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101 ab 1345-1415

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  • 1. 巨量分析BigData,發掘企業新契機,讓不可能變可能SAS巨量分析事業處產品顧問林輝倫( Allen Lin )2012/9/11http://www.sas.com/offices/asiapacific/taiwan/high-performance-analytics/index.html Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 2. SAS是企業成長最忠實的夥伴 全球企業;在地支援  成立於 1976年  總部:美國 北卡羅來納州 卡麗  全球52個國家有400+個據點  台灣分公司成立於1989年(20年以上) 深耕台灣;國際接軌  全球10,000+位員工 2011營收:US $2.75 Billion  台灣50+位 研發經費:24 % ($660 million) 全球超過55,000個客戶  台灣300+客戶  Fortune 500前100大中有97家採用 SAS  BusinessWeek 50 List中有41家採 用SAS 2 Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 3. SAS 致力於進階商業分析已超過35年 傳統的商業智慧 進階的商業分析 Business Intelligence Advanced Analytics 最適化分析 警示 商業智慧 Optimization Alert 進階商業分析 預測模型 多維度分析 Predictive Modeling OLAP 過去發生了什麼? 文字分析 即時性報表 Text Analytics 未來會發生什麼? Ad-hoc Report 趨勢分析 標準報表 反應型決策模式 Forecasting Standard Report 統計分析 主動型決策模式 Statistical Analysis No. 1 World Leader In Business AnalyticsSAS leads Advanced Analytics Market by Wide Margin (IDC, June 2011) Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 4. 巨量資料的挑戰 趨勢 資料量 VOLUME 資料種類 VARIETY 資料產生的速度 VELOCITY 資料蘊含的價值 VALUE資料量大小 現在 未來 Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 5. 當進階商業分析遇到巨量資料… 進階商業分析 SAS高效能分析巨量資料Big Data + Advanced Analytics = SAS High Performance Analytics 能夠充分運用平行處理資源進行高效能進階分析的廠商 讓分析不需受限於資料種類、樣本大小、變數量、及歷史資料的長短 讓充分的情境模擬分析可於短時間內完成 讓分析人員得以解決更多更複雜的業務問題 讓即時分析、預測、與模擬的結果融入於決策過程中 支援Hadoop, Greenplum與其他資料庫廠商等 http://www.sas.com/offices/asiapacific/taiwan/high-performance-analytics/index.html Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 6. SAS High-Performance Analyticsfor Greenplum Offering SAS Visual Analytics– Visualize ALL your data – billions of records • -- to understand the variables that your datasets contain. Uncover relationships and PREDICT correlations in your data. IVE MODELI NG DATA EXPLORATION SAS HPA•(the product) –  Allows in-memory modeling against entire data VARIABL Develop predictive models in E memory alongside distributed sets on a specialized Greenplum appliance relational databases. Data is not SELECTI physically moved, SAS processing is brought to the ON database appliance. Models can be built on ALL of the data. ANALYTIC MODEL  Increases business value of models by DEVELOPMENT LIFECYCLE improving model selection  Dramatically accelerates the analytic lifecycle MODEL DEPLOYMENT process for select modelsScoring Accelerators –Translate Enterprise Miner models intodatabase-specific functions to executein database. Copyright © 2012, SAS Institute Inc. All rights reserved. 6
  • 7. SAS High-Performance AnalyticsKey Components 7 Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 8. Approach: Use Access Engines SAS Server Appliance Master Workers Access Enginelibname GP joe; SELECT delay SELECT delay FROM flights FROM flightsproc means data=joe.flights; var delay;run; SELECT delay FROM flights Big Data 8 Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 9. Inside the Database – SQL and UDF’s SAS Server Appliance Master Workers Access Enginelibname GP joe; Aggregator UDF UDF that accumulates X’Xproc reg data=joe.flights; model delay=length day;run; TKTS X’X X’X 9 Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 10. SAS高效能分析解決方案 – 架構說明SAS® IN-DATABASE Traditional Architecture In-Database Architecture SAS SAS SAS SAS Model Model M M Modeling Modeling Model Scoring Translation Modeling Scoring Modeling ADS ADS ADS Analytical Scoring Data Data Preparation Preparation Data Analytical Data Scoring Data Data Extracts Preparation Preparation Extracts In-database Scoring Database /DataDatabase /Data Warehouse SAS Modeling ScoringWarehouse Model ADS ADS Greenplum Model Development Model Deployment Model Development Model Deployment Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 11. SAS High-Performance AnalyticsKey Components 11 Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 12. Alongside-the-Database SAS Server Appliance General Captains tkgridlibname GP joe; MPI TK TK TKproc hpreg data=joe.flights; TK TK class airline