This white paper discusses the findings of a study conducted by SAS and Health Data Management in an effort to shed light on the attitudes of senior actuarial executives toward the use of analytics. According to study findings, SAEs are not fully aware of tools that offer advanced functionality, such as forecasting, predictive modeling and optimization capacity. The study, which was conducted via in-depth interviews with health plan actuarial executives from across the country, uncovers opinions on the use of analytics in managing and leveraging data, forecasting, trend analysis, reserve management and related matters.

The secret to consistently beating both profitability goals and competitors may sound simple - just understand your customers better and faster than anyone else, and then target them more effectively than anyone else. But with the scope and scale of marketing today, delivering meaningful, personal service to customers is a difficult task.

This white paper discusses the evolution of analytics-based marketing automation and then looks briefly at the critical technologies that support the latest generation of marketing automation: an enterprise architecture, sophisticated analytics, capabilities that give more control to business users and the ability to extend into other areas of marketing.

This white paper provides five steps to resource optimization, with a visual model and a variety of real-world examples to help business leaders understand how to allocate resources in alignment with enterprise-level objectives. You'll also learn about the technology required to support resource optimization.

Natural resources agencies in the Americas must understand how to enhance the effectiveness of programs and policies while maintaining an adequate level of funding. This white paper describes how analytics can provide optimized solutions to these challenges. The paper first describes the use of analytics in resource management, education and CRM, operations and performance management. Ultimately, you will learn about SAS' analytic capabilities for natural resource agencies.

This white paper describes ways the healthcare industry can use the data at its disposal to evolve toward more personalized medicine. In particular, you will learn about the promising possibilities of electronic medical records and powerful analytic solutions for healthcare providers from SAS. The paper also includes some real-life situations in which SAS analytics are being used to improve patient care and research.

Pharmaceutical sales and marketing professionals face a unique set of challenges in their efforts to boost sales enough to recoup staggering development costs. This white paper explores the possibilities of data integration and advanced analytics in marketing and selling pharmaceuticals. The paper also includes a list of key analytical techniques and several industry case studies.

Most pharmaceutical companies focus their sales and marketing activities on the top-decile prescribing physicians for a given therapeutic area, based on purchased data. But such practices are no longer yielding desired results. This white paper discusses why now is the right time to make sales and marketing decisions based on deeper analytic insights - using predictive modeling - and how organizations that take control over their own physician targeting will get more timely insights, targeting decisions aligned with business issues and real competitive advantage.

While many areas of government have successfully employed aspects of fact-based decision making, current initiatives to reduce waste and expenses correspond with what business analytics offers organizations. This white paper produced by BusinessWeek looks at how government agencies are struggling to embrace the spirit of initiatives like the President's Management Agenda and how business analytics can give them an anchor on which to operate as they search for operational agility based on deeper insights, better answers and faster reaction times geared toward the future. 

This white paper discusses some of the key infrastructure challenges that IT faces in meeting the ever-increasing demands for intelligence across their organizations. It provides an overview of how the platform for SAS Business Analytics can help overcome those challenges. It also describes SAS strengths within each of the platform components -- data integration, analytics, and reporting. Most importantly, it outlines how SAS is here to help organizations achieve success through analytic solutions built upon an integrated framework. 

This paper, based on research by nGenera Corporation, provides answers to six key questions that executives should be asking about how to use business analytics to improve performance and compete successfully -- from "Where should we leverage business analytics?" and "What's the payoff?" to "What kinds of people do we need?" and more.

More sophisticated state government revenue departments are accurately identifying and prioritizing tax returns that have a high likelihood of under-reporting and a high magnitude of potential collection by augmenting their rules-based tax auditing systems with scores generated by analytical modeling – improving audit success by as much as 20 to 50 percent. This paper describes the benefits of advanced, non-linear modeling over traditional rules-based approaches, for more precision and better rank ordering, fewer false positives, higher revenues and faster ROI.

To improve student achievement, educators and administrators are effectively using valuable data -- through data warehousing and business analytics -- to integrate and analyze data sources in a flexible, easy-to-manage reporting environment. This white paper describes the benefits of using data-driven decision making, as well as information and case studies on SAS onsite and hosted solutions for education.

This white paper reviews a portion of a research program conducted by BusinessWeek Research Services designed to understand how companies can optimize business analytics to improve fact-based decision making and to determine the attitudes and opinions of C-level executives with regard to the use and value of business analytics. It is part of a series of white papers for C-level executives intended to facilitate sharing the most important insights from the research. 

