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Title Date Added Company

Real-Time Business Intelligence and Data Integration as a Strategic and Critical Component 2006-02-10 10:43:39

Change Data Capture (CDC) is a strategic component in the data integration infrastructure that dramatically improves efficiencies, eliminates the needs for batch windows, deals with the growth of data volumes, delivers information in real-time, and reduces costs. Attunity Stream provides an enterprise-scale CDC solution that complements and works seamlessly with existing ETL and EAI investments. Visit us at www.attunity.com .

Managing Master Data for Business Performance Management: The Issues and Hyperion's Solution 2007-04-10 14:59:40 Hyperion

This white paper from IDC defines master data management and explores the various scenarios and issues gaining attention both from IT and business managers. The challenge for organizations is to align business roles with responsibilities for management of specific master data domains, with IT providing the technical support for the underlying data resources and data models.

Best Practices in Selecting Performance Management Software 2006-02-07 09:05:11

A new generation of sophisticated, Web-based database applications is changing the way companies look at planning and financial reporting. These corporate performance management (CPM) solutions combine a wide variety of financial functions into a single suite, resulting in one real time data pool for budgeting, forecasting, consolidation, reporting, business modeling, strategic planning and decision support.

This white paper, created by CFO Research Services, documents the experiences learned from organizations that have previously deployed performance management solutions. It discusses how companies defined their business problem, evaluated technology and process change, and implemented their solutions with the goal of achieving sustainable business results. In addition, a list of best practices to help any organization undertaking a CPM project is provided.

OSS for The New World 20040302121649 Axiom Systems

The communications companies at the heart of the New World Economy are not only providing those enterprise businesses with the network and higher value services which can be supported by their wireline and wireless infrastructures, but are also now searching for the new Operational Support System (OSS) and Business Support System (BSS) technologies needed to sustain the resulting complex business and operational processes. To operate at business speed is to perform in ever shrinking elapsed time frames for the period from order to delivery of product, or consumption of service. Speed concerns the reduction of product and service lifecycles. The time from launch to the point at which the product or service becomes redundant, surpassed by other differentiated offers, or is morphed into hybrid variations and customer crafted customisations of the original. Speed has an impact on customer expectations that are firmly targeted on the benefit of now.

A Brief History of Decision Support Systems 20040302121454 Decision Support Systems Resources

Today, a number of disciplines provide the substantive foundations for DSS development and research. Database researchers have contributed tools and research on managing data. Management Science has developed mathematical models for use in DSS and provided evidence on the advantages of modeling in problem solving. Cognitive Science, especially Behavioral Decision Making research has provided descriptive information that has assisted in DSS design and has generated hypotheses for DSS research.

The Decision-Driven Warehouse - Attention Warehouse Shoppers: The Output is in the Decision 0000-00-00 Thomson

Todays Decision Support System (DSS) market place has about as many definitions of warehouse as vendors: Centralized warehouse, operational data store, distributed warehouse, virtual warehouse, data mart, replicated online transaction processing (OLTP) data. If you are currently undertaking a Data Warehousing project, you are faced with trying to select the right approach from a myriad of options. Proponents of each warehouse strategy often defend their design as the only acceptable one and focus on the physical aspects of extracting, moving, organizing, and accessing huge amounts of data. Obviously, data is necessary for Decision Support. However, while selecting a physical approach is necessary, it is not enough to build a successful Data Warehouse.

Technology and Policy in Decision Support Systems 1998-01-30 Thomson

Data warehousing, data marting, online analytical processing (OLAP) -- these terms dominate discussions of enterprise decision support systems (DSS). At the same time, it is becoming increasingly clear that none of these product categories has a particularly stellar track record for improving the quality or quantity of commercial decisions. This is so because none of the technological answers to the commercial decision-making problem focuses on decision-making processes themselves--on the entirety of the decision-making problem -- which are as much matters of policy as they are of technology. This white paper discusses the evolution of the data warehousing marketplace from data infrastructure to enterprise decision support systems, focusing on the decision-making process as the design center for effective DSS environments.

