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SAS and
June 2011




            Copyright © 2010 SAS Institute Inc. All rights reserved.
Who is SAS: The Leader in Enterprise Analytics Software
Basic company statistics:
•   Founded 1976: 11,000+ employees in 400+ offices
•   600+ global alliances
•   Revenues have increased every year
•   2010 worldwide revenue $2.43 B
•   24% of revenues reinvested in R&D
•   Ranked in Leader’s Quadrant for Gartner’s 3 key areas for
    Analytics: Data Integration, Analytics and Reporting
•   IDC: SAS is leader in Analytics with a 34.5% market share
                                                                                                                  Services
                                                                                                         Retail
Customers:                                                                                                4%
                                                                                                                   11%
                                                                                       Other                                       Financial Services
•   4.5 million users worldwide                                                         2%                                               42%
•   50,000+ sites in 114 countries                                       Manufacturing
                                                                             6%
•   92 of the Top 100 Fortune Global 500
                                                                           Healthcare
•   9 of 10 Leading Media Agencies                                       & Life Sciences                                                Communications
                                                                                                                                            8%
•   Over 1,000 Universities                                                     8%

•   Over 90% of US Federal Agencies                                                       Government                                 Education
                                                                                             14%                  Energy & Utilities    3%
•   All 50 US State Governments                                                                                         2%                              2



                                             Copyright © 2010, SAS Institute Inc. All rights reserved.
SAS and Netezza Partnership

 R&D
    SAS In-database partner
    Several Netezza TwinFin’s at SAS
    SAS Software at Netezza
    Mutual resource investments
 Marketing
    Joint sponsors of annual conferences – Enzee and SAS Global
     Forum/M2010
 Sales
    250+ mutual accounts
    60+ SAS Access to Netezza customers
    SAS Scoring Accelerator for Netezza now in production
                                                                                    3



                        Copyright © 2010, SAS Institute Inc. All rights reserved.
SAS Specific Products for Netezza
 SAS® Access to Netezza
    Provides optimized read/write connectivity for Netezza data
     appliances
    Allows fast connection to NZ for loading and extracting data to
     and from SAS tools & platform, and solutions - connect to
     Oracle, DB2, SQL server, and more
 SAS® In-Database
    SAS® Scoring Accelerator for Netezza
      » Allows the SAS analytic models to execute inside the
        Netezza appliance
      » Deploys models quickly, reduces data movement, and
        leverages the power of the Netezza appliance


                                                                                    4



                        Copyright © 2010, SAS Institute Inc. All rights reserved.
Joint Business Value Proposition and IT
     Value Proposition
    Business Value Proposition                                                                    IT Value Proposition
•   Increase Analysts‘ Productivity (not just a fast                     •       Improved governance and data compliance
    report)                                                                      through centralized data

                                                                         •       Reduced data movement and latency
•   Fast – find answers quickly through improved
    integration                                                          •       Reduced costs for development and validation
•   Flexible – update business processes and                             •       Improved scalability and performance
    analysis without requiring IT support
                                                                         •       Lower TCO - greater leverage of existing
•   Simple – focus on exploring the business issue                               investment
    - not connectivity and data movement
                                                                         •       Supercharge SAS with Netezza’s high
•   Reduced time-to-model implementation                                         performance, scalable scoring
•   Leverage existing SAS knowledge and                                  •       Effective resource utilization via automatic code
    Netezza high-performance                                                     generation

                                                                         •       Reduced end-to-end processing time
                                                                         •       Simplified infrastructure to maintain and administer

                                                                         •       SAS Enterprise Miner model development process
                                                                                 is simple and easy to manage

                                                                         •       Score Database more frequently for better results      5



                                           Copyright © 2010, SAS Institute Inc. All rights reserved.
SAS and Netezza:
Integration and In-Database Processing
          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
                                                                            •Model Development



