can you provide Melissa with nearly perfectsong recommendation?
    • Architecture criteriaRun-time platform options Analysis runtime platform options Analyst tools runtime optionsWorkload optimization Performance features Scalability featuresSecurity Data security Model security User securityPerformance referenceScalability reference
    • Data criteriaData typesData sourcesData set preparation tools
    • Discovery criteriaAlgorithms supported Structured Unstructured NetworkData discovery visualization toolsAutomated discoveryAlgorithm extensibilityLife-cycle management tools
    • Evaluation & optimization criteriaModel evaluationModel optimizationOverride rulesContinuous optimization
    • Deployment criteriaExecutionInput dataOutput data
    • Tools criteriaData scientistsBusiness analystsApplication developers
    • Standards, integration, solutions, andextensibility criteriaPMML supportPlatform integrationsTargeted solutionsUser interface extensibility
    • StrategyLicensing and pricing Licensing Pricing (average and entry) Maintenance fees Support options TransparencyCommitment Employee headcount in market R&D spending Ability to executeProduct roadmap
    • Market PresenceCompany financials Revenues Revenue growthGlobal presence and installed base Installed base (total and by geography) MomentumPartnerships Software vendors SaaS/hosting providers Professional services
    • Forrester’s Wave evaluation criteria for BigData Predictive Analytics solutionsCurrent Offering Strategy Architecture Licensing & pricing Data Commitment Discovery Product roadmap Evaluation & Market presence Optimization Company financials Deployment Global presence and install base Tools Partnerships Standards, integration, solutions, and extensibility
    • Forrester weights the criteria, but clients canset custom weightings
    • Big data predictiveanalytics solutions make it easier.
    • Big data predictive analytics solutions range from coding tools to specific business solutions (list not ordered or grouped) Alpine Data Labs Zementis Alteryx Google Prediction API Pentaho Angoss R Matlab EMC KNIME Rapid – I Teradata SAS Opera Solutions Teradata Aster IBM Revolution Analytics FICO Cetus Pegasystems KXEN Oracle Salford Microsoft Statsoft Pitney Bowes SAP FuzzyLogix TIBCO Weka Mahout© 2012 Forrester Research, Inc. Reproduction Prohibited 40
    • Forrester Wave™: Big Data Predictive Analytics Solutions planned publication Q1 2013 Forrester methodology limited this Forrester Wave to ten vendors. Many vendor solutions and combinations of solutions exist for a variety of use cases. Publication of the Forrester Wave is expected in Q1 2013. Schedule an inquiry to discuss your unique circumstances.© 2012 Forrester Research, Inc. Reproduction Prohibited 41
    • Thank you Mike Gualtieri mgualtieri@forrester.com Twitter: @mgualtieri