Many forward-looking executives are turning to predictive maintenance (PM) solutions to help prevent equipment failures and avoid the costs of unplanned downtime. This paper explores the business case for investing in predictive maintenance solutions, examines how they work to lower maintenance costs and minimize disruptions across the enterprise, and describes what is required to get started with PM today.

Amid the current climate of greater demand for both environmental awareness and corporate accountability, organizations are finding that success is increasingly being measured not only by financial performance, but also by ecological and social accomplishments as well. In addition, the current economic climate has reinforced the need to plan for long-term success. This white paper, based on a launched research program conducted by BusinessWeek Research Services, looks at how the most forward-thinking enterprises are using analytics to their advantage by applying it to sustainability.

To truly exploit analytics enterprisewide for a competitive edge, an organization must have a centralized group that provides core expertise, supports users, enforces standards and drives performance. The author dubs this group an "analytical center of excellence" (ACE). After laying out his recommended ACE infrastructure, the author prepares you to engage your organization in establishing an ACE. He describes three primary phases of infrastructure, the different levels of enterprise analytical maturity that determine ACE requirements, and the analytical maturity assessment that must occur in order to develop an implementation plan.

This paper reviews a portion of the research done by BusinessWeek Research Services to determine the attitudes and opinions of C-level executives with regard to the use and value of business analytics and provides analysis and insights on the topic of business analytics.

This white paper discusses the drivers and the challenges in implementing a longitudinal data system. It then explores how, with SAS' Business Analytics Framework, information gaps among key educational agencies need no longer exist, and decision makers can be armed with the accurate data they need to make proactive decisions and effective education policies.

This white paper illustrates a new patent-pending approach that may be helpful in certain new product forecasting situations.  It combines human judgment with time series mining and statistical modeling.  This "structured analogy" approach helps automate the selection of analogous products ("like items"), facilitates review and clustering of past new product introductions, and generate statistical forecasts.  Users can make manual overrides to the statistical forecasts, and get a better sense of the risks and uncertainties in new product forecasts through visualization of past new product introductions.

Radio frequency identification (RFID) is spreading quickly through the global network of supply chains. The technology promises improved efficiency and more accurate tracking--along with untold amounts of data. Read this white paper to get a brief introduction to RFID and learn about a variety of SAS technologies that can help you harness the value of your RFID-related data. Such technologies include data quality, business intelligence, predictive analytics and even retail-specific applications.

This paper illlustrates how Credit Scoring for SAS Enterprise Miner software is used to build credit scoring models for the retail credit industry. It discusses the benefits of performing credit scoring and the advantages of building credit scoring models in-house using SAS Enterprise Miner. It goes on to discuss the advantages and disadvantages of three important model types: the scorecard, the decision tree and the neural network. Finally, it presents a case study where an application scoring model is built with SAS Enterprise Miner, beginning with reading the development sample, through classing and selecting characteristics, fitting a regression model, calculating score points, assessing scorecard quality (in comparison to a decision tree model built on the same sample) and going through a reject inference process to arrive at a model for scoring the new customer applicant population.

As in other sectors of the economy, the insurance industry has experienced many changes in information technology. Advances in hardware, software, and networks have offered benefits, such as reduced costs and time of data processing as well as increased potential for profit. Competition has also increased, making effective IT solutions even more necessary.

This paper discusses how insurance companies can benefit from modern data mining methodologies, which help companies reduce costs, increase profits, retain current customers, acquire new customers, and develop new products. You will learn about how to implement data mining projects and about changes in U.S. legislation that affect insurance firms. A list of recommended reading is also included.

This white paper outlines the flexible architecture of SAS Enterprise Miner. It shows how the SAS architecture enables users to create data mining projects for interactive or batch execution and share projects with other business users and decision makers across the organization.  

This white paper illustrates a new patent-pending approach that may be helpful in certain new product forecasting situations.  It combines human judgment with time series mining and statistical modeling.  This "structured analogy" approach helps automate the selection of analogous products ("like items"), facilitates review and clustering of past new product introductions, and generate statistical forecasts.  Users can make manual overrides to the statistical forecasts, and get a better sense of the risks and uncertainties in new product forecasts through visualization of past new product introductions.