                                                                                                        6



                           Copyright © 2010, SAS Institute Inc. All rights reserved.
SAS and Netezza: Integration
 SAS ® Access to Netezza
 Allows SAS to Read/Write Netezza tables directly
 Implicit SQL support which generates Netezza specific SQL
 Supports Explicit SQL support and Pass-Through which
  enables more SQL functions to run in-database
 Communicates with Netezza and leverages its utility
  capabilities for optimized extracts and loads.
 Some In-Database processing by supporting publishing SAS
  Formats into Netezza




                                                                                  7



                      Copyright © 2010, SAS Institute Inc. All rights reserved.
SAS and Netezza: In-Database
       SAS ® Scoring Accelerator for Netezza
   SAS ® Scoring Accelerator:
      combines the statistical transformation and modeling methods available in SAS Enterprise
       Miner with the scalability and processing speed offered through the database system
      takes the complete scoring model code, the associated property file that contains model
       inputs and outputs and a catalog of user-defined formats, and deploys (or publishes) them
       within the data warehouse database
   Reduces Overall Costs: By moving the scoring function to the database, the common security,
    auditing and administration capabilities offered by the database are honored and leveraged
      Achieve higher model-scoring performance and faster time to results
      Increases Analysts’ productivity
      Improve accuracy and effectiveness of analytic models
      Reduce data movement and latency
      Eliminate model score code rewrite and model re-validation efforts (i.e. labor costs and error
       prone)
      Consolidate data to improve regulatory compliance
      Better manage, provision and govern data
   Bottom-line: Takes a SAS Enterprise Miner model and publishes it as a native database
    function (in your case a Netezza native function)                                               8



                                       Copyright © 2010, SAS Institute Inc. All rights reserved.
SAS ® Enterprise Miner – What does it do?

 Increase Revenue and/or Reduce Costs = More Profitable
 Three things necessary in order to effectively perform data
  mining
    Good historical data
    Strong modeling tool
    A Statistician
 FYI: SAS ® Rapid Predictive Modeler available in:
     SAS ® Enterprise Guide
     SAS Add-in to Microsoft Office (Excel only)

 Bottom-line: modeling tends to be used in order to better understand
  customers and as a result be able to be more profitable

                                                                                         9



                             Copyright © 2010, SAS Institute Inc. All rights reserved.
SAS Support on Netezza for Analytics Processing




                                                                            10



                Copyright © 2010, SAS Institute Inc. All rights reserved.
Netezza Enabled with SAS Software
      Database Connector                                                                             In-Database Analytics


                            Analyst                                                       P
P             Scoring                                                                     u
u                                                                                         s                                          Analyst
       Algorithms & Transforms
ll                                                                                        h
e                                                                                         e
d                                                                                         d
                                                                                          d
f                                                                                         o
r                                                                                         w
o                                                                                         n
m                                       DW
                                      Developer




                                                                                                          Scoring Algorithms & Transforms
          Recoded Scoring Processes                                                                  Published to Database as Scoring Processes



                                                                                                                                                  11
                                                                                                                                 Page 11
                                             Copyright © 2010, SAS Institute Inc. All rights reserved.
Netezza and SAS Connected
            Database Connector                                                            In-Database Analytics



Analytics     Data Extraction
              • Base SAS – Proc SQL
                                                                                             DataEnterprise Miner
                                                                                             • SAS Extraction
 Server       • SQL Pass-Thru Option                                                 • SAS Scoring Accelerator for Netezza
             • SAS/Access to Netezza


                        FA                                                                                FA
                        ST                                                                                ST
                                                                                                          ER




  Data
             • SAS/Access to Netezza                                                        • SAS Scoring Accelerator for Netezza
Warehouse     Data Extraction                                                                Data Extraction
                                                                                                    • Netezza Database
               • Netezza Database
                                                                                                   • In-Database Analytics

