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© 2010 Netezza, Inc. All rights reserved	<br />Analytics Without Constraints<br />Netezza Integration with SAS Software<br />
Data Analysis before Netezza<br />
Where were we before Netezza? <br /><ul><li>  Extremely long processing cycles for Data analysis – long waits…
  Working with small datasets (Subsets) – very restrictive
  Analytic Models restricted to tests against small datasets
  Too much data is being moved between servers
Data Models run for long time periods against full data base – processing of other jobs impacted severely
  Data Models sometimes re-coded in C/C++ for better performance
  Productivity of the Data Analysts is low</li></li></ul><li>SAS Software and Netezza DWH Appliance<br />Page 4<br />SAS<b...
Big Data Meets Big Math – Netezza + SAS Software<br />Page 5<br />Analytics Without Constraints<br />Confidential Briefing...
SAS Support on Netezza for Analytics Processing<br />Page 6<br />
Netezza Enabled with SAS Software<br />Page 7<br />Data Extraction<br />Database Connector<br />In-Database Analytics<br /...
Netezza and SAS Connected<br />Page 8<br />Data Extraction<br />Database Connector<br />In-Database Analytics<br />Data Ex...
 Base SAS – PROC SQL
 SAS/Access to ODBC
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Netezza integration with SAS software

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Netezza integration with SAS software

  1. 1. © 2010 Netezza, Inc. All rights reserved <br />Analytics Without Constraints<br />Netezza Integration with SAS Software<br />
  2. 2. Data Analysis before Netezza<br />
  3. 3. Where were we before Netezza? <br /><ul><li> Extremely long processing cycles for Data analysis – long waits…
  4. 4. Working with small datasets (Subsets) – very restrictive
  5. 5. Analytic Models restricted to tests against small datasets
  6. 6. Too much data is being moved between servers
  7. 7. Data Models run for long time periods against full data base – processing of other jobs impacted severely
  8. 8. Data Models sometimes re-coded in C/C++ for better performance
  9. 9. Productivity of the Data Analysts is low</li></li></ul><li>SAS Software and Netezza DWH Appliance<br />Page 4<br />SAS<br />SAS for Fraud Detection<br />SQL<br />SAS/Access to Netezza<br />SAS for Customer Scoring<br />SAS<br />SAS Score Code <br />Confidential Briefing for Customer <br />
  10. 10. Big Data Meets Big Math – Netezza + SAS Software<br />Page 5<br />Analytics Without Constraints<br />Confidential Briefing for Customer <br />
  11. 11. SAS Support on Netezza for Analytics Processing<br />Page 6<br />
  12. 12. Netezza Enabled with SAS Software<br />Page 7<br />Data Extraction<br />Database Connector<br />In-Database Analytics<br />Pulled from<br />Pushed down<br />Pulled from<br />Scoring<br />Algorithms & Transforms<br />Analyst<br />Analyst<br />Scoring<br />Algorithms & Transforms<br />Analyst<br />011011010010100101110011011010010100101110<br />01101101001010 LOTS of DATA Movement<br />01101101000101110000101110<br />Less Data<br />AND Faster<br />Process<br />Automation<br />DW Developer<br />More Transforms<br />In-Database<br />DW Developer<br />Scoring Algorithms & Transforms <br />Published to Database as Scoring Processes<br />Recoded Scoring Processes<br />Recoded Scoring Processes<br />011011010010100101110011011010010100101110011011010010100110110100101001011100110110010100101110011011010010100110110100101001011100110110100101001011100110110100101001101101001010010111001101101001010010111001101101001010011011010010100101110011010100101001011100110110100101011111000<br />Data Warehouse<br />
  13. 13. Netezza and SAS Connected<br />Page 8<br />Data Extraction<br />Database Connector<br />In-Database Analytics<br />Data Extraction<br />Data Extraction<br />Data Extraction<br />Analytics Server<br /><ul><li> Base SAS – DATA STEP
  14. 14. Base SAS – PROC SQL
  15. 15. SAS/Access to ODBC
  16. 16. Base SAS – Proc SQL
  17. 17. SQL Pass-Thru Option
  18. 18. SAS/Access to Netezza
  19. 19. SAS Enterprise Miner
  20. 20. SAS Scoring Accelerator for Netezza</li></ul>ODBC<br />FAST<br />FASTER<br />Data Extraction<br />Data Extraction<br />Data Extraction<br />Data Warehouse<br /><ul><li> ODBC
  21. 21. Netezza Database
  22. 22. SAS/Access to Netezza
  23. 23. Netezza Database
  24. 24. SAS Scoring Accelerator for Netezza
  25. 25. Netezza Database
  26. 26. In-Database Analytics</li></li></ul><li>Netezza in the SAS Ecosystem<br />Open standards platform to enable actionable intelligence “out of the box”<br />Business Analytics Applications<br />NetezzaPerformance Server<br />Enterprise Applications<br />Transactional Databases<br />Users<br />ETL – SAS DI Studio, or other<br />CRM<br />Billing<br />Employees<br />ERP<br />RFID<br />Customers<br />Suppliers<br />HR<br />SCM<br />NPS<br />External Source Systems<br />Representative vendors<br />Supplier Data<br />E-Commerce<br />Key Advantages<br /><ul><li>Performance
  27. 27. Scalability
  28. 28. Low TCO</li></ul>9<br />
  29. 29. Catalina Marketing Case Study<br />Page 10<br />
  30. 30. Value Proposition<br />Supercharge SAS with Netezza’s high performance, scalable scoring<br />Effective resource utilization via automatic code generation<br />Reduced end-to-end processing time<br />Reduced time-to-model implementation<br />Simplified infrastructure to maintain and administer<br />SAS Enterprise Miner model development process is simple and easy to manage <br />Leverage existing SAS knowledge and Netezza high-performance<br />Increase Analyst Productivity<br />Score Database more frequently for better results<br />Page 11<br />
  31. 31. Model Scoring In-Database<br />SAS Scoring Accelerator for Netezza<br />Page 12<br />
  32. 32. SAS® In-Database<br /> Traditional Architecture In-Database Architecture <br />Analytic Modeling<br />Analytic Modeling<br />SAS Scoring<br />Data<br />Preparation<br />Data<br />Preparation<br />SAS Scoring<br />SAS Modeling<br />SAS C & PMML Scoring<br />Data Preparation<br />NetezzaTwinFin™<br />NetezzaTwinFin™<br />
  33. 33. SAS® Scoring Accelerator for Netezza1.6<br />BIClient<br />SAS Enterprise Miner<br />SAS 9.2<br />Model<br />NZ TwinFin™<br />Export<br />SAS Model ManagerorSAS publishing agent<br />sas_score()<br />Score asDATA Stepcode<br />SASFormatLibrary<br />SASDATA StepEngine<br />ScoreDefinitions<br />FormatDefinitions<br />Publishing Macro<br />
  34. 34. Benefits<br />Achieve higher model-scoring performance and faster time to results<br />Improve accuracy and effectiveness of analytic models<br />Reduce data movement and latency <br />Eliminate model score code rewrite and model re-validation efforts (i.e. labor costs and error prone)<br />Consolidate data to improve regulatory compliance<br />Better manage, provision and govern data <br />

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