What-if scenarios that predict what might happen given different business conditions and decisions are most enlightening when we understand the relationships between the variables that influence potential results. Data visualization expert Stephen Few describes the characteristics of good visual analytics and describes how to use the JMP Prediction Profiler to build predictive business models and interact with data and graphs to observe how changes in one variable influence changes in the others.

This paper presents a methodology for conducting a forecasting strategic value assessment for your organization.

In today's unstable economy, many organizations are finding out that they have inadequate processes to handle demand planning, and traditional methods of predicting demand aren't efficient in a fluctuating market. The paper makes specific recommendations for organizations striving to move up the demand forecasting maturity curve by providing them an assessment framework to evaluate their current stage, and highlighting the characteristics common to best-class companies.

How effectively an organization manages its supply chain depends on many factors. An organization can have excellent business processes, yet lack the ability to successfully align supply with demand. Read this white paper to learn how advanced forecasting technology and business intelligence can enhance Sales and Operations Planning while supporting better communications and collaboration throughout an enterprise.

Retailers are commonly faced with the challenge of forecasting demand for items that are sold only at certain times of the year, but in high volumes. This paper suggests a compression approach for dealing with these kinds of highly seasonal forecasts using SAS software, which could produce more accurate results than forecasts based on standard time series modeling. It provides an illustrative example based on real-life data. 

This case study describes how SAS helped the Ontario Ministry of Health and Long-Term Care achieve a solution to predict hip and knee replacement demand – enabling the Ministry to solve what had become a crisis in long wait-times for the surgery. Based on powerful SAS® Forecast Server, this solution now provides the forecasts that guide Ontario’s ongoing investment in orthopedic staff, facilities and services.

Ensure that your organization is getting the best possible forecasts, as efficiently as possible. Through this paper you will discover how the forecast value added (FVA) metric can be used to identify waste in forecasting processes and expose factors that diminish accuracy. The author provides detailed instruction on using FVA: from gathering data, to conducting analysis, to effectively reporting the results to management. He also discusses the real-world results of FVA analysis at companies from a variety of industries. 

This white paper discusses fundamental issues that impact an organization's ability to forecast accurately. These issues include the operational definition of "demand," what to forecast, how to measure performance, organizational practices and demand volatility. Without addressing these issues, the investment may yield no return.

This white paper discusses multi-causal analysis as a way of integrating consumer demand information with shipment forecasts to capture the impact of marketing activities on shipments. With improvements in technology, data collection, data storage and analytical knowledge, CPG companies are now looking to integrate consumer demand with their shipment forecasts to capture the impact of marketing activities on shipments. As a result, multi-tiered causal analysis (MTCA) is receiving renewed interest. This paper explains the MTCA process, including an anonymous beverage industry case study that describes the process used to develop and link the Consumer Demand and Factory Shipment models. The by-product of this process was a more accurate forecast that reflected the company's marketing investment strategy.

Web sites and transactional databases collect large quantities of time-stamped data. Businesses often want to make future predictions based on numerous sets of time-stamped data (sets of transactions). The number of time series to forecast, however, may be enormous or the forecasts may need to be updated frequently, making human interaction impractical. This detailed white paper proposes a technique for automating large-scale forecasting using SAS Forecast Server. You will learn about time series data, forecast modeling and statistics of fit. The paper also provides a step-by-step explanation of the automated forecasting technique and a brief discussion of implementation.

This white paper discusses the drivers and the challenges in implementing a longitudinal data system. It then explores how, with SAS' Business Analytics Framework, information gaps among key educational agencies need no longer exist, and decision makers can be armed with the accurate data they need to make proactive decisions and effective education policies.

The use of predictive analytics has enabled organizations to more accurately predict outcomes and increase profitability. As the number of models grows, it is imperative that organizations implement sound model management practices. This white paper provides an overview of the model management lifecycle process and gives an introduction to SAS Model Manager. Ultimately, the paper recommends best practices for the management of predictive models in a production environment.

This paper details challenges that affect how communications are planned and deployed, including limiting factors such as budget caps, campaign volumes and channel capacities. Communications often can't be anticipated until a trigger-based or real-time interaction uncovers a need and the opportunity for an additional communication. Successful processes utilize the latest analytical techniques and consider a company's corporate objectives and business rules. This paper discusses a process called adaptive contact planning as a way to create more effective, and thus more profitable, marketing campaigns.

This white paper provides five steps to resource optimization, with a visual model and a variety of real-world examples to help business leaders understand how to allocate resources in alignment with enterprise-level objectives. You'll also learn about the technology required to support resource optimization.

