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 TitleDate AddedCompany
whitepaper Implementing CDISC Submission Data Standards2006-08-11 01:00:09 Clinical Data Interchange Standards Consortium
  Now that the SDTM has become the submission data standard, pharmaceutical and biotech companies are facing the challenge of implementing these standards in combination with their internal operational, and reporting standards. This webinar will focus on how and where to implement the Study Data Tabulation Model (SDTM) and how analysis datasets fit in with SDTM regulatory submissions. The webinar provides a series of practical considerations for those seeking to implement SDTM within their own companies, suggesting appropriate functional partnerships, and strategic "Linking" of existing systems that serve a variety of purposes.   
whitepaper Standardizing Your Product Knowledge Base: A Solution for Effective Medical Content Management2006-08-11 01:00:09 First Consulting Group
  One of the most critical capabilities a medical communication function can have is to standardize and automate product and related medical inquiries delivered to a broad range of constituencies. But this is no easy task. There are a number of disparate processes, technologies, channels to the market, and medical practice differences across global markets that require smarter approaches. There is untapped potential to collect data points on adverse events and to analyze other data that can help the company gain greater customer insights. This webcast shows how Shire Pharmaceutical Group streamlined its medical communications, standardized global product launches, seamlessly integrated product information across operations, and was able to customize product responses across markets via a standard knowledge base.   
whitepaper Getting Started With Operations Analytics2006-08-10 01:00:12 Investcorp
  Even sophisticated organizations are sometimes unsure how to proceed with analytic applications. This paper uses a case study to define an analytic application and characterize the problems analytic applications are good at solving. It then shows how analytics can deliver value to the operations function. As organizations mature in their use of Data Warehousing/Business Intelligence (DW/BI) solutions, many see the use of analytic applications as a logical next step. Success stories, such as credit scoring and fraud detection in the credit card industry, are well publicized and make analytic applications sound wonderful. Yet many organizations, even those that are quite sophisticated in their use of DW/BI technologies, are unsure how to proceed with analytic applications.   
whitepaper Dominant Trends in Financial Services2006-08-10 01:00:12 SAS Institute
  It's clear that business intelligence has become a major priority for financial institutions. If a person looks at the major business issues in 2005, all of them focused on the need for greater access to data - data of "Certified" quality and accuracy, or at an enterprise versus Line-Of-Business (LOB) level, all coupled with enhanced analytics aimed at managing the business from a factual perspective. Business intelligence is no longer just a synonym for "Reporting." It truly has grown into its last name: "Intelligence". The push is squarely behind using data and analytics to reduce the uncertainty involved in managing a large enterprise. The acceleration of this phenomenon is driven by a number of interesting and converging drivers.   
whitepaper The Truth Will Keep You Free: Analytics, BI, and Compliance2006-08-10 01:00:12 SAS Institute
  Risk valuation is required by financial accountability regulations, such as Sarbanes-Oxley (SOX) and Basel II. To comply, companies must document operational risks. To scope compliance efforts, they must determine a corporate risk threshold. And finally, there's the risk of jail time if a person fudge the calculations. Compliance is a risky business, even if the business isn't risky. Of course, risk is nothing new to corporate executives. It's the static electricity on the doorknob of opportunity: drag the feet, and it will zap. Thus, with or without the impetus of legislation, most companies perform some degree of business analytics, and larger enterprises employ increasingly sophisticated Business Intelligence (BI) systems to identify and avoid costly contingencies.   
whitepaper Who Needs Customers, Anyway?2006-08-10 01:00:12 SAS Institute
  Today, there is a clear and integrated connection from the uppermost company measurement categories, to the metrics for the individual financial advisors. The marketing campaigns can be aligned with specific target groups. Moreover, the behavior of customers is analyzed by means of data mining which generates suggestions for up-selling and cross-selling. In doing so, those customers that are more likely to accept a certain offer are selected. All these evaluations and analyses are based upon a CRM Data Mart, in which all historical customer-related data is stored and readily available.   
whitepaper Performance Management - Making It Work, Part 4: Data Mining to Support Performance Management With Analytical Intelligence2006-08-10 01:00:12 SAS Institute
  This paper describes how information technologies, namely data warehousing; data mining with their powerful Extraction, Transform, and Load (ETL) features, and business analytics (e.g., statistics, forecasting, and optimization) all produce data from diverse source platforms transparent. That is, these technologies convert raw data into intelligence - the power to know. In almost all industries and commercial sectors today, information is key to becoming competitive. But before discussing how technology will create value, the paper first discusses some confusing issues related to value.   
whitepaper TechNet Webcast: Getting Started With Data Mining (Level 200)2006-08-04 01:00:11 Microsoft
  This webcast presents overview of data mining from a database development perspective. It begins with a discussion of the business value and uses of data mining, such as prediction and forecasting and explains how to detect anomalies, and how to recognize scenarios for which Microsoft data mining technology is best suited. Using a typical business-driven approach to data mining, the webcast shows how to identify data mining opportunities, and cover the practical elements needed to make it work well, such as data preparation, model building, and validation.   
whitepaper Using the Oracle Data Mining API2006-11-08 01:00:18 Oracle
  Following best practices, Oracle releases PL/SQL and Java Application-Programming Interfaces (APIs) well before there is a point-and-click tool or builder available taking advantage of a newly released API. This practice enables developers to incorporate new functionality into their applications immediately and allows their organizations to benefit accordingly. However, considerable development is required to create specialized tools that take advantage of a newly released API. This paper shows how to quickly incorporate analytic and other APIs into a spreadsheet platform from which the end user can easily access the new code.   
whitepaper Backup Failure Is Not an Option for Equant: Equant Turned to WysDM Software for Backup Performance Management2006-07-27 09:27:37 WysDM Software
  Serving over 800 businesses in more than 140 countries, data backup is a mission critical component of Equant's business. In any network, especially on one this large and dispersed, backup infrastructure is complex. The interdependencies between different technologies make it very difficult to find the causes behind failures and performance bottlenecks. Equant's IT Project Manager, Systems Integration and Engineering Group, saw a way out of this backup performance management problem. His vision was to gather information on the performance of the individual elements in the backup path, bring that information together and then automatically 'Correlate' that data looking for failures, performance bottlenecks and potential failures. WysDM Software's WysDM for Backups software helped to turn this vision into reality.