Technology Update

Technology Update
Deepak Ramanathan
Asia Pacific - Technology

Copyright © 2011, SAS Institute Inc. All rights reserved.

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Technology Update?

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Data Integration Studio 4.3

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What’s New in DI Studio 4.3?
 New and Enhanced Access Engines
 Greenplum, Sybase IQ, Aster Data

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What’s New in DI Studio 4.3?
 New Transformations

• SQL Union
• Easy import of UDFs into expressions
• Optimized Oracle Bulk Loader
• Additional DBMS Expression Builder functions
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Metadata Search

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Metadata Search

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SAS Code Importer

 Support optional Macro expansion
 New “Analyze” only feature
 Detailed summary information
 Collision detection with warnings
 Ex: Library already exists but different path
 Better logging and error checking
 Work tables can be registered as physical tables
 Many more fixes and user requested enhancements

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SAS Code Importer Enhancements

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And much more!

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What’s New in Reporting
 Enterprise Guide 5.1
 Add in for Microsoft Office 5.1
 Roambi for SAS
 SAS VAE

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Enterprise Guide – 5.1

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EG 5.1

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Add-In for MS Office 5.1 - Outlook
Integration

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Add-In for MS Office 5.1 - Task Gallery

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BI Dashboard 4.3

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SAS Analytics – What’s New
 Enterprise Miner
 Model Manager
 SAS/STAT
 SAS/ETS
 SAS/OR

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SAS ® Enterprise Miner 7.1

 Data Mining
 Release Objectives
 Application tools
 In-database processing

 Key Features
 Survival data mining for time dependent outcomes
 High performance rate making (claims, severity, and pure premium)
 Support for logistic regression models in LAR/LASSO node
 Optimal binning with constraints for credit score carding
 In-database expansions for statistical transformations and modeling
 Time series data mining tools (Experimental)

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These materials are proprietary to SAS® and constitute SAS confidential information pursuant to the terms of the confidentiality or nondisclosure agreement in place between you and SAS®

SAS ® Model Manager 3.1

 Data Mining
 Release Objectives
 Deeper support for existing models
 Broader support for additional model types

 Key Features
 Workflow to replace lifecycle templates and enable automated and collaborative model
import, comparison, validation, scoring, monitoring and retraining
 Model retraining in MM
 New report types
 Model management for additional types of models including R models

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SAS/STAT ® 9.3

 Statistics
 Key Features
 New FMM procedure (experimental) for finite mixture modeling

 Shared frailty models in PHREG

 Expanded capabilities for Bayesian analysis including the addition of a RANDOM
statement and multivariate priors in MCMC

 Production SURVEYPHREG procedure

 New model diagnostics in NLIN

 GRAPH license no longer required for ODS Graphics

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SAS/ETS ® 9.3

 Forecasting and Econometrics
 Key Features
 New procedure for fitting copula distributions
 New procedure for statespace modeling
 Automatic variable selection for COUNTREG procedure
 Update data engines to support latest releases
 Additional / improved ODS Graphics plots

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SAS/OR ® 9.3

 Operations Research
 Key Features - Optimization
 New network simplex linear programming algorithm
 Crossover feature for interior-point linear programming solver (experimental)
 Improvements to nonlinear solvers and introduction of a multi-start method for nonlinear
programming
 Performance improvements for mixed integer programming solver
 Key Features - Simulation
 Using data to drive models – empirical distributions, nonhomogeneous Poisson processes
 Improved usability to simplify navigation of large models
 Support for Windows 64 and remote SAS servers
 Automatic input distribution fitting using JMP for Simulation Studio

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Introducing SAS High-Performance Analytics

 SAS High Performance Analytics has been developed to
solve complex business problems that require
sophisticated high-end analytics and access to big data
 Statistical techniques addressed by the product include:
Correlation analysis, Linear regression and variable selection with
classical and modern methods, Logistic regression, Neural nets,
Linear mixed models, Nonlinear regression and maximum
likelihood, Optimization

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SAS High-Performance Analytics: Topology
(DRAFT)
Base SAS1

Client Tier SAS/STAT1

SAS High Performance Analytics1

SAS/Access Interface for Teradata or
Greenplum1

SAS Grid Manager2
Appliance

SAS In-Memory Analytics

SAS Embedded Process

Database Storage

Teradata or EMC Greenplum
1 Dependent products, 2 Optional products 32


SAS High-Performance Analytics:
Capabilities
Data Preparation Data Exploration Analytics

• (HP)DS2* • SUMMARY/MEANS • HPLOGISTIC
• SORT • FREQ • HPREG
• RANK • HPLMIXED
• HPFOREST
• HPNEURAL
• HPREDUCE
• HPNLIN

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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;

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Architecture
Master
Request is sent to the appliance
and received by the Master Node

Worker Node 1 Worker Node 2 Worker Node N

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Architecture
Master


Analytical Computation and data request sent to the worker nodes

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Architecture
Master


Data request sent to the database, data slice moved into memory
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Architecture
Master


Analytic Processing with internode communication

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Architecture
Master


Worker node results returned to the Master Node, finalize
computation
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Architecture
Root Node


Result returned to the client
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Much More Being Introduced

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Call to Action to SAS Jedi Warriors
 Speak to your SAS Representative on Technology
Updates
 Join the SAS Singapore User Community
 SASCommunity.org
 May the Proc be with you!

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Technology Update

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