                                                                                                                                    12



                              Copyright © 2010, SAS Institute Inc. All rights reserved.
Why use SAS and Netezza?
 SAS for Analytic Insight/Solutions
    The Leader in Analytics Software
    SAS provides more analysis options/models with greater functionality
     than any other vendor
 Netezza appliances architecturally integrate database, server
  and storage into a single, easy to manage system that requires
  minimal set-up and ongoing administration.
    Netezza is know for its data warehouse appliance that delivers high
     performance out of the box.
 When you combine SAS and Netezza you get both the leader
  in analytics and the leader in warehouse appliances working
  together to provide the most efficient infrastructure for the
  customer to solve business problems
 Bottom Line: Working together SAS and Netezza help to
  accelerate your business processes                                                     13



                             Copyright © 2010, SAS Institute Inc. All rights reserved.
Customer Success Story – Marketing Agency
Providing Flexibility in Data Mining
                   Past Approach                                In-Database Approach
                Modeling data created in                        Modeling data created in
                      Warehouse                                       Warehouse

               Modeling performed in SAS                     Modeling performed in SAS
                   Enterprise Miner                              Enterprise Miner                               ABT



               Scoring data created and                       Scoring data created and
               aggregated in Warehouse                        aggregated in Warehouse
                                                                                                         SAS Enterprise
                                                                                                             Miner
                Enterprise Miner Model                         Enterprise Miner Model
               converted to STAT code –                       PUBLISHED into RDBMS
                REGRESSIONS ONLY                                 for use – Scoring
                                                               Algorithms available:
                                                                    •REGRESSION
                                                                   •DECISION TREE
                                                                 •NEURAL NETWORK
                                                                  •GRADIENT BOOST
                                                              •PARTIAL LEAST SQUARES
                                                             •SUPPORT VECTOR MACHINE           Scoring          Scored
                                                                                                ABT              Data
              Data extracted from                           Data scored in SAS and                       Scorin
              Warehouse                                     remains in Warehouse
                                                                                                          g in
              Data scored in SAS                                                                         Wareho
                                                                                                          use
              Data imported back into                                                         SAS
              Warehouse                                                                     Scoring
                                                                                           Accelerator                    14



                             Copyright © 2010, SAS Institute Inc. All rights reserved.
Customer Success Story – Propensity to Pay
      Providing Performance gains by Refactoring
            Flat file        Past Approach                                   In-Database Approach
OpSys1      extract       • Daily process begins                              • Daily process begins
                                                                                                          OpSys1
                          with flat file creation at                        at 4:00am with EDW load.
                         6:30am – SLA delivered
                                at ~9:30am.

                         • File transferred to SQL                            • All operational data
                         Server, limited to ~350K                          loaded directly to EDW. No
                        customer records based on                             flat file or intermediate
                              specific criteria.                              processing is needed.
             SQL                                                                                                    SAS
            Server                                                                                                Scoring
                                                                                                                 Accelerator
                          • 300 step process to                                 • 10 step process
                         support data mining life                            • Scoring and customer
           Customer               cycle.                                   selection done in-database
SAS
           Selection                                                       against ALL customer rows       EDW


                        30 MINUTES TO SCORE                                   4 MINUTES TO SCORE
                           ~350k customers                                       ~40M customers
                        Runs in ~ 3 HOURS                                 Runs in 12 MINUTES
                                                                                                                               15



                                      Copyright © 2010, SAS Institute Inc. All rights reserved.
Contacts & Links
SAS Alliance                                                        Netezza, an IBM Company
Kevin Go                                                            Tim McCarthy
    kevin.go@sas.com                                                          tmccar@us.ibm.com
    (919) 531-0680 - office                                                   (802) 291-0457
Tracye Giles                                                        Bernard Doering
     tracye.giles@sas.com                                                     bernard.doering@de.ibm.com
Links
•   Netezza homepage                                                   SAS and Netezza Brochure
•   SAS homepage

•   Netezza partner page for SAS

•   SAS Access to Netezza

•   SAS In-Database

•   SAS Scoring Accelerator for Netezza

•   SAS Scoring Accelerator for Netezza Documentation

•   SAS In-Database Technology

•   BASE SAS Procedures with In-Database processing                                                        16



