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SAS aster data big data dc presentation public

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  • 1. SAS In-Database Michelle Wilkie, Product Manager Copyright © 2009, SAS Institute Inc. All rights reserved.
  • 2. Agenda  Overview of SAS  SAS product and solutions  SAS In-Database overview  SAS and Aster Data partnership Copyright © 2009, SAS Institute Inc. All rights reserved.
  • 3. 2009 Worldwide Revenue $2.31 Billion Copyright © 2009, SAS Institute Inc. All rights reserved.
  • 4. Customers 45,000 sites world-wide 1,389 customers added in 2009 Copyright © 2009, SAS Institute Inc. All rights reserved.
  • 5. Copyright © 2009, SAS Institute Inc. All rights reserved.
  • 6. SAS® for Federal Government Federal Financials Operations Fraud & Improper Payments Disaster Preparedness/Emergency Response Financial Risk Cybersecurity Audit & Compliance Logistics Financial Visibility Green IT/Sustainability Budget & Performance Integration Data Center Optimization Cost Management Operational Risk Human Capital Organization Workforce Planning & Analysis Performance Management Recruitment & Retention IT Management Healthcare Reporting Copyright © 2009, SAS Institute Inc. All rights reserved.
  • 7. SAS® for Banking Risk Customers Firmwide Risk Customer Experience Analytics Credit Risk/Counterparty Risk Customer Profitability & Relationship Pricing Market Risk Acquisition, On-Boarding & Retention Asset/Liability Management Cross-Sell & Up-Sell Operational Risk Collections Optimization Fraud/Financial Crimes Marketing Optimization Finance Operations Regulatory Compliance Performance Measurement & Reporting Capital Allocation & Management Workforce Planning & Management Legal/Financial Consolidation & Reporting IT Performance Management Cost & Profitability Management Sustainability/Green Initiatives Copyright © 2009, SAS Institute Inc. All rights reserved.
  • 8. What is SAS® In-Database? Integration In-Database SAS Applications are integrated to The ability to embed and use leverage standard database SAS functions, framework, features. processes and applications inside the database. Examples Examples • SAS Format function • Database Specific SQL • SAS Scoring functions • SQL functions • Predictive Modeling Functions • Stored Procedures Copyright © 2009, SAS Institute Inc. All rights reserved.
  • 9. Value Proposition SAS® In-Database Capability Value Streamline Analytic • Minimize data preparation Workflow • Accelerate data discovery • Decrease time to value Scalability and • Reduce data movement Performance • Leverage MPP systems for parallelization Data Consistency • Reduce Data Redundancy • Reduce Information Latency Fit for IT • Enable Data Governance • Increase Hardware Utilization • Integrate with Resource Management • Facilitate standardization on a single enterprise analytics platform Copyright © 2009, SAS Institute Inc. All rights reserved.
  • 10. SAS® In-Database Overview Traditional Architecture In-Database Architecture Analytic Modeling Analytic Modeling SAS Data Data Preparation Preparation Scoring SAS SAS Modeling Scoring SAS C & Data PMML Scoring Preparation Data Warehouse / Database Data Warehouse / Database Copyright © 2006, SAS Institute Inc. All rights reserved. Company confidential - for internal use only
  • 11. SAS In-Database Direction Short-term To streamline and optimize the customers’ business process Data Data Analytics Reporting Preparation Exploration Long-term A database will be the next HOST in which SAS can be deployed. Allowing SAS to leverage the high performance compute architecture and database features seamlessly. Copyright © 2009, SAS Institute Inc. All rights reserved. 11
  • 12. Design Principles SAS® In-Database Principle Reduce Data Movement • Push data-intensive work to database • Make use of database resources: disks and CPUs • Generate optimized SQL • Re-use SAS C code libraries when needed Preserve SAS user • SAS Language skills experience • SAS Procedures experience • SAS Environment knowledge Maintain SAS • Scalability in Rows and Columns Standards • Numerical accuracy and precision • Statistical integrity • Software quality Copyright © 2009, SAS Institute Inc. All rights reserved.
  • 13. + Copyright © 2009, SAS Institute Inc. All rights reserved.
  • 14. In-Database Scoring select * from sas_score( on mytable sas_code(’hmeq.sas') format_xml(’fmt.xml') ); Aster nCluster Queen Publishing Agent Worker Worker Worker SAS Schema 14 Copyright © 2009 Aster Data Systems and SAS Institute Inc. All rights reserved.
  • 15. In-Database DATA Step Example Pivoting transactional data into a time-series format data aster.out; keep item_num item_desc ID ID jan feb mar ...; array month_qty[12] jan feb mar ...; set aster.in; by item_num; if first.item_num then do i = 1 to 12; month_qty[i] = .; end; select * from m = month(datepart(processed_dttm)); sas_data_step( month_qty[m] + item_qty; on retail_trans partition by item_num if last.item_num then sas_code('pivot.sas') output; ); run; 15 Copyright © 2009 Aster Data Systems and SAS Institute Inc. All rights reserved.
  • 16. Copyright © 2009, SAS Institute Inc. All rights reserved.