This white paper describes the nature and purpose of optimization and considers the various types of optimization problems that can be solved with SAS/OR software. In addition, the paper explores the value that optimization adds to enterprise data, analytical technologies and business intelligence. You will also learn about new optimization features available with SAS/OR and how they make optimization with SAS easier, more transparent and more scalable than ever before.

Manufacturing and supply chain organizations must not only optimize resources and minimize waste, but also predict future growth and demand. Event-handling and transactional systems cannot merge data into an integrated source of business intelligence; organizations need adequate data management, forecasting, optimization and modeling techniques to bring disparate data together and gather useful intelligence from it. With key performance indicators and process metrics that span functional areas, managers and other stakeholders can see changes and trends as they occur and make business decisions based on those indicators.

This white paper discusses the drivers and the challenges in implementing a longitudinal data system. It then explores how, with SAS' Business Analytics Framework, information gaps among key educational agencies need no longer exist, and decision makers can be armed with the accurate data they need to make proactive decisions and effective education policies.

This white paper by Stephen E. Arnold explores the value of text mining as a way to process unstructured information and identify themes without reading an entire collection of text. In particular, Arnold focuses on the value of SAS Text Miner for integrating text-based information with structured data and enhancing organizations' predictive modeling capabilities.

Accurate, timely and relevant information saves companies both time and money through increased efficiency, improved productivity and an improved ability to make knowledge-based decisions. So why do many companies fail to realize the benefits of all the information in their organization? This white paper answers that question by focusing on the capabilities of SAS Integration Technologies, which are used to tap into SAS solutions from other enterprise applications. You will get an overview including key terminology, as well as a detailed description of the individual components of SAS Integration Technologies. The paper also outlines how many SAS solutions already use the capabilities of SAS Integration Technologies.

While Web services have great potential as a technology for implementing applications such as stock price delivery or inventory ordering over the Internet, there is another key business benefit — the delivery of analytical services and business intelligence functionality. This white paper provides a technical overview of how Web services fit into the SAS Intelligence Architecture and shows how to develop applications that make use of the Web services framework. It gives in-depth code examples of how to implement a simple, real-world scenario. The paper describes how to implement Web services using both the.NET and J2EE frameworks and provides an appendix outlining a basic Web services model.

This is a thought leadership paper by Mark David Milliron for education that describes the need to focus on fostering critical, creative, social and courageous learners ready and willing to face our challenges, build our economies, lead our companies and transform our schools. 

This white paper discusses some of the key infrastructure challenges that IT faces in meeting the ever-increasing demands for intelligence across their organizations. It provides an overview of how the platform for SAS Business Analytics can help overcome those challenges. It also describes SAS strengths within each of the platform components -- data integration, analytics, and reporting. Most importantly, it outlines how SAS is here to help organizations achieve success through analytic solutions built upon an integrated framework. 

In an effort to provide better, cost-effective care, health care providers are increasingly turning to IT-enabled business strategies. This white paper by Health Industry Insights, an IDC company, and sponsored by SAS presents the findings and analysis of in-depth interviews conducted with nine senior executives and system architects at three prestigious teaching hospitals acknowledged to be industry leaders in their use of health information technology, in general, and BI applications, in particular.

In March 2007, SAS conducted a survey of 175 business intelligence professionals from around the globe to assess current trends in the use of business information -- specifically business intelligence and competency centers -- and their effect on organizational performance. This report outlines the results of that survey and its implications for information management in your organization.

The implementation of a business intelligence (BI) environment is not simple, but it does yield tremendous benefits for companies that want to receive the most value from their data resources. Read this paper by BI visionary Dr. Claudia Imhoff to understand the fundamental questions anyone must ask to ensure a successful BI implementation.

You will learn to identify what you have, build a business case for the BI environment, establish the technical infrastructure to support it, maintain data quality and, ultimately, to expand the capabilities of BI through predictive and embedded analytics.

Healthcare leaders are challenged to improve care delivery, reduce costs and enhance physician and employee engagement. Doing so requires the ability to access data from a variety of siloed and disparate systems, and then to get that data into the hands of those closest to the issues. Applying business intelligence in a healthcare setting is a powerful way to break down political barriers, overcome resistance to change, align strategic priorities and improve communication. This white paper explores the ways that business intelligence and performance management software systems can facilitate evidence-based healthcare delivery in hospitals. The paper provides background on implementing business intelligence and then offers case studies demonstrating successful BI at several prominent hospitals.

