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Business Intelligence and New Trends
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Business Intelligence and New Trends



Business Intelligence and Analytics World 2013

Business Intelligence and Analytics World 2013



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    Business Intelligence and New Trends Business Intelligence and New Trends Presentation Transcript

    • Muzaffer YÖNTEMmuzaffer.yontem@sybase.com.trHttp://www.muzaffer.yontem.comTwitter: @myontemLinkedin ProfileBusiness Analytics ProfessionalSybase Turkey Sales Business Dev. Dir.İstanbul Doğuş ÜniversitesiMay 8, 2013
    • Data is the new oil ?Source:www.platon.net
    • Typical Any CompanySource:SAP AG
    • Core BusinessApps (ERP)Typical Any CompanySource:SAP AG
    • RUNTypical Any CompanyOPERATIONALSource:SAP AG
    • RUNTypical Any CompanyCore BusinessApps (ERP)OPERATIONALSource:SAP AG
    • RUNTypical Any CompanyOPERATIONALERPCustomersEmployeesStuffSuppliers+ LoBSource:SAP AG
    • Your CompanyUNDERSTANDSource:SAP AG
    • Typical Any CompanyRUNUNDERSTANDiPad
    • What BI means for Business and IT ?Source:Gartner BI Summit London 2010
    • MARKET EVOLUTIONSource: IDC, 2011Operational Reporting &Data warehousingBusinessAnalyticsSource: Sybase
    • Performans Yönetimi bir bütünSource:Gartner BI summit Turkey 2007
    • BI provides common understanding within companySource:Gartner BI Summit London 2010
    • Everything started with....
    • OLAP / Dashboard /Widget /Google like Search
    • Business UsersC-Level ExecutivesIT UsersPortalIntegration/InfoDistributionData ExplorationVisual IntelligenceInteractiveDashboardingBusinessSemanticLayer/ImpactAnalysisDesktop WidgetOffline AnalysisMultinational OLAP/ROLAPBusiness AnalyticsNeedsOperationalReportingAd-Hoc QueryMobile Business IntelligencePredictive AnalysisAdvancedVisualizationEnterprise Information Management(Master Data Management)1..n1..x1..y
    • “Big Data”… Overly Simplified?•The real value of “Big Data" is not driven by its mere size…•…but, rather, by the effectiveness and quality of the processes thatmanage it.• “Big Data” becomes an indispensible competitive advantage for theenterprise; only when, it is turned into accurate and meaningfulinformation in a timely and effective manner.“Make everything as simple as possible,but not simpler.” ~ Albert EinsteinSource: Sybase
    • VolumeVarietyApplicationVerticalsSocial MediaMobileCloudInternetDatabaseInformation JourneyTheBigDataPhenomenonBig Data10n Bytes■ Extreme Data Volumes■ Data Variety and atomic storage formats■ De-Duplication, Security, AccessO( f(n) )■ Computational Complexity■ Iterative Procedures■ Distributed ComputingEvents / sec■ Time to Value of Data■ Streaming Data and Continuous Intelligence■ Data Growth
    • How Big is 7.9 Zettabytes of Data?The Library of Congress147 Million AssetsUp to 462 terabytes of digital datain 2011 1.8 zettabytes of data will be created & replicatedExpected to increase to 7.9 zettabytes by 2015The equivalent of 18 million Libraries of congressCenturyLink, Inc. Resource Center, Infographic:Data Deluge – 8 Zettabytes of Data by 2015, 2011
    • Big Data MattersTransformational business value from dataDrive BetterProfit MarginsNewStrategies andBusiness ModelsOperationalEfficienciesBusinessValueVelocityVolumeVarietyMobileCRM DataPlanningOpportunitiesTransactionsCustomerSales OrderThingsInstant MessagesDemandInventorySource:SAP AG
    • Big Data for Big VisionSource: Utopia
    • Big Data inReal-Time
    • Key trend: real-time enterpriseRethinking the way we workReal-time analysis – When it happens, you know itAccelerate Business Performance – with 3600x fasteranalyticsUnlock New Insights – interrogate more granular dataIncrease Business Productivity – Real time data availablefor consumption on any device.Improve IT Efficiency – manage large data volumes whilereducing IT complexity
    • Picture this!
    • Source: VoltDB
    • Source:VoltDB
    • PRIMER ON NEW CONCEPTSHADOOP• Open source S/W framework for MapReduce on large data sets in a distributed filesystem• Storage Layer: Hadoop Distributed File System (HDFS) – stores data in files(schema-free)• Application Programming Interface: MapReduce framework• Commercial support available from – Cloudera, HortonWorks, IBM, EMC/Greenplum• SWOT• Strengths: scalable, cost effective, fault tolerant• Weaknesses: batch oriented, weak support for BI tools, tedious programming interface• Opportunities: coexistence in large installations can be lucrative (ComScore)• Threats: repurposed over time to become a general purpose DW or Analytics PlatformSource:Sybase
    • PRIMER ON NEW CONCEPTSMAPREDUCE• A framework for distributed computing on large data sets on clusters of computers.Processing can occur on data from file systems or DBMS.• The framework is based on map (distribute work) and reduce (collate & output results)steps. Map and Reduce functions can be written and accessed via many languages.• MapReduce technique is widely used for pre-processing web logs, text data, graphdata, …Examples: Find web links for search phrase, find patterns in social network graphsSource:Sybase
