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SAS and Teradata Partnership Overview October, 2007 Headlines SAS and Teradata Enter into Strategic Partnership BusinessIntelligence.com – 10/8/07 “In-database analytics is a key development that promises to improve efficiency and effectiveness of business analytic solutions. It will decrease data movement and increase performance, thus enabling IT to better respond to the decision support needs of business decision makers.” Dan Vesset, Vice President, Business Analytics, IDC 2 SAS - Teradata CEO’s Announcing Strategic Partnership October, 8th 2007 Mike Koehler, president and chief executive officer (CEO) of Teradata Jim Goodnight, chief executive officer (CEO) of SAS 3 Session Topic: Benefits of SAS and Teradata Partnership Jeff Mudd – Senior Account Executive Support All Operating Divisions within DHHS Maximize Value via SAS Enterprise License Agreement (ELA) CMS SAS users supporting key initiatives: Center for Medicaid Management (CMM) Office of Actuary (OAC) Office of Clinical Standards and Quality (OCSQ) Office of Research and Development (ORDI) Program Integrity / Program Safeguard SAS & Teradata integration leveraged across most SAS offerings What does this announcement and integration mean for CMS ? 4 IT Infrastructure to Support CMS Mission MACs FFS PLANs Part C & D States Medicaid QICs Enterprise Data Center (EDC) Industry Partners Streamlined MMA Applications HIGLAS Modernized FFS Claims Applications Medicaid Related Applications Medicare Appeals System Web Services QIO Related Applications Integrated Data Repository Medicare Beneficiary Medicare Part A & B Claims Medicare Part D Claims Medicaid Beneficiary Enrollment Standard Interfaces (EDI) SSA OPM RRB Standard Interfaces (Portal) Standard Front End e-Health Initiatives e-Gov Initiatives Medicaid Claims Source: CMS RDDC CMS Internal Users •Internal Extracts •Public Use Files HHS Opdivs (FDA, NIH…) FHA Partners (VA, DOD…) QIO’s, Program Integrity 5 Agenda • Marketplace Challenges • Partnership Vision and Benefits • Outside Perspective • Joint Development Roadmap • SAS and Teradata Center of Excellence • Summary 6 Market Trends on Decision Making Stayed the same, 29% “…the number of decisions you make daily has...” “… the amount of data available to you is...?” Increased, 68% More Decisions 68% say number of daily decisions has increased over last year “… the complexity of the business decisions you are making has ...?” Decreased , 4% Less complex, 9% More complex, 45% More Complexity 45% say decisions are more complex About the same, 46% Increasing, 4% Increasing slightly, 40% Not increasing, 4% Tripling, 8% More Data 96% say data is increasing 52% say data is doubling or tripling every year Doubling, 44% Source: The 2006 Teradata Report on Enterprise Decision-Making 7 Technology Barriers to Decision Making Limitations: > Insufficient analytical capabilities and usage > Inability to capture value from growing volumes of data > Data movement and data quality issues > Data redundancy & high infrastructure costs > Database architectures that do not scale Requirements: > > > > > Faster analytic answers, faster time to market Reduced data movement and latency issues Enhanced effectiveness - analysts focused on higher value tasks Improved data quality and data consistency Lower total cost of ownership and investment protection 8 SAS and Teradata Strategic Partnership Vision and Value Already Hundreds of Shared Customers Globally! Partnership vision • To create breakthrough customer value > True scalable analytic solutions > Improved time to value > Reduced technology infrastructure costs Enhanced Performance Enhanced Productivity •Entertainment Company • Financial Services Company > Reduces analytic processing from 36 to one hour > Opportunity to redeploy 500 SAS analysts from data prep to customer and fraud analysis More Choice Lower TCO • Major North America Insurer • Major Bank > Reviewing new SAS BI opportunity with Teradata due to data integration and partnership > Eliminates data redundancy and reduces IT costs by integrating SAS and Teradata 9 SAS and Teradata Background SAS Teradata • Global reach, local presence • Leader in Data Warehousing > Global presence > 43,000 customer installations > Hundreds of local user groups > $1.9B revenue in 2006 • Market leader for: > Business intelligence > Data quality and integration > Data mining and analytics > Horizontal/Vertical Solutions • Breadth and depth of tools > General/specialized analytics > 40+ countries worldwide > 850+ global customers > $1.6B revenue in 2006 • Enterprise view > Smarter, faster decision making > Analytical technologies and solutions • Highest performing technology > Parallel environment > Speed and scalability > Relational view of data 10 The SAS and Teradata Strategic Partnership • Teradata is SAS’ first RDBMS partner for its “In-Database” initiative • Joint Product Roadmap • Dedicated R&D for Optimizing SAS for Teradata • The SAS and Teradata Center of Excellence • SAS and Teradata Executive Customer Advisory Board 11 Outside Perspective "In-Database Analytics is a key development that promises to improve efficiency and effectiveness of business analytics solutions…” > Dan Vesset, Vice President, Business Analytics, IDC "The ability to achieve a higher level of integration with both SAS and our Teradata platforms will provide both increased operational efficiencies and enhanced information analytics...” > Mark Halloran, CIO, Medco Health Solutions, Inc. “As a result of integrating SAS and Teradata technologies, we have reduced overall processing time to run our forecasting model from 36 hours to 1 hour and 15 minutes.” > Thomas Tileston, Vice President of Business Decision Support, Warner Home Video 12 SAS® In-Database Processing for Teradata Current Capabilities Future Option Analytic Modeling Analytic Modeling SAS SAS Data SAS Scoring Data SAS Modeling Teradata EDW SAS Scoring Teradata EDW 13 Joint R&D Roadmap 4Q 2007 1st Half 2008 2nd Half 2008 2009+ Phase 0 Phase 1 Phase 2 Futures • Optimize current tools and solution approach • Begin integration of SAS functions into Teradata • Optimize SAS functions within Teradata • Complete ELT support • Certify Retail applications on Teradata • Certify joint data mining solution > SAS/Enterprise Miner > Teradata ADS Generator > SAS/Teradata investments • Improved data integration options • Integrate SAS AML Analytics with Teradata • SAS Credit Risk database on Teradata • SAS Risk solution on Teradata > Map SAS to Teradata Financial Services Logical Data Model • Continued evaluation of industry solutions on Teradata • Enhance Teradata Demand Chain Mgmt • Managed SAS/Teradata environment Benefits • Improve SAS end-user productivity • Maximize current SAS/Teradata investments • Minimize data movement • Deploy more SAS models in Teradata • Faster data access • SAS analytics in Teradata • Improved data integration • Optimize SAS/Teradata investments • Minimize data movement • Tighter application integration 14 The SAS and Teradata Center of Excellence Business Value: A strategic dedicated team of solution & technical architects that can consult with customers and assist them in developing a roadmap to optimize & improve the efficiency of their technology platform’s performance. Domain Knowledge and Best Practices: > > > > > SAS products, applications, and solutions Data integration, business intelligence, and analytical software deployment Teradata data warehousing, client tools, and data modeling Financial Services, Insurance, Healthcare, Retail and Communications IT infrastructure (servers, storage, database, network) Deliverables include: > > > > Architecture assessments and roadmap recommendations Proof-of-concepts Benchmarking and sizing analysis Customized consulting services 15 Summary Together, the SAS and Teradata partnership delivers: > A compelling and robust business intelligence and analytics environment from two industry leaders > Solutions that allow companies to focus on higher value business opportunities – Expands the use of analytics to increase competitive advantage – Delivers top-line and bottom-line growth faster > A reduction in the complexity and cost for decision making – Reduced data movement and latency issues – Improved data quality and data consistency – Lower total cost of ownership and investment protection 16 Highlights from Initial SAS and Teradata R&D Integration Experiments … • Based on a multi-node Teradata machine • Move work from a SAS procedure into the database • Move SAS formats to the database • Move a scoring