Products & Solutions / In-Database Processing

SAS® Analytics Accelerator for Teradata

In-database analytics improve data governance on predictive analytics projects and produce faster, better results

SAS Analytics Accelerator for Teradata enables the execution of key SAS analytical, data discovery and data summarization tasks within a Teradata database or data warehouse. This type of in-database processing reduces the time needed to build, execute and deploy powerful predictive models. It also increases the utilization of the enterprise data warehouse or relational database to reduce costs and improve the data governance that is required for successful analytic applications.

Benefits

  • Reduce data movement and redundancy to ensure data quality and enhance resource use.
  • Improve accuracy and achieve better outcomes using more data points and sophisticated analytical models.
  • Achieve faster time to results by building, updating and deploying models more quickly.
  • Enhance the productivity of analytic teams.

Read more

Features

  • Statistical and analytical functions enabled for in-database processing
  • SQL generation options specify the type of in-database computing

Read more

How SAS® Is Different

  • SAS has taken an industry lead in promoting in-database analytics as one of the best practices for high-performance analytic deployments for customers interested in pursuing a centralized database or data warehouse strategy.
  • SAS offers a variety of commonly used statistical and analytical functions for in-database data discovery and predictive modeling. This enables customers to work with larger volumes of data and build sophisticated predictive models that leverage parallel processing and scalability to improve processing time and achieve answers more quickly.
  • An unmatched set of integrated data management and analytical capabilities from SAS combined with Teradata's in-database processing capabilities enables organizations to drive innovation and improve performance across all lines of business.
  • With in-database solutions, SAS unites the requirements of IT and the needs of analytic users by providing improved model development and deployment processes while offering an IT environment that scales and promotes better data governance.

Benefits

  • Reduce data movement and redundancy to ensure data quality and enhance resource use. In-database analytics reduce, or eliminate, the need to move massive data sets between a data warehouse and the SAS environment or other analytical data marts for multipass data preparation and compute-intensive analytics.
  • Improve accuracy and achieve better outcomes using more data points and sophisticated analytical models. The massively parallel architecture of data warehouses is useful for processing larger, more complex information sets. Modelers can easily add new sets of variables if model performance degrades or changes are needed for business reasons.
  • Achieve faster time to results by building, updating and deploying models more quickly. SAS Analytics Accelerator for Teradata enables analytical processing to be pushed down to the database or data warehouse, shortening the time needed to build and deploy predictive models. It also reduces the latency and complexity associated with the model development process. Analytics professionals have fast access to up-to-date, consistent data and increased processing power. This delivers faster time to results and provides better insights for improved business decision making.
  • Enhance the productivity of analytic teams. In-database analytics helps modelers, data miners and analysts focus on developing high-value modeling tasks instead of spending time consolidating and preparing data.

Features

Statistical and analytical functions enabled for in-database processing
  • SAS/STAT® in-database versions of the following procedures:
    • CORR (correlation).
    • CANCORR (canonical correlation).
    • FACTOR (factor).
    • PRINCOMP (principal components).
    • REG (regression analysis, including stepwise regression).
    • SCORE (scoring of linear models).
    • VARCLUS (group variables into clusters).
  • SAS/ETS® in-database version of the following procedure:
    • TIMESERIES (analyzes time-stamped transactional data and aggregates the data into a time series format for trending and seasonal analysis).
  • SAS® Enterprise Miner TM in-database versions of the following macros and procedures:
    • Sampling macro (simple random, stratified and oversampling).
    • Binning macro (quantile binning with Weights of Evidence calculation).
    • DMDB (data mining database model effects summarization).
    • DMINE (variable selection).
    • DMREG (linear and logistic regression analysis, including support for stepwise regression).
SQL generation options specify the type of in-database computing
  • NONE (specifies that no in-database computation be performed).
  • DBMS (specifies the SAS procedure to be used for in-database processing when possible):
    • Uses conventional SAS processing when the specific procedure statement and options do not support in-database processing.
  • ALL (specifies that in-database computation be performed whenever possible).
  • These options can be specified as either a LIBNAME statement option or as a system option in an OPTIONS statement.

System Requirements

Host Platforms/Server Tier
  • HP/UX on Itanium: 11iv3 (11.31)
  • HP/UX on PA-RISC: 11iv3 (11.31)
  • IBM AIX on POWER architectures: 6.1 and 7.1
  • IBM z/OS: V1R10 and higher
  • Linux (32-bit): Novell SuSE 10 and 11; RHEL 5 and 6
  • Linux x64 (64-bit): Novell SuSE 10 and 11; RHEL 5 and 6; Oracle Linux 5.5 and 6
  • Microsoft Windows (32-bit): Windows XP Professional, Windows Vista *, Windows 7**, Windows Server 2003 family, Windows Server 2008 family
  • Microsoft Windows on x64 (64-bit): Windows XP Professional for x64, Windows Vista* for x64, Windows 7** for x64, Windows Server 2003 family for x64, Windows Server 2008 family for x64
  • Solaris on SPARC: Version 10 Update 8
  • Solaris on x64 (x64-86): Version 10 Update 8
Required Software
  • SAS/ACCESS® Interface to Teradata (SAS 9.3)
  • Base SAS 9.3
  • SAS/STAT 9.3 and/or SAS/ETS 9.3 and/or SAS Enterprise Miner 7.1
  • Teradata 13 or higher

* NOTE: Windows Vista supported editions are: Enterprise, Ultimate and Business.
** NOTE: Windows 7 supported editions are: Enterprise, Ultimate and Professional.

Ready to learn more?

Call us at 1-800-727-0025 (US and Canada) or request more information.