day(split); model delay=airline day duration …; selection method=lasso;run; SQL SQL SQL SQL SQL Access Engine Master Workers 12 Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 13. SAS高效能分析解決方案運作方式SAS® IN-MEMORY ANALYTICS Greenplum Node SAS High-Performance Analytics Appliance Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 14. SAS High-Performance Analytics:Architecture Submit a program from a SAS client session (eg. HPLOGISTIC) proc hplogistic data=GPlib.sgf_binary; class A B C; model y = a b c x1 x2 x3; performance details host="green1"; run; 14 Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 15. SAS High-Performance Analytics:Architecture Master Request is sent to the appliance and received by the Master Node Worker Node 1 Worker Node 2 Worker Node N 15 Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 16. SAS High-Performance Analytics:Architecture Master Worker Node 1 Worker Node 2 Worker Node N Analytical Computation and data request sent to the worker nodes 16 Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 17. SAS High-Performance Analytics:Architecture Master Worker Node 1 Worker Node 2 Worker Node N Data request sent to the database, data slice moved into memory 17 Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 18. SAS High-Performance Analytics:Architecture Master Worker Node 1 Worker Node 2 Worker Node N Analytic Processing with internode communication 18 Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 19. SAS High-Performance Analytics:Architecture Master Worker Node 1 Worker Node 2 Worker Node N Worker node results returned to the Master Node, finalize computation 19 Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 20. SAS High-Performance Analytics:Architecture Root Node Worker Node 1 Worker Node 2 Worker Node N Result returned to the client 20 Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 21. SAS高效能分析解決方案 – SAS HAP與EM整合SAS® IN-MEMORY ANALYTICS 高效能資料採礦與 SAS EM整合,提供 多個高效能運算分 析節點 採礦處理流程可進 行自動化處理 與模型比較整合 Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 22. SAS® HPA MODELING RESULTSServerVariable Selection Classification and Prediction Text Mining 22 Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 23. SAS高效能分析解決方案 (VISUAL ANALYTICS)SAS® IN-MEMORY ANALYTICS Central Entry Point Integration Role-based Views DATA PREPARATION EXPLORER DESIGNER MOBILE • Perform ad-hoc analysis • Create dashboard style • Native iOS application • Monitor SAS® LASR™ and data discovery reports for web that delivers interactive Analytic server • Load and join data or mobile reports created in the • Create calculated designer columns SAS® LASR™ ANALYTIC SERVER Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 24. SAS High-Performance AnalyticsKey Components 24 Copyright © 2012, SAS Institute Inc. All rights reserved.
  • 25. SAS High-Performance Analyticsfor Greenplum Offering SAS Visual Analytics– Visualize ALL your data – billions of records • -- to understand the variables that your datasets contain. Uncover relationships and PREDICT correlations in your data. IVE MODELI NG DATA EXPLORATION SAS HPA•(the product) –  Allows in-memory modeling against entire data VARIABL Develop predictive models in E memory alongside distributed sets on a specialized Greenplum appliance relational databases. Data is not SELECTI physically moved, SAS processing is brought to the ON database appliance. Models can be built on ALL of the data. ANALYTIC MODEL  Increases business value of models by DEVELOPMENT LIFECYCLE improving model selection  Dramatically accelerates the analytic lifecycle MODEL DEPLOYMENT process for select modelsScoring Accelerators –Translate Enterprise Miner models intodatabase-specific functions to executein database. Copyright © 2012, SAS Institute Inc. All rights reserved. 25
  • 26. • SAS是充分運用平行處理資源進行高效 能進階分析的廠商WHY SAS 巨量分析 • 讓分析人員得以解決更多更複雜的業務 問題 • 讓即時分析、預測、與模擬的結果融入 於決策過程中 • 讓原本很多不可能的服務與應用變可能 最高準確 度之預測 無與倫比 最大廣度 之企業績 及深度之 效 分析 最佳之執 行效能 http://www.sas.com/offices/asiapacific/taiwan/high- performance-analytics/index.html Copyright © 2012, SAS Institute Inc. All rights reserved.