                                      Copyright © 2010, SAS Institute Inc. All rights reserved.
Q/A
     More information

 About SAS on Netezza website:
   http://www.netezza.com/partners/comp-tech-detail.aspx?CTpid=1043
 SAS to deliver in-database analytic scoring for Netezza platform (press
  release):
   http://www.sas.com/news/preleases/SASScoringAcceleratorForNetezza.html
 Catalina Marketing gains unparalleled brand traction with SAS® and
  Netezza (press release):
   http://www.sas.com/news/preleases/CatalinaNetezza.html
 Catalina Marketing helps predict customer behavior with SAS® Enterprise
  Miner
  http://www.sas.com/success/catalina.html
 Foxwoods Plays a strong hand with SAS and Netezza
  http://www.netezza.com/releases/2008/release120808.htm


                                                                                           17



                               Copyright © 2010, SAS Institute Inc. All rights reserved.
Thank You




    Company Confidential - For Internal Use Only
Copyright © 2010, SAS Institute Inc. All rights reserved.

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SAS and Netezza Enzee universe presentation_20_june2011

  • 1. SAS and June 2011 Copyright © 2010 SAS Institute Inc. All rights reserved.
  • 2. Who is SAS: The Leader in Enterprise Analytics Software Basic company statistics: • Founded 1976: 11,000+ employees in 400+ offices • 600+ global alliances • Revenues have increased every year • 2010 worldwide revenue $2.43 B • 24% of revenues reinvested in R&D • Ranked in Leader’s Quadrant for Gartner’s 3 key areas for Analytics: Data Integration, Analytics and Reporting • IDC: SAS is leader in Analytics with a 34.5% market share Services Retail Customers: 4% 11% Other Financial Services • 4.5 million users worldwide 2% 42% • 50,000+ sites in 114 countries Manufacturing 6% • 92 of the Top 100 Fortune Global 500 Healthcare • 9 of 10 Leading Media Agencies & Life Sciences Communications 8% • Over 1,000 Universities 8% • Over 90% of US Federal Agencies Government Education 14% Energy & Utilities 3% • All 50 US State Governments 2% 2 Copyright © 2010, SAS Institute Inc. All rights reserved.
  • 3. SAS and Netezza Partnership  R&D  SAS In-database partner  Several Netezza TwinFin’s at SAS  SAS Software at Netezza  Mutual resource investments  Marketing  Joint sponsors of annual conferences – Enzee and SAS Global Forum/M2010  Sales  250+ mutual accounts  60+ SAS Access to Netezza customers  SAS Scoring Accelerator for Netezza now in production 3 Copyright © 2010, SAS Institute Inc. All rights reserved.
  • 4. SAS Specific Products for Netezza  SAS® Access to Netezza  Provides optimized read/write connectivity for Netezza data appliances  Allows fast connection to NZ for loading and extracting data to and from SAS tools & platform, and solutions - connect to Oracle, DB2, SQL server, and more  SAS® In-Database  SAS® Scoring Accelerator for Netezza » Allows the SAS analytic models to execute inside the Netezza appliance » Deploys models quickly, reduces data movement, and leverages the power of the Netezza appliance 4 Copyright © 2010, SAS Institute Inc. All rights reserved.
  • 5. Joint Business Value Proposition and IT Value Proposition Business Value Proposition IT Value Proposition • Increase Analysts‘ Productivity (not just a fast • Improved governance and data compliance report) through centralized data • Reduced data movement and latency • Fast – find answers quickly through improved integration • Reduced costs for development and validation • Flexible – update business processes and • Improved scalability and performance analysis without requiring IT support • Lower TCO - greater leverage of existing • Simple – focus on exploring the business issue investment - not connectivity and data movement • Supercharge SAS with Netezza’s high • Reduced time-to-model implementation performance, scalable scoring • Leverage existing SAS knowledge and • Effective resource utilization via automatic code Netezza high-performance generation • Reduced end-to-end processing time • Simplified infrastructure to maintain and administer • SAS Enterprise Miner model development process is simple and easy to manage • Score Database more frequently for better results 5 Copyright © 2010, SAS Institute Inc. All rights reserved.