    • PRIMER ON NEW CONCEPTSHIVE• Open source data warehousing framework for SQL like interface to Hadoop / Amazon• Storage Layer: Hadoop Distributed File System (HDFS) and Amazon S3 FileSystem• Application Programming Interface: HiveQL – a variant (and subset) of ANSI SQL• Commercial support: None today• SWOT• Strengths: makes Hadoop more usable due to declarative nature of HiveQL• Weaknesses: does not cover much of SQL (very rudimentary), so usefulness is limited• Opportunities: coexistence in large installations with purely SQL based applications• Threats: with more maturity of its SQL, it can become a threat to commercial DW DBMSSource:Sybase
    • PRIMER ON NEW CONCEPTSNOSQL (NOT ONLY SQL) – A MOVEMENT• A broad class of DBMS that differ from the classic RDBMS with following characteristics• May not require fixed table schemas and tend to avoid join operations• Key value store and analysis – put (key, value), get(key), MapReduce(keylist, fns),…• Run on large number of commodity machines (usually in the cloud)• Data (hash) partitioned and replicated among these machines• Relaxed data consistency requirement• Document store formats (JSON, XML) and Web 2.0 APIs (PHP, PERL, Python, Ruby)• Examples:• NoSQL techniques primarily used for document & multi-media mgmt and search, web urlindexingRead more: http://horicky.blogspot.com/2009/11/nosql-patterns.htmlSource:Sybase
    • BIG DATA LANDSCAPE IS LIKE LONDON MAP For Source blog: Click please
    • Know yourself and your needs !
    • In-Memory Platforms open new era in IM WorldEliminate Redundant Layers; Combine Transactions & AnalyticsSource:SAP
    • Information Management LandscapeIntegration, Federation, Operational BIHistoricalEvent InitiatedUser InitiatedReal TimeDataFederationDataIntegration(ETL based)OperationalBusinessIntelligence /(EventProcessing)New MarketSegmentBusiness question are send to dataand not data to business questions
    • Faster Time To Value (React Quicker, Create Better Value)Continuous Intelligence creates another market in BI/BAAction TakenTimeValueLatencyEvent HappensData StoredAction ValueSource:SAP
    • Example of Complex Event ProcessingTradtional BI: “How manyFraudulent credit card transactionsoccurred last week in İstanbul?”1 2 3 4 5 6 7 8 9timeComplex Event Processing: “when three credit cardauthorizations for the same card occur in any five secondswindow, deny the requests and check for fraud.”Source:SAP
    • TOP 10 CIO Business and TechnologyPrioritiesSource: Gartner com (http://www.gartner.com/newsroom/id/2304615)
    • Source: B-eye Network
    • Business Intelligence Business AnalyticsSource: http://www.timoelliot.com/
    • Mobility & Mobile Intelligence Soars !
    • Source: Forbeshttp://www.forbes.com/sites/bitsyhansen/2012/03/29/data-visualization-landscape/Data Visualization is profession! Dedicate yourself !Tableau Software
    • Source:http://www.timoelliot.com/
    • Socialytics is in BI/BAMichael FauscetteSource:
    • Hot appliance market will be around for a while butsooner or later it will diminish with for paradigm
    • SLIDE56
    • BI &Predictive Analysisconverges and gets simplifiedSource: SAP
    • IN-DB ANALYTICS and Revolution Analytics will bedemanded more
    • COSTS
    • The new way datawarehousingSource: Christian Grant, University of Florida 2011
    • SLIDE 61learn as much as possible
    • Rule of thumb ‘’ Business and IT must be together!!Right Balance is ‘SUCCESS’Source : Saama
    • Upcoming BI/BA world will be sodifferent than last two decades..
    • Source: http://www.oralytics.com/2012/06/data-science-is-multidisciplinary.html
    • be persistentwith hardwork and BI/BA knowledge 
    • Simplicity is not the opposite ofcomplexity: complexity is a fact ofthe world, whereas simplicity is inthe mind.Stephen FewPerceptual Edge
    • http://www.yellowfinbi.com/YFCommunityNews-8-reasons-why-embedded-Business-Intelligence-beats-DIY-119889Finally, not only embedded BI but alsoembedded BA will be coming soon !!!
    •  Confusing terminology makes the value of BI hard to determine The mission and importance of BI are unclear There’s no clear link to business strategy and critical businessprocesses BI/BA is about technology Hard –long and complex project ! BI is about Data Hard to practise BI/BA Expensive and Costly Datamining is too hard , we need pHD guys Big Data brings complexity with no clear benefits Social Media Analysis is something different from BIPlease fight against ;Source:Spotfire
    • Follow Japanesee Proverb ‘ Never give up’
    • For source: Click
    • http://www.getbusymedia.comBI/BA Vendors can’t avoid ‘Innovation’End Users define ‘winners’
    • Awareness becomes Predictive Analytics
    • Big Thanks to Doguş UniversityIndustry Vertical Student Club
    • ExecuseSome of the visuals or materials used inpresentations have been historically collectedduring internet research. Despite the fact that Ihave tried to write all sources, there are somemissing source names or unknown sources. I ampleased to correct promptly missing/wrong names,if you know the sources and can inform me.Thank you for understanding and accept my sincereexcuses if I cause any inconvenience