application into the database • Executing SAS stored processes from the database server 18 Experiment #1 • Make PROC FREQ more database aware 19 Descriptive Statistics – Your basic Crosstab proc freq data=credit_data; table state * credit_score; 20 Proc Freq Today Teradata SAS® Session proc freq table state*credit; SQL Access Engine 21 SAS/ACCESS MVA SAS® Proc Freq SAS/ACCESS to Teradata • Multiload support • Fastload support • Fastexport support • Multi-statement insert •TPT support (near future) • Implicit and Explicit SQL support SAS I/O Supervisor Access Engine 22 Proc Freq Today Teradata SAS® Session proc freq table state*credit; Request All Rows SQL select state, credit Access Engine 23 Proc Freq Today – BIG data pull Teradata SAS® Session proc freq table state*credit; Request All Rows SQL select state, credit Access Engine 24 Future: Proc Freq Teradata SAS® Session proc freq table state*credit; SQL Access Engine 25 Future: Proc Freq – Smarter SQL Teradata SAS® Session proc freq table state*credit; select count(*), state, credit from … group by state, credit SQL Access Engine 26 Future: Proc Freq – Smarter SQL Teradata SAS® Session proc freq table state*credit; select count(*), state, credit from … group by state, credit SQL Access Engine 27 Future: Proc Freq – Smarter SQL Traditional Freq Test Rows Returned Push Down Elapsed Time Rows Returned Elapsed Time 1 9,000,000 55 51 2 Total 9,000,000 55 51 2 28 Experiment #2 • Running SAS Formats on the database server 29 Bin States in Regions – There is always a catch. proc freq data=credit_data; format state $region.; table state * credit_score; 30 Region Format – Something a User would do proc format; value $region 'AL'='South' 'AK'='West' 'AS'='Other' 'AZ'='West' 'AR'='South' 'CA'='West' 'CO'='West' ... 31 User formats require managed database objects Teradata SAS® Session region_fmt.xml SQL proc format; value $region 'AL'='South' 'AK'='West' 'AS'='Other' 'AZ'='West' 'AR'='South' 'CA'='West' 'CO'='West' ... SAS Format Library putc() 32 Proc Freq Tomorrow Teradata SAS® Session proc freq table state*credit; SQL select count(*), putc(state, "$region.") as region, credit from… group by region, credit Access Engine SAS Format Library putc() 33 Proc Freq Tomorrow Teradata SAS® Session proc freq table state*credit; SQL select count(*), putc(state, "$region.") as region, credit from… group by region, credit Access Engine SAS Format Library putc() 34 Proc Freq Tomorrow – Smarter SQL Calling SAS provided UDF’s Traditional Freq Test Rows Returned Push Down Elapsed Time Rows Returned Elapsed Time 1 9,000,000 55 51 2 2 w/ format 9,000,000 151 51 11 3-Sort 10,000,000 592 3-Freq 0 5 109 3 4 1,499,600 29 51 3 5 9,980,000 180 15,767 11 39,479,600 1,012 15,818 32 Total 35 Experiment #3 • Move the Scoring work to the Database… 36 Scoring Today BIG data pull and push Teradata SAS® Session data out; set cust; <<score code>> Request All Rows SQL select * from cust Access Engine 37 Scoring Tomorrow – Score at the data Teradata SAS® Session proc sql create table out as (select a,b,c, score(a,b,c) as score… SQL create table out as (select a,b,c, score(a,b,c) as score… Access Engine SAS TSPL Library score() 38 Scoring – 6,000,000 rows Insert into sas_usr.myresults Sel clage,clno,debtinc,loan,"VALUE",job,reason ,ninq,delinq,mortdue,yoj,derog,id ,sas_usr.udf_i_bad(clage,clno,debtinc,delinq,derog,j ob,loan,mortdue,ninq,reason,"VALUE",yoj) as score From hmeq; 224 225 227 228 229 230 231 data reslib.results (bulkload=yes); set scorelib.hmeq_score; *------------------------------------------------------------*; * EM SCORE CODE; * VERSION: 5.2; * GENERATED BY: carynt\sasled; * CREATED: 09AUG2006:13:57:12; 39 In Database Scoring vs. External Scoring 800,000 750000 Obs / Second Scored 700,000 625000 600,000 500,000 500000 400,000 375000 300,000 250000 200,000 Optimized I/0 125,000 100,000 16,400 77,040 0 1 2 3 4 5 6 Number Teradata Nodes External Process In place via UDF 40 Experiment #4 • Executing SAS stored process server from DBMS 41 SAS Stored Process - Simple Values Call sasStoredProcess(“calcRisk”,balance) Select … /* Any sas code */ SAS $20,000.00 Foundation Teradata account 42 Experiment Results • Reduced Data Pull • Execute SAS Specific Syntax on the DBMS • Leverage MPP Scalability of Teradata • Processing Options 43