To improve student achievement, educators and administrators are effectively using valuable data -- through data warehousing and business analytics -- to integrate and analyze data sources in a flexible, easy-to-manage reporting environment. This white paper describes the benefits of using data-driven decision making, as well as information and case studies on SAS onsite and hosted solutions for education.

This white paper reviews a portion of a research program conducted by BusinessWeek Research Services designed to understand how companies can optimize business analytics to improve fact-based decision making and to determine the attitudes and opinions of C-level executives with regard to the use and value of business analytics. It is part of a series of white papers for C-level executives intended to facilitate sharing the most important insights from the research. 

How effectively an organization manages its supply chain depends on many factors. An organization can have excellent business processes, yet lack the ability to successfully align supply with demand. Read this white paper to learn how advanced forecasting technology and business intelligence can enhance Sales and Operations Planning while supporting better communications and collaboration throughout an enterprise.

Smart corporations today are creating one source of consistent, reliable and high-quality data for strategic analyses and tactical decision making. This paper, written by BI expert Claudia Imhoff, outlines some of the key considerations for companies working toward enterprise business intelligence, including data quality, maintaining a program approach to BI and establishing centers of competency for managing a BI program. The paper also provides some advice for getting started with an enterprise BI program.

OLAP has become a standard requirement for almost any BI-related project because it enables users to navigate quickly through complex business data. This white paper provides an overview of several integrated SAS products that can be used for OLAP. You will learn how these products, all part of SAS Enterprise BI Server, allow different types of users to perform analysis of varying sophistication, from simple reporting and exploration to advanced visualization and publishing of results.

OLAP has become a standard requirement for almost any BI-related project because it enables users to navigate quickly through complex business data. This white paper provides an overview of several integrated SAS products that can be used for OLAP. You will learn how these products, all part of SAS Enterprise BI Server, allow different types of users to perform analysis of varying sophistication, from simple reporting and exploration to advanced visualization and publishing of results.

Enterprises are experiencing information overload. Dozens of systems generate reports, slice and dice data and collect it from every possible data point within the enterprise. With all this data, enterprises are beginning to see how effective delivery and sharing of information improves the process of making informed business decisions.

This white paper provides a detailed overview of the SAS Information Delivery Portal, a powerful vehicle for delivering enterprise information to the right people at the right time. The paper describes the state of enterprise information and provides a roadmap and business scenario for implementing the SAS Information Delivery Portal. You will learn about the flexibility of the portal and about its architecture, functionality and administration.

By putting data in motion, people can spot trends and see details they might otherwise miss. That's a guiding premise of this white paper from data visualization expert Stephen Few. Find out how interactive graphs lead to valuable analytical insights, illustrating not just the degree of change from one point in time to the next, but also the shape, velocity and direction of change.

This white paper discusses some of the key infrastructure challenges that IT faces in meeting the ever-increasing demands for intelligence across their organizations. It provides an overview of how the platform for SAS Business Analytics can help overcome those challenges. It also describes SAS strengths within each of the platform components -- data integration, analytics, and reporting. Most importantly, it outlines how SAS is here to help organizations achieve success through analytic solutions built upon an integrated framework. 

Collaborative data integration supports governance and stewardship, and it fosters reuse and remote management for distributed development teams. Read this white paper by TDWI's Philip Russom to learn about organizational issues, best practices and software tools for collaborative data integration.

To improve student achievement, educators and administrators are effectively using valuable data -- through data warehousing and business analytics -- to integrate and analyze data sources in a flexible, easy-to-manage reporting environment. This white paper describes the benefits of using data-driven decision making, as well as information and case studies on SAS onsite and hosted solutions for education.

The challenge of integrating enterprise data is not getting any easier, according to this research report published by TDWI. This paper analyzes the results of a survey designed to provide insight into the development of data integration technologies and techniques. The paper also explores requirements for developing an enterprise data integration strategy.

To survive and emerge stronger from the current financial crisis, it is essential that insurance companies implement an enterprise risk management strategy. And for any ERM project to be successful, it must be fundamentally linked to a holistic, unified approach to data management - one that ensures a smooth flow of information throughout the organization. This white paper discusses how using SAS for data management enables decision makers at all levels to see a complete picture of enterprise risk.

