Release of SAS® 9.4 Version

SAS^® 9.4 Software

The evolution of the SAS®9 architecture continues with SAS 9.4. This release fully uses multicore technologies to deliver increased processing capabilities through high-performance, in-database and in-memory analytics resulting in greater insights more quickly from big data and streaming data. Important foundational updates allow you to deploy SAS in the manner that best suits your needs. SAS 9.4 delivers a more highly available and resilient platform for deploying SAS in traditional on-site environments along with additional support for private and public cloud deployments.
SAS 9.4 includes features that will benefit all of the users at your site.

• For IT departments, SAS 9.4 provides a simplified architecture, increased security, and more deployment options.



• For SAS administrators, SAS 9.4 reduces your dependence on IT with new management capabilities and administration tools.



• For data administrators, the integration of the DataFlux products creates a more complete data management solution. Also new programming languages enable you to manipulate your data and access relational data from various data sources. New programming languages enable you to update data on the database and access relational data from various sources.



• For SAS programmers, high-performance analytics enable you to quickly analyze large amounts of data. Multi-threading capabilities have also been added so you can perform analyses on single machine deployments.



• For the business user, reports are available from a variety of mobile devices, so you have the information that you need, when you need it.

For more information about the features of SAS 9.4, read What's New in SAS 9.4. If you are interested in more specifics about a particular SAS product or solution, find the product or solution in which you are interested in the SAS Product Listing: Index A-Z and review the information on the product page.

Release of SAS® 9.3 software

SAS^® 9.3

Solve next-generation problems with SAS^®

^OVERVIEW:

The newest release of SAS software continues our vision to help our customers solve next-generation business problems with our market-leading business analytics solutions. Through advancements in high-performance computing, improvements in environment management, enhancements in data management, and expanded analytics capabilities to better manage and process "big data," SAS software’s “big analytics” technologies are embedded in a framework that supports the entire decision-making process.

The SAS Business Analytics Frameworkcombines the strengths of SAS solutions and technologies with SAS' commitment to innovation, continuous technical support, professional services, training and partnerships.

BENEFITS:

• Increased productivity. SAS 9.3 will make users more productive by providing new capabilities and enhancements that streamline integration, activity and responsiveness, freeing them to work on value-added projects.
• Broader enablement. Added features and functionality will give users the ability to resolve bigger and more complex issues.
• Improved scalability. SAS software's unparalleled ability to handle vast of amounts of information goes even further with components in SAS 9.3 that address the big data issues customers currently face, with the capabilities to continue to scale with voluminous growth in the future.
• Higher performance. SAS 9.3 takes high-performance computing to a new level, reducing the time to results and therefore allowing for faster decision making.

FEATURES:

Data management

• Enhanced manageability for improved performance
  • Version and source control, including archival, differencing and rollback, including plug-ins for third-party version control products CVS and SubVersion.
  • Job status and performance reporting for tracking metrics such as CPU utilization, memory, I/O, number of jobs, number of records, etc., in a historical view.
  • Automated job deployment allows use of common scripting languages to deploy SAS Data Integration Studio batch jobs in an automated fashion.
  • New command-line job deployment for deploying single and multiple jobs.
  • Enhanced SAS code import capabilities enable current SAS users to import their SAS jobs into SAS Data Integration Studio. Includes improved logging and error checking.
• In-database processing (ELT pushdown)
  • Optimized SQL set transforms.
  • Support for Oracle bulk loader.
  • Import capabilities for user-defined functions that enable in-database scoring for analytics.
• Enhanced performance for loading Oracle data
  • Provides native support for bulk loading.
  • Includes an easy-to-use GUI for integration.
  • Provides support for flexible loading options, including direct path and load to partition.
  • Includes the ability to drop or recreate indices.
• New ETL transforms
  • New transforms generate SAS code that is very efficient with high performance.
  • New transforms include: Type 1 SCD supports both MERGE and HASH techniques, Table Differencing and enhancements for Type 2 SCD loaders.
  • New Compare Tables transform compares two data sources and detects changes in data.
• Data access
  • Support for new data sources: Teradata, Aster Data, EMC/Greenplum and Sybase IQ.
  • Native support for SQL-based processing. Support for bulk-load utilities.
  • Push-down processing supports in-database processing.

Data quality

• SAS^® Enterprise Data Integration Server includes DataFlux^® Data Management Platform for enhanced data quality
  • Includes integrated profiling, exploration and entity resolution capabilities.
  • Provides powerful process orchestration layer for jobs, SAS code and SQL.
  • Creates the basis for a master data management strategy.
• Master Data Management (DataFlux^® qMDM)
  • Provides support for master hub of trusted entity data.
  • Supports a data-quality-driven approach for mastering key business entities.
  • Provides data models for key business domains.
  • Provides governance and data steward services that support inspection, root-cause analysis and the correction of data and propagation of corrections across the IT environment.

