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 TitleDate AddedCompany
whitepaper Improving the Accuracy of Spend Analysis through Data Quality2009-04-30 DataFlux
  Organisations can spend as much as 60 percent of revenue to acquire the goods and services necessary to conduct business. Procurement professionals are being asked to reduce the organisation's overall spend, while simultaneously improving supplier collaboration. Companies now realise more than ever the effect of procurement strategies on their profitability and viability. Poor-quality product data creates difficulties in controlling the costs of production, promoting the productivity of the company, and the delivering finished goods. This white paper offers practical advice on how data quality technology can be used to address these issues.

Tags: Data Infrastructure, Data Infrastructure, Data Tools		   
whitepaper UK Biobank Records Data on the Health of 500,000 Individuals for Groundbreaking Medical Research2009-04-01 Oracle
  UK Biobank wanted to build a secure repository for long-term storage and protection of confidential medical, health, and lifestyle data collected on 500,000 study participants and create a single, consistent electronic record for each individual that complies with the Health Level 7 Version 3 (HL7v3) protocol for the format, content, and exchange of data. The challenge was to extract and deliver comprehensive data sets to medical researchers in a format that maintains participant anonymity and is easy for researchers to access and use. UK Biobank implemented Oracle Healthcare Transaction Base to establish a proven, scalable, HL7 v3-compliant healthcare repository for collecting, storing, and sharing validated data.

Tags: Data Infrastructure		   
whitepaper Towards Data Quality and Data Mining Using Constraints in XML2009-03-01 University of South Australia
  Quality data is necessary for different data mining techniques and reversely, data mining techniques can be utilized to measure quality of data. Data mining and data quality issues got much attention for relational data in past. But, as a massive amount of data is being stored and represented over the web in XML, the issue of data quality for mining purposes and also using data mining techniques for quality measures get research interest. The paper proposes two important interrelated issues: how quality XML data is useful for data mining in XML and how data mining in XML is used to measure the quality data for XML.

Tags: Data Tools, Data Infrastructure		   
whitepaper Business Intelligence for Siebel Enterprise Leveraging the SAP BusinessObjects Solution Portfolio2009-03-01 SAP
  The challenge was to integrate Siebel applications data with other systems, to ensure data quality across applications and deliver rich, formatted, interactive reports for the Siebel environment and to deliver trusted information that supports operational and analytical initiatives. The SAP BusinessObjects solution portfolio provides the technology, tools, and packaged data applications to integrate Siebel applications data with other systems rapidly and successfully and enrich Siebel environment. SAP BusinessObjects Business Intelligence (BI) solutions include SAP BusinessObjects Enterprise software, SAP BusinessObjects Data Quality Management software, SAP BusinessObjects Data Integrator software, and SAP BusinessObjects Rapid Marts packages, among other solutions.

Tags: Data Tools, Homeland Security		   
whitepaper Dana-Farber Cancer Institute Speeds Medical Research With Advanced Data Warehouse2009-02-01 Oracle
  In the quest for more effective cancer treatments, researchers face a fundamental challenge: how to make sense of mountains of scientific and clinical data and find clues buried in them. The Human Genome Project, an unprecedented program that resulted in a map of the human genome and opened up limitless opportunities for exploring the genetic mechanisms behind diseases, also resulted in considerable challenges for researchers. Leveraging Oracle Healthcare Transaction Base, a comprehensive data repository and service infrastructure that enables data interoperability, and Oracle Fusion Middleware components as its foundation, the institute has pioneered a data infrastructure that is uniquely efficient, effective and secure.

Tags: Data Infrastructure, Software Development Tools		   
whitepaper Top 10 Trends in Business Intelligence for 20092009-02-01 Hewlett-Packard (HP)
  Conducting business in an economy that has no precedent makes fact-based decision making more than a nice-to-have. Furthermore, increased efficiency and productivity will be needed to help lift companies, industries and countries out of the recession. To make the most of BI, first one needs to get the data right. And indeed, according to surveys by industry analysts and HP, the greatest Business Intelligence (BI) challenges and the leading BI initiatives focus on data quality, MDM, attaining a single version of the truth, and providing a data foundation for doing analysis and making better and faster decisions across the enterprise.

Tags: Data Tools		   
whitepaper Information Quality Management Services: Make Information Meaningful to the Processes It Fuels2009-02-01 Hewlett-Packard (HP)
  Today's organisations certainly do not lack data: corporate information stores continue to grow at an impressive rate. However, actionable, high-quality information is another thing entirely. Organisations are on a quest for better information, and in many cases, it eludes them. The result is an inefficient work environment with increased exposure to risk. People have to work harder to find answers to their questions; money and time are wasted with ad hoc remediation efforts; and cataclysmic events (such as an audit or lawsuit) reveal impairments only when it is too late to avoid a loss.

Tags: Data Infrastructure		   
whitepaper Journal of Management Excellence - Creating Value2009-02-01 Oracle
  The principles underlying TVI are as old as control theory. Accountants audit a company by aligning money, information, and the flow of goods—or core business processes, in more modern terms. It begins to go wrong when information is lacking or when money flows do not align anymore to the core business process. TVI is not the only performance indicator that aims to predict business success. The most well known indicator is economic value added (EVA) which includes a charge against profit for the cost of capital. With this charge, EVA penalizes inappropriate behaviors at least in X3 and X4. But EVA will not tell you if your strategy to create value is "right". Another indicator—aimed at predicting bankruptcy—is Altman's Z-score. But again, this indicator does not account for "fairness". There are many initiatives aimed at measuring and managing intangible value such as social responsibility and morality, but most do not claim to have any predictive value for company success. However, TVI alone is not enough. You could allow suppliers a fair margin, have an appropriate non-primary income, try to not fool your customers . . . and still fail. TVI must be used in addition to other critical performance indicators.

Tags: Data Infrastructure, Data Infrastructure		   
whitepaper New Integrated Data Management Tools for DBAs2009-01-27 IBM
  Let's face it, DBAs have a tough job. DBAs must manage a complex set of tasks including ensuring high performance and availability, maintaining business critical production applications and managing changes. In these tough economic times, mistakes have even more significant consequences. Using IBM's Integrated Data Management tools for the DBA, users can effectively manage database and application changes and reduce the long, after hours finger pointing though proactive performance monitoring all while facilitating collaboration and driving organizational efficiencies. Empowered DBAs translates to better application performance, greater revenue, more satisfied customers and greater ability to meet SLAs.

Tags: Data Tools, Data Infrastructure, Data Tools, Data Infrastructure		   
whitepaper Populating a Data Quality Scorecard with Relevant Metrics2009-01-16 DataFlux
  Too often, data governance teams rely on existing measurements as the metrics used to populate a data quality scorecard. But without a defined understanding of the relationship between specific measurement scores and the business's success criteria, it is difficult to determine how to react to emergent data quality issues - and determine whether their fixing these problems has any measurable business value. This white paper by David Loshin explores ways to qualify data control and measures to support the governance program.

Tags: Data Infrastructure, Data Infrastructure, Data Infrastructure