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Latest Content From SAS Institute

Whitepaper: Data Quality and Regulatory Compliance: Watching Your Watchlists

by SAS InstituteJan 01, 2008

A key element to any compliance initiative is the ability to identify and flag customers or transactions that violate government regulations. This white paper provides a how-to guide for organizations that want to use data quality and identity management technology to meet their compliance goals. This paper offers a complete approach to watchlist compliance. There are other approaches, of course, approaches that leverage matching to the exclusion of other technologies and preparations.

Whitepaper: Master Data and Master Data Management: An Introduction

by SAS InstituteJan 01, 2008

Master data management is a composition of tools, methods and policies that will mold the future of exploiting the value of the corporate information asset. The secrets to success lie in understanding how MDM will transition the organization into one with a strong data governance framework, articulating the roles and responsibilities for data stewardship and accountability, and creating a culture of proactive data quality assurance. This paper explores the basics of master data management, the policies and procedures employed, and the tools and techniques used for a successful MDM program.

Whitepaper: The Truth About Performance Improvement: Part 1 - Moving Beyond the Metrics

by SAS InstituteJan 01, 2008

In the past, performance management in a typical organization meant one of two things: finance managers scrutinizing company expenditures to track revenue against goals, or the human resources department prodding managers to evaluate their employees’ job performance. Not anymore. Now performance management has found its way across the organization. In the vast majority of companies surveyed, most areas of the organization are involved in performance management activities to some degree.

Whitepaper: Analyzing Time Series Cross-Sectional Data With the PANEL Procedure

by SAS InstituteJan 01, 2008

In the past, estimation techniques that use time series cross-sectional (panel) data approaches have become widely used. The PANEL procedure in SAS/ETS software fits classes of linear models that arise when time series and cross-sectional data are combined. This research paper from SAS Global Forum 2007 uses simulated data to compare the techniques and outline their advantages and disadvantages. The paper starts with a brief theoretical overview of panel data methods. Several examples are given to demonstrate these techniques and their implementation in the PANEL procedure. The PANEL procedure is then compared with other SAS procedures.

Whitepaper: Ubiquitous Scoring of 1000+ Warranty Categories Using Predictive Rules Derived From Text

by SAS InstituteJan 01, 2008

Volvo North America extracted warranty code predictive classification information from the text fields of over 1,000,000 records that represented warranty repair data over a 5-year period. The work discussed in this paper demonstrated that thousands of warranty codes could be reliably assigned by computer agents with an accuracy rate that ranged from 60% to 90%. Because the computer agents can be triggered from such applications as Microsoft Word and Excel, reliable, text-based, decision-making information can be available on-demand and can be used by operators and business analysts who have no special information technology or engineering training.

Whitepaper: Local and Global Optimal Propensity Score Matching

by SAS InstituteJan 01, 2008

Propensity score methods were developed to facilitate the creation of comparison groups that are similar. ""Similar"" in this sense refers to the distribution of observed characteristics. This research paper describes how to match samples using both local and global optimal matching algorithms. The paper includes macros to perform the nearest available neighbor, caliper, and radius matching methods with or without replacement and matching treated observations to one or many controls. The similarity between observations is evaluated using both the absolute value and the Mahalanobis distance that includes the propensity score along with other covariates.

Whitepaper: Forecasting Methods - An Overview of Models and Techniques

by SAS InstituteJan 01, 2008

The SAS System has a powerful suite of tools for analyzing and forecasting data taken over time. An important feature of this or any statistical analysis is that the user have some understanding of the methodology behind the tool, that is, for good analysis the computer program should be more than a black box to the user. To address that issue, this research paper reviews the methodologies available in the SAS System focusing more on the PROCs that underly the newer point and click technologies than on the user friendly front ends.

Whitepaper: DataFlux Version 8: Accelerate to Compliance, Data Governance and MDM

by SAS InstituteJan 01, 2008

With the Version 8 release of DataFlux core technology, DataFlux takes data quality and data integration to the next level. It helps organizations seamlessly control the quality of source information - and integrate information from complex, disparate data sources onto one single, unified view of the enterprise. This paper published by DataFlux provides an in-depth look at the Version 8 release and how it helps companies accelerate their compliance, data governance and MDM initiatives.

Whitepaper: Comparisons Among Various Educational Assessment Value-Added Models

by SAS InstituteJan 01, 2008

During the past several years there has been a growing interest nationally in using standardized test data to provide a measure of the impact of various educational entities on the rate of student progress. This paper from SAS Institute characterize the differences among several different classroom-level ""Value-added"" modeling efforts each having been applied to the same data structure from two different rather large school districts. An attempt will be made to show the advantages and disadvantages of each, with special attention given to the egregious risks of misclassification when some of these models are applied to provide classroom teaching effects estimates.

Whitepaper: Building Your Own Real-Time SAS Server Monitor Under Unix

by SAS InstituteJan 01, 2008

No matter how abundant the production or development hardware resources may be, one may run into problems once in a while, whether it is CPU, memory, or disk space. If such problems occur too frequently, one needs to take some preventive measures, such as getting an advance warning system. Base SAS provides all the tools need to construct own real-time SAS server monitoring and reporting system, and this paper will show how to put them together.