This white paper reviews a portion of a research program conducted by BusinessWeek Research Services designed to understand how companies can optimize business analytics to improve fact-based decision making and to determine the attitudes and opinions of C-level executives with regard to the use and value of business analytics. It is part of a series of white papers for C-level executives intended to facilitate sharing the most important insights from the research. 

Data migration projects often fail because of an underestimation of the effort required or a lack of planning. This paper focuses on the main areas associated with data migration: source system exploration, data assessment, migration design, migration build, execution, transition and production, and provides recommendations to enhance your chances for successful data migration projects. SAS Enterprise Data Integration Server provides a complete suite of functionality to complete all types of data migrations, as well as a platform that is reliable and scalable. It helps accelerate the delivery of data migration projects and also facilitates component reuse between projects.

Oil and gas companies invested heavily in ERP and DCS systems, which brought about increased efficiency. But when global business dynamics – driven by increased data volumes and changes in transaction infrastructures, decision patterns and performance criteria – began to shift from the status quo attitude of  "let things run by themselves," proactive planning and decision making took on greater importance as a way to adapt to change and gain competitive advantage. This white paper focuses on a four-layer model for regaining the benefits of ERP and DCS systems by enabling organizations to make full use of their corporate information and knowledge.

This white paper discusses the drivers and the challenges in implementing a longitudinal data system. It then explores how, with SAS' Business Analytics Framework, information gaps among key educational agencies need no longer exist, and decision makers can be armed with the accurate data they need to make proactive decisions and effective education policies.

Data migration projects often fail because of an underestimation of the effort required or a lack of planning. This paper focuses on the main areas associated with data migration: source system exploration, data assessment, migration design, migration build, execution, transition and production, and provides recommendations to enhance your chances for successful data migration projects. SAS Enterprise Data Integration Server provides a complete suite of functionality to complete all types of data migrations, as well as a platform that is reliable and scalable. It helps accelerate the delivery of data migration projects and also facilitates component reuse between projects.

Data is only as valuable as its actual or perceived quality. The traditional approach to data quality management is to correct quality problems as they are encountered. There is an emerging approach to data quality that takes a more proactive approach by putting data quality standards and processes in place that govern data throughout its lifecycle. This white paper, based on two research projects, describes a three-tiered approach the research uncovered for managing data quality in the insurance market.

This white paper discusses the drivers and the challenges in implementing a longitudinal data system. It then explores how, with SAS' Business Analytics Framework, information gaps among key educational agencies need no longer exist, and decision makers can be armed with the accurate data they need to make proactive decisions and effective education policies.

Read this white paper to explore SAS Data Integration, a component of the SAS platform for Business Analytics. The paper first describes the barriers to establishing efficient extraction, transformation and loading (ETL) processes that ensure data quality. It then explains the benefits of SAS Data Integration, including faster development of data integration processes, more efficient processing, better accountability and increased value from existing systems.

SAS and IBM have had a long-standing relationship that represents a true win-win for both companies. By coordinating the development of DB2 8.1 and SAS®9, IBM and SAS are allowing customers to take advantage of enhancements to both systems. This paper explores the impact of SAS and DB2 configuration options by outlining different methods of accessing your DB2 database with a focus on performance. Examples are given to highlight the performance trade-offs of choosing different access methods, SAS®9 application parameters, and DB2 8.1 configuration options. In addition, this paper highlights some of the new features in SAS®9 and DB2 8.1.

Data migration projects often fail because of an underestimation of the effort required or a lack of planning. This paper focuses on the main areas associated with data migration: source system exploration, data assessment, migration design, migration build, execution, transition and production, and provides recommendations to enhance your chances for successful data migration projects. SAS Enterprise Data Integration Server provides a complete suite of functionality to complete all types of data migrations, as well as a platform that is reliable and scalable. It helps accelerate the delivery of data migration projects and also facilitates component reuse between projects.

This report from Bloor Research evaluates SAS ETL^Q, outlining a number of key findings about the SAS offering. In particular, this report highlights that, while SAS has not traditionally been well known in the ETL marketplace, SAS ETL products are mature and worth consideration. In addition to outlining key findings, this report provides some background on SAS, its available products, and its capabilities in data access and data quality. The paper also includes a discussion of SAS ETL Studio, the primary development environment for ETL processes in SAS ETL^Q.

This white paper discusses the drivers and the challenges in implementing a longitudinal data system. It then explores how, with SAS' Business Analytics Framework, information gaps among key educational agencies need no longer exist, and decision makers can be armed with the accurate data they need to make proactive decisions and effective education policies.