Clinical Reminder System: A Relational Database Application for Evidence-Based Medicine Practice 2006-09-08 01:00:28 Carnegie Mellon University

Evidence-based medicine is the distillation of a large volume of medical research and standards into treatment protocols for diseases and preventive care procedures that represent the most accurate knowledge available. In the project discussed in this paper, the authors implement evidence-based medicine principles via a decision support system that provides suggested actions for physicians based on individual patient characteristics and established treatment protocols. The paper presents a prototype DSS, called Clinical Reminder System, that combines a relational database, a knowledge base consisting of algorithms that implement disease treatment protocols, integration with hospital legacy systems and a web-based interface allowing for physician management of patient data and suggested medical responses.

Decision Analysis: Concepts, Tools and Promise 2005-08-30 03:00:03 Fair Isaac

At Fair Isaac, some powerful and unique decision analytic tools have been developed in recent years. These tools add significant value to clients who use our products and services to optimize their strategies. While traditionally the emphasis at Fair Isaac had been on sophisticated prediction technologies, it has shifted in recent years to developing and using a powerful, synergetic coupling of these time-proven tools with state-of-the-art decision modeling and techniques. The combination of decision analytic expertise, models, and tools with existing prediction and exploratory analysis techniques, promises substantial added value to clients.

EU Project: Data Mining and Decision Support for Business Competitiveness - A European Virtual Enterprise (Sol-Eu-Net) 2006-04-25 04:35:05 Jozef Stefan Institute

This paper defines the mission of this European project to spread the use of technologies of Data Mining (DM) and Decision Support (DS) to enhance efficiency, effectiveness and quality of operations in business, industry and public services. The virtual enterprise model is proposed as the dynamic problem-solving link between experienced Data Mining and Decision Support experts on the one hand, and customers in need of specific solutions on the other.