  • 6. SAS and Netezza: Integration and In-Database Processing 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 •Model Development 6 Copyright © 2010, SAS Institute Inc. All rights reserved.
  • 7. SAS and Netezza: Integration SAS ® Access to Netezza  Allows SAS to Read/Write Netezza tables directly  Implicit SQL support which generates Netezza specific SQL  Supports Explicit SQL support and Pass-Through which enables more SQL functions to run in-database  Communicates with Netezza and leverages its utility capabilities for optimized extracts and loads.  Some In-Database processing by supporting publishing SAS Formats into Netezza 7 Copyright © 2010, SAS Institute Inc. All rights reserved.
  • 8. SAS and Netezza: In-Database SAS ® Scoring Accelerator for Netezza  SAS ® Scoring Accelerator:  combines the statistical transformation and modeling methods available in SAS Enterprise Miner with the scalability and processing speed offered through the database system  takes the complete scoring model code, the associated property file that contains model inputs and outputs and a catalog of user-defined formats, and deploys (or publishes) them within the data warehouse database  Reduces Overall Costs: By moving the scoring function to the database, the common security, auditing and administration capabilities offered by the database are honored and leveraged  Achieve higher model-scoring performance and faster time to results  Increases Analysts’ productivity  Improve accuracy and effectiveness of analytic models  Reduce data movement and latency  Eliminate model score code rewrite and model re-validation efforts (i.e. labor costs and error prone)  Consolidate data to improve regulatory compliance  Better manage, provision and govern data  Bottom-line: Takes a SAS Enterprise Miner model and publishes it as a native database function (in your case a Netezza native function) 8 Copyright © 2010, SAS Institute Inc. All rights reserved.
  • 9. SAS ® Enterprise Miner – What does it do?  Increase Revenue and/or Reduce Costs = More Profitable  Three things necessary in order to effectively perform data mining  Good historical data  Strong modeling tool  A Statistician  FYI: SAS ® Rapid Predictive Modeler available in:  SAS ® Enterprise Guide  SAS Add-in to Microsoft Office (Excel only)  Bottom-line: modeling tends to be used in order to better understand customers and as a result be able to be more profitable 9 Copyright © 2010, SAS Institute Inc. All rights reserved.
  • 10. SAS Support on Netezza for Analytics Processing 10 Copyright © 2010, SAS Institute Inc. All rights reserved.
  • 11. Netezza Enabled with SAS Software Database Connector In-Database Analytics Analyst P P Scoring u u s Analyst Algorithms & Transforms ll h e e d d d f o r w o n m DW Developer Scoring Algorithms & Transforms Recoded Scoring Processes Published to Database as Scoring Processes 11 Page 11 Copyright © 2010, SAS Institute Inc. All rights reserved.
  • 12. Netezza and SAS Connected Database Connector In-Database Analytics Analytics Data Extraction • Base SAS – Proc SQL DataEnterprise Miner • SAS Extraction Server • SQL Pass-Thru Option • SAS Scoring Accelerator for Netezza • SAS/Access to Netezza FA FA ST ST ER Data • SAS/Access to Netezza • SAS Scoring Accelerator for Netezza Warehouse Data Extraction Data Extraction • Netezza Database • Netezza Database • In-Database Analytics 12 Copyright © 2010, SAS Institute Inc. All rights reserved.