Metadata provides a means for both the technical documentation of data and the business communication of its meaning. In an integrated metadata environment this information is automatically used to drive your applications, without having to replicate this information for various applications.

This white paper discusses the role of metadata, or "data about data," to create a single version of enterprise truth and shows how to reduce the total cost of ownership for IT by leveraging a SAS metadata framework.

This paper provides information on key highlights of SAS 9.2 that have been released thus far, and is intended to help existing SAS customers understand SAS 9.2 software enhancements. It includes a short section on why customers should upgrade and provides a general overview of what is included with the release. It discusses new software modules and provides enhancement information for many other SAS products. It also includes a section on system management and security features, and a section on installing, configuring and migrating to SAS 9.2.

According to analysts, business intelligence applications are a top priority for CIOs. To help cut through the clutter of conflicting and overstated vendor claims, SAS has developed a comprehensive framework that can be used to evaluate any and all BI vendors. This white paper outlines the criteria included in this framework, which include measures of technology, alignment with customer needs corporate vision and geographic scope.

This paper explores the concepts of Information Management, including the challenges and importance of effectively managing ALL data whether it is structured, unstructured or semi-structured. It discusses the evolution of information management and outlines the SAS approach for a coherent IM strategy, which includes implementing a business intelligence competency center and the use of a comprehensive, integrated software platform.

SAS provides the perfect environment for turning operational ERP and front-office data into mission-critical business intelligence by helping organizations locate, identify, understand and extract the complex data structures locked within transactional systems. Learn about some of the key challenges IT groups face as they try to provide their users with a unified picture based on operational and legacy data, and see how SAS can help make the most of your operational data so you can provide users with the information they need to make fact-based decisions. This paper discusses SAS' data integration platform, including our powerful data access interfaces; new SAS®9 Data Surveyors for integrating ERP application data with the rest of your organizational information; and specialized adapters for moving data to and from SAP applications and SAS solutions, quickly and easily.

This IDC paper, sponsored by Platform Computing and SAS, focuses on the value of deploying business analytics solutions on grid computing platforms. It discusses high-performance computing environments (evolution is moving from clusters to grids to cloud computing), the reasons for choosing business analytics software on grid computing platforms and the benefits achieved by three organizations. These case studies illustrate how SAS Business Analytics and grid computing technologies can enable competitive differentiation, even with increasing data volumes, challenging and ever-changing decision-support requirements, and pressure on IT departments to do more with less.

Read this white paper to explore SAS Data Integration, a component of the SAS platform for Business Analytics. The paper first describes the barriers to establishing efficient extraction, transformation and loading (ETL) processes that ensure data quality. It then explains the benefits of SAS Data Integration, including faster development of data integration processes, more efficient processing, better accountability and increased value from existing systems.

This white paper discusses some of the key infrastructure challenges that IT faces in meeting the ever-increasing demands for intelligence across their organizations. It provides an overview of how the platform for SAS Business Analytics can help overcome those challenges. It also describes SAS strengths within each of the platform components -- data integration, analytics, and reporting. Most importantly, it outlines how SAS is here to help organizations achieve success through analytic solutions built upon an integrated framework. 

This technical white paper discusses the test results of SAS Scalable Performance Data Server (one component of SAS Intelligence Storage) on a Sun Solaris 10 x64 Sun Fire X4600 server with two attached Sun StorageTek 6540 arrays. The findings of the test can be applied easily to any engine or server being used as a component of SAS Intelligence Storage.

This IDC paper, sponsored by Platform Computing and SAS, focuses on the value of deploying business analytics solutions on grid computing platforms. It discusses high-performance computing environments (evolution is moving from clusters to grids to cloud computing), the reasons for choosing business analytics software on grid computing platforms and the benefits achieved by three organizations. These case studies illustrate how SAS Business Analytics and grid computing technologies can enable competitive differentiation, even with increasing data volumes, challenging and ever-changing decision-support requirements, and pressure on IT departments to do more with less.

This paper provides information on key highlights of SAS 9.2 that have been released thus far, and is intended to help existing SAS customers understand SAS 9.2 software enhancements. It includes a short section on why customers should upgrade and provides a general overview of what is included with the release. It discusses new software modules and provides enhancement information for many other SAS products. It also includes a section on system management and security features, and a section on installing, configuring and migrating to SAS 9.2.