PSHA May 16 th 2013 in Karachi amp May 20 th in Lahore Opportunity in Big Data Copyright 2013 Asrym Inc 1 May 16 2013 Introduction Nauman Sheikh Graduated from FAST Lahore in 1994 ID: 759901
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Nauman Sheikh
Hosted by P@SHA – May 16th, 2013 in Karachi & May 20th in Lahore
Opportunity in Big Data
Copyright 2013 – Asrym Inc.
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May 16, 2013
Slide2Introduction
Nauman Sheikh
Graduated from FAST Lahore in 1994Moved to USA in 1997Started working on a large Enterprise Data Warehouse Project4 data martsFully normalized EDWFormal ETL tool and staging layerFormal OLAP tool and ad-hoc analysisNext 10 years worked on very large and complex data warehouse systemsBuilt a 100+ TB data warehouse system as a hosted productGenerated $40 million in first year of productionLast 5 years have been focused on Analytics in Customer AnalyticsConsumer banking and servicesFraud and Waste prevention
Copyright 2013 – Asrym Inc.
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May 16, 2013
Slide3The Theory Works
Start-up Venture
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Slide4The Theory Works
Implementing Analytics
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May 16, 2013
Slide5What is it and how to exploit it
Agenda
Definition – 20 minBackground and Hype – 15 minConventional Wisdom – 15 minShort Q/A – 10 minMy Perspective – 10 minOpportunity – 15 minChallenges – 10 minQ/A – 20 minClosing, Refreshments and Networking
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Slide6Definition
Wisdom
Big Data Vs AnalyticsVelocityVarietyVolumeSuppose every instrument could by command or anticipation of need execute its function on its own; suppose that spindles could weave of their own accord and plectra strike the strings of zithers by themselves; then craftsmen would have no need of hand-work and masters have no need of slavesCommandAnticipation of NeedAristotle said that almost 2300 years ago
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Slide7Big Data and Entrepreneurship
Entrepreneurship
Essence of EntrepreneurshipGreed- Riches?ExecutionInnovationHave you heard ofAlexander FlemingTim-Berners LeeWhat is InnovationProduct InnovationApple, Sony, P&G, GE, GMWhat about Google and WalmartProcess InnovationOperational EfficiencyCustomer ExperienceBig Data Analytics is all about Process Innovation
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May 22, 2013
Slide8Definition
Decisions – Human Cognitive ability
Activity and ActionsExperience and Knowledge Future course of ActionIn the digital world….Business Operations and their automationData WarehousingAnalyticsIt is not about Petabytes of data and massive computing infrastructureIt is about finding the insight and acting on it
Copyright 2013 – Asrym Inc.
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Slide9Definition
Working Example
A company sells stationary across PakistanOperate in 5 regions and 3 national warehousesImplement an order and Invoicing SystemSearch and look-upCounts and ListsOperational ReportingSummary ReportingHistorical ReportingMetrics, KPIs and Thresholds – DashboardsGeo-spatial Analysis or Data Visualization
Copyright 2013 – Asrym Inc.
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Slide10Information Continuum
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May 16, 2013
Low Implementation Complexity High
Low Business Value High
Search & Lookup
Counts &
Lists
Operational Reporting
Summary Reporting
Historical Reporting
Metrics, KPIs, & Thresholds
Analytical Applications
Analytics Models
Monitoring & Tuning
Decision Strategies
Present
Now
Past
Historic
Future
Slide11Definition
Analytics - Models
Algorithm Vs. ModelMusical Instrument Vs. TunePredictive ModelingRegressionDecision TreesNeural networks and Bayesian NetworksDescriptive ModelingClusteringAssociation RulesNetwork AnalysisMarket basket Analysis
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May 16, 2013
Slide12May 30, 2013
Data Mining: Concepts and Techniques
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Working Example
Prediction –Training Dataset
Slide13May 30, 2013
Data Mining: Concepts and Techniques
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age?
overcast
student?
credit rating?
<=30
>40
no
yes
yes
yes
31..40
no
fair
excellent
yes
no
Working Example
Prediction – Decision Tree Model
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Decision Tree Algorithm
Decision Tree Model
Predicted Variable
Known
Values
Predicted Variable
Unknown Values
Input
Output
Working Example
Prediction –Decisions on Model
Slide15Background and Hype
Google, Yahoo and Facebook
Map Reduce – 2003-2004 (Google)No SQL Initiative – 2004Hadoop – 2005 (Yahoo)Massive adoption and use 2008 (Facebook)
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May 16, 2013
Slide16Background and Hype
All Aboard
Competing on Analytics – Tom DavenportHarrah’s Casino – Case StudyNate SilverObama Election CampaignMS programs at various UniversitiesWallstreet Journal – Full page review February 2013October 2012 – HBR - Cover
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Slide171.5
Working Example
HBR Cover
Slide18Conventional Wisdom
Davenport and Tech Vendors
Data scientistsHadoopStatistics/high-end softwareBuild-itInteresting Insight
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May 16, 2013
Slide19Any Questions
May 16, 2013
Copyright 2013 – Asrym Inc.
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Q and A
Slide20My Perspective
Implementing Analytics
SimplificationCommoditizationDemocratizationInnovationStatistics Vs. Data MiningInput – Output – Black boxAnalytics for Everyone
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May 16, 2013
Slide21Opportunity
Emerging Markets
BankingTelecommunicationsEnergyAgricultureMobile bankingMicrofinanceMarketingFraud, Anti-theft, anti-corruption
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Slide22Opportunity
Export Market
Domain knowledge through operational dataProblem statement – constant innovationDeploying data miningProactive pilots and samplesGaming, social media, mobile apps – opportunityNon-traditional sectors like shipping, education, construction, small business
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Slide23Challenges
Value from data
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Slide24Challenges
Challenges
ManpowerAI is sexy againDomain knowledgePilot – needs actual dataResults and convincing the management – black box works
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Slide25Any Questions
May 16, 2013
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Q and A