  • 13. Why use SAS and Netezza?  SAS for Analytic Insight/Solutions  The Leader in Analytics Software  SAS provides more analysis options/models with greater functionality than any other vendor  Netezza appliances architecturally integrate database, server and storage into a single, easy to manage system that requires minimal set-up and ongoing administration.  Netezza is know for its data warehouse appliance that delivers high performance out of the box.  When you combine SAS and Netezza you get both the leader in analytics and the leader in warehouse appliances working together to provide the most efficient infrastructure for the customer to solve business problems  Bottom Line: Working together SAS and Netezza help to accelerate your business processes 13 Copyright © 2010, SAS Institute Inc. All rights reserved.
  • 14. Customer Success Story – Marketing Agency Providing Flexibility in Data Mining Past Approach In-Database Approach Modeling data created in Modeling data created in Warehouse Warehouse Modeling performed in SAS Modeling performed in SAS Enterprise Miner Enterprise Miner ABT Scoring data created and Scoring data created and aggregated in Warehouse aggregated in Warehouse SAS Enterprise Miner Enterprise Miner Model Enterprise Miner Model converted to STAT code – PUBLISHED into RDBMS REGRESSIONS ONLY for use – Scoring Algorithms available: •REGRESSION •DECISION TREE •NEURAL NETWORK •GRADIENT BOOST •PARTIAL LEAST SQUARES •SUPPORT VECTOR MACHINE Scoring Scored ABT Data Data extracted from Data scored in SAS and Scorin Warehouse remains in Warehouse g in Data scored in SAS Wareho use Data imported back into SAS Warehouse Scoring Accelerator 14 Copyright © 2010, SAS Institute Inc. All rights reserved.
  • 15. Customer Success Story – Propensity to Pay Providing Performance gains by Refactoring Flat file Past Approach In-Database Approach OpSys1 extract • Daily process begins • Daily process begins OpSys1 with flat file creation at at 4:00am with EDW load. 6:30am – SLA delivered at ~9:30am. • File transferred to SQL • All operational data Server, limited to ~350K loaded directly to EDW. No customer records based on flat file or intermediate specific criteria. processing is needed. SQL SAS Server Scoring Accelerator • 300 step process to • 10 step process support data mining life • Scoring and customer Customer cycle. selection done in-database SAS Selection against ALL customer rows EDW 30 MINUTES TO SCORE 4 MINUTES TO SCORE ~350k customers ~40M customers Runs in ~ 3 HOURS Runs in 12 MINUTES 15 Copyright © 2010, SAS Institute Inc. All rights reserved.
  • 16. Contacts & Links SAS Alliance Netezza, an IBM Company Kevin Go Tim McCarthy kevin.go@sas.com tmccar@us.ibm.com (919) 531-0680 - office (802) 291-0457 Tracye Giles Bernard Doering tracye.giles@sas.com bernard.doering@de.ibm.com Links • Netezza homepage SAS and Netezza Brochure • SAS homepage • Netezza partner page for SAS • SAS Access to Netezza • SAS In-Database • SAS Scoring Accelerator for Netezza • SAS Scoring Accelerator for Netezza Documentation • SAS In-Database Technology • BASE SAS Procedures with In-Database processing 16 Copyright © 2010, SAS Institute Inc. All rights reserved.
  • 17. Q/A More information  About SAS on Netezza website: http://www.netezza.com/partners/comp-tech-detail.aspx?CTpid=1043  SAS to deliver in-database analytic scoring for Netezza platform (press release): http://www.sas.com/news/preleases/SASScoringAcceleratorForNetezza.html  Catalina Marketing gains unparalleled brand traction with SAS® and Netezza (press release): http://www.sas.com/news/preleases/CatalinaNetezza.html  Catalina Marketing helps predict customer behavior with SAS® Enterprise Miner http://www.sas.com/success/catalina.html  Foxwoods Plays a strong hand with SAS and Netezza http://www.netezza.com/releases/2008/release120808.htm 17 Copyright © 2010, SAS Institute Inc. All rights reserved.
  • 18. Thank You Company Confidential - For Internal Use Only Copyright © 2010, SAS Institute Inc. All rights reserved.