Analytics

• SAS/STAT®
  • Finite mixture models.
  • Random effects for Bayesian models.
  • Cox regression for sample survey data.
  • Updates to mixed models for data with large numbers of observations.
  • Shared frailty models.
  • Fully conditional specification method for multiple imputation.
• SAS/ETS®
  • Simulate realizations or estimate parameters of multivariate distributions by using the copula approach.
  • Powerful and versatile tools for state space modeling and forecasting of time series and longitudinal data.
  • Data access engine SASEXCCM for the CRSP/COMPUSTAT Merged Database.
  • New graphs such as forecast plots, periodogram for an error series, and spectral density estimation plots.
  • New features for modeling the size of losses or insurance claims.
• SAS/QC®
  • Monitor multivariate process variation over time in order to determine whether a process is stable or to detect and diagnose changes in a stable process.
  • Fit Gumbel, inverse Gaussian, generalized Pareto, power function, and Rayleigh distributions.
  • Fit parametric models for recurrent events data and constructs probability plots for models based on a three-parameter Weibull distribution for lifetime data.
• SAS/IML®
  • Call SAS procedures and DATA steps.
  • Provides an interface to the R statistical programming language.
  • New functions and subroutines.
• SAS® Enterprise Miner™
  • Provides new standardized Web Infrastructure Platform mid-tier services for data integration, BI, SAS solutions and analytics.
  • New survival data mining analysis predicts when an event will happen, not just if it will happen (e.g. predicts event probability for time intervals for each customer).
  • New rate-making capability for insurance predicts optimal insurance premium for individuals based on attributes known at application time.
  • Time Series Data Mining node (experimental) applies data mining techniques to transactional, time-stamped data.
  • Support Vector Machines node (experimental) provides a supervised machine learning method for prediction and classification.
  • New interactive tree application features enable users to select optimal tree based on assessment on validation data. Other evaluation plots are automatically updated based on the selection of a sub-tree.
  • Least Angle Regression node is now supported for both interval and binary targets.
  • SAS Rapid Predictive Modeler adds the ability to score the training data with an option to save the scored data set.
  • Improved speed for large data sets.
  • Procedures optimized for utility file usage.
  • SAS code optimized for efficient file usage.
• SAS® Forecast Server
  • Automatic time series combination (ensemble) models allow users to combine different forecasts to produce another forecast.
  • Ability to define customized time intervals.
  • Rolling simulation lets you interactively simulate a forecasting process.
  • Temporal reconciliation enables users to reconcile forecasts across time dimensions (e.g., daily, weekly, monthly, yearly). (Included with the SAS High-Performance Forecasting engine.)
  • Administrators can now assign role-based access to the SAS Forecast Studio GUI.
  • Export model selection list enables modelers to export models to a repository using point and click.
  • Auxiliary data set support.
  • Increased scalability for SAS Forecast Studio.
  • Exploits multikernel machines for faster response times.
  • SAS Forecast Server is integrated with the SAP APO Demand Planning module to provide SAP users with access to a superior forecasting engine and automatic forecasting capabilities.
• SAS® Model Manager
  • Analytic workflow management. Using SAS Workflow Studio, users can define a workflow process for each model based on their needs using notifications, timers, etc.
  • Seamless integration of R models with the ability to register and manage R models in SAS Model Manager.
  • Ability to perform champion/challenger side-by-side comparisons between SAS and R models to see which model performs best for a specific need.
  • Model retraining enables existing models created with SAS Enterprise Miner to be retrained with up-to-date data to generate a new set of modeling results.
  • Improved performance-monitoring dashboards. Update all reports or update reports for projects that have new performance data.
• SAS/OR® and SAS^® Simulation Studio
  • Optimization
    • New network simplex linear programming algorithm.
    • Crossover feature for interior-point linear programming solver (experimental).
    • New multistart capability for nonlinear programming solvers.
    • Performance improvements for all optimization solvers (linear, mixed-integer, quadratic and nonlinear).
  • Simulation
    • Automatic input distribution fitting using JMP with SAS Simulation Studio.
    • Use 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.

Text analytics

• SAS® Text Miner
  • Enhanced language support (now supporting 27 languages + dialects).
  • New text import capabilities for sourcing file system and Web data.
  • Reuse synonym data sets and other usability enhancements.
• SAS® Enterprise Content Categorization
  • Wikipedia integration to support the generation of taxonomies & add-on industry-specific taxonomies.
  • New graphical reports enable users to understand the precision and accuracy of the classification process.
  • New operators, including co-reference and pronoun resolution.
• SAS® Sentiment Analysis
  • Enhanced language support (now supporting 27 languages + dialects).
  • Enhanced rule-building, editing, verification and operators.
  • Interactivity makes it easier for subject-matter experts to add new concepts.

Scalability and high performance

• SAS® Analytics Accelerator for Teradata (new product)
  • Enables in-database data discovery and predictive modeling.
  • Allows a key set of SAS statistical and analytical procedures used during data discovery, summarization and predictive modeling to be executed directly within a Teradata database or Teradata data warehouse.
  • Includes SAS/STAT procedures: CORR, CANCORR, FACTOR, PRINCOMP, REG, SCORE and VARCLUS.
  • Includes SAS/ETS^® procedure: TIMESERIES.
  • Includes SAS Enterprise Miner procedures: DMDB, DMINE and DMREG.
• SAS® Grid Manager
• SAS Stored Process Server, SAS OLAP Server and SAS Workspace Server now support processing in a grid environment.
• Note: Source www.sas.com

Sample Size Software - "nMaster 2.0"

Hi All,

This is to inform you that the second version of Sample Size software - “nMaster 2.0”  has been released from the Biostatistics Resource and Training Centre, Dept. of Biostatistics, Christian Medical College, Vellore.  This has enhanced features in Clinical Trials,  Non-parametric and Clusters Sampling etc. 

This has been validated against the expensive software nQuery and also by the Prof.R.M. Pandey, AIIMS and Prof. Sreekumaran Nair, Manipal University and their teams. 

The single user license is Rs.2500/-. 

Please visit their website for further details (http://www.cmc-biostatistics.ac.in)

If you need further information, feel free to contact them from the website above.