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Title	Date Added	Company
Real-Time Business Intelligence and Data Integration as a Strategic and Critical Component	2006-02-10 10:43:39
Change Data Capture (CDC) is a strategic component in the data integration infrastructure that dramatically improves efficiencies, eliminates the needs for batch windows, deals with the growth of data volumes, delivers information in real-time, and reduces costs. Attunity Stream provides an enterprise-scale CDC solution that complements and works seamlessly with existing ETL and EAI investments. Visit us at www.attunity.com .
Managing Master Data for Business Performance Management: The Issues and Hyperion's Solution	2007-04-10 14:59:40	Hyperion
This white paper from IDC defines master data management and explores the various scenarios and issues gaining attention both from IT and business managers. The challenge for organizations is to align business roles with responsibilities for management of specific master data domains, with IT providing the technical support for the underlying data resources and data models.
Best Practices in Selecting Performance Management Software	2006-02-07 09:05:11
A new generation of sophisticated, Web-based database applications is changing the way companies look at planning and financial reporting. These corporate performance management (CPM) solutions combine a wide variety of financial functions into a single suite, resulting in one real time data pool for budgeting, forecasting, consolidation, reporting, business modeling, strategic planning and decision support. This white paper, created by CFO Research Services, documents the experiences learned from organizations that have previously deployed performance management solutions. It discusses how companies defined their business problem, evaluated technology and process change, and implemented their solutions with the goal of achieving sustainable business results. In addition, a list of best practices to help any organization undertaking a CPM project is provided.
OSS for The New World	20040302121649	Axiom Systems
The communications companies at the heart of the New World Economy are not only providing those enterprise businesses with the network and higher value services which can be supported by their wireline and wireless infrastructures, but are also now searching for the new Operational Support System (OSS) and Business Support System (BSS) technologies needed to sustain the resulting complex business and operational processes. To operate at business speed is to perform in ever shrinking elapsed time frames for the period from order to delivery of product, or consumption of service. Speed concerns the reduction of product and service lifecycles. The time from launch to the point at which the product or service becomes redundant, surpassed by other differentiated offers, or is morphed into hybrid variations and customer crafted customisations of the original. Speed has an impact on customer expectations that are firmly targeted on the benefit of now.
A Brief History of Decision Support Systems	20040302121454	Decision Support Systems Resources
Today, a number of disciplines provide the substantive foundations for DSS development and research. Database researchers have contributed tools and research on managing data. Management Science has developed mathematical models for use in DSS and provided evidence on the advantages of modeling in problem solving. Cognitive Science, especially Behavioral Decision Making research has provided descriptive information that has assisted in DSS design and has generated hypotheses for DSS research.
The Decision-Driven Warehouse - Attention Warehouse Shoppers: The Output is in the Decision	0000-00-00	Thomson
Todays Decision Support System (DSS) market place has about as many definitions of warehouse as vendors: Centralized warehouse, operational data store, distributed warehouse, virtual warehouse, data mart, replicated online transaction processing (OLTP) data. If you are currently undertaking a Data Warehousing project, you are faced with trying to select the right approach from a myriad of options. Proponents of each warehouse strategy often defend their design as the only acceptable one and focus on the physical aspects of extracting, moving, organizing, and accessing huge amounts of data. Obviously, data is necessary for Decision Support. However, while selecting a physical approach is necessary, it is not enough to build a successful Data Warehouse.
Technology and Policy in Decision Support Systems	1998-01-30	Thomson
Data warehousing, data marting, online analytical processing (OLAP) -- these terms dominate discussions of enterprise decision support systems (DSS). At the same time, it is becoming increasingly clear that none of these product categories has a particularly stellar track record for improving the quality or quantity of commercial decisions. This is so because none of the technological answers to the commercial decision-making problem focuses on decision-making processes themselves--on the entirety of the decision-making problem -- which are as much matters of policy as they are of technology. This white paper discusses the evolution of the data warehousing marketplace from data infrastructure to enterprise decision support systems, focusing on the decision-making process as the design center for effective DSS environments.
Clinical Reminder System: A Relational Database Application for Evidence-Based Medicine Practice	2006-09-08 01:00:28	Carnegie Mellon University
Evidence-based medicine is the distillation of a large volume of medical research and standards into treatment protocols for diseases and preventive care procedures that represent the most accurate knowledge available. In the project discussed in this paper, the authors implement evidence-based medicine principles via a decision support system that provides suggested actions for physicians based on individual patient characteristics and established treatment protocols. The paper presents a prototype DSS, called Clinical Reminder System, that combines a relational database, a knowledge base consisting of algorithms that implement disease treatment protocols, integration with hospital legacy systems and a web-based interface allowing for physician management of patient data and suggested medical responses.
Decision Analysis: Concepts, Tools and Promise	2005-08-30 03:00:03	Fair Isaac
At Fair Isaac, some powerful and unique decision analytic tools have been developed in recent years. These tools add significant value to clients who use our products and services to optimize their strategies. While traditionally the emphasis at Fair Isaac had been on sophisticated prediction technologies, it has shifted in recent years to developing and using a powerful, synergetic coupling of these time-proven tools with state-of-the-art decision modeling and techniques. The combination of decision analytic expertise, models, and tools with existing prediction and exploratory analysis techniques, promises substantial added value to clients.
EU Project: Data Mining and Decision Support for Business Competitiveness - A European Virtual Enterprise (Sol-Eu-Net)	2006-04-25 04:35:05	Jozef Stefan Institute
This paper defines the mission of this European project to spread the use of technologies of Data Mining (DM) and Decision Support (DS) to enhance efficiency, effectiveness and quality of operations in business, industry and public services. The virtual enterprise model is proposed as the dynamic problem-solving link between experienced Data Mining and Decision Support experts on the one hand, and customers in need of specific solutions on the other.