Showing papers on "Business intelligence published in 1999"

That ‘Internet of Things’ Thing

Abstract: Jun 22, 2009—I could be wrong, but I'm fairly sure the phrase "Internet of Things" started life as the title of a presentation I made at Procter & Gamble (P&G) in 1999. Linking the new idea of RFID in P&G's supply chain to the then-red-hot topic of the Internet was more than just a good way to get executive attention. It summed up an important insight—one that 10 years later, after the Internet of Things has become the title of everything from an article in Scientific American to the name of a European Union conference, is still often misunderstood.

Anonymous Web transactions with Crowds

Abstract: eb server log files are riddled with information about the users who visit them. Obviously, a server can record the content that each visitor accesses. In addition, however, the server can record the user’s IP address—and thus often the user’s Internet domain name, workplace, and/or approximate location—the type of computing platform she is using, the Web page that referred her to this site and, with some effort, the server that she visits next [7]. Even when the user’s IP address changes between browsing sessions (for example, the IP address is assigned dynamically using DHCP [4]), a Web server can link multiple sessions by the same user by planting a unique cookie in the user’s browser during the first browsing session, and retrieving that cookie in subsequent sessions. Moreover, virtually the same monitoring capabilities are available to other parties, for example, the user’s ISP or local gateway administrator who can observe all communication in which the user participates. The user profiling made possible by such monitoring capabilities is viewed as a useful tool by many businesses and consumers; it makes it possible for a Web server to personalize its content for its users, and for businesses to monitor employee activities. However, the negative ramifications for user privacy are considerable. While a lack of privacy has, in principle, always characterized Internet communication, never before has a type of Internet communication been logged so universally and revealed so much about the personal tastes of its users. Thus, our thesis is Web users should have the ability to limit what information is revealed about them and to whom it is revealed. Some with Crowds

The Complexity Challenge: Technological Innovation for the 21st Century

Abstract: Part One: the silent emergence of complexity fitting concept to reality the evolution of technological innovation complexity summary of cases used in Part Two. Part Two: self-organization network self-organization network learning path dependence. Part Three: emerging patterns adaptive network strategies adaptive public policies.

Anticipatory Humanitarian Intervention in Kosovo

Abstract: political relationship. It will be difficult to rebuild Kosovo's economy while Serbia is excluded from regional economic plans, and the displacement of an oppressive provincial apparat will seem a mixed success if NATO police power cannot reverse the retaliatory actions that have driven out most of Kosovo's Serb minority. The consistency of the air campaign with the traditional protection given to civilian objects and the problem of dualuse targets are also open to reflection. Some will wonder whether the more flexible terms allowed by NATO to end the conflict should not have been offered before. At die same time, it is important to acknowledge that the Kosovo intervention may represent a sea change in die responsibility of multilateral organizations to attempt to thwart ethnic slaughter—even if multilateralism takes a different form. Kosovo did not happen in isolation, but after the United Nations was unable to act effectively in Rwanda and Bosnia. The veto of the permanent members of the Security Council has often thrown a monkey wrench in die machinery of collective security, and a mature judgment is required to test whether strict proceduralism should be applied. The Secretary-General's call for Council action to meet future humanitarian crises may inspire unified support for the \"developing international norm in favour of intervention to protect civilians from wholesale slaughter.\" Even after the Cold War, one wants to avoid undue provocation of major powers, and to preserve the centrality of the Council as a forum for the resolution of security disputes. But the admonition to \"never say never\" must apply as well. Legitimacy—and legality—represent a complex cultural process not confined to the Council chamber.

Beyond Productivity: How Leading Companies Achieve Superior Performance by Leveraging Their Human Capital

Abstract: Changing the rules of the game finding and keeping "the best and the brightest" technology - building bridges and leveraging capabilities designing organizations - eliminating the barriers incentives and boundaries making it happen - leadership and organizational learning strategies for implementation.

Kosovo: a 'good' or 'bad' war?

Abstract: ing. Because the Council neither authorized NATO's actions before they commenced nor approved them subsequently in its resolution of June 10, 1999, their legality remains questionable, at best. In fact, the Kosovo intervention reflects the problems of an undeveloped rule of law in a morally dangerous situation. It was actually an \"anticipatory humanitarian intervention\" based on past actions of the FRY regime and future risks. Such intervention, like \"anticipatory self-defense,\" is a particularly dangerous permutation of an already problematic concept. Although many will share the view that the intervention was morally just in light of subsequent developments, it presents an unfortunate precedent. If this action stands for the right of foreign states to intervene in the absence of proof that widespread grave violations of international human rights are being committed, it leaves the door open for hegemonic states to use force for purposes clearly incompatible with international law. Perhaps the example of Kosovo may stimulate the development of a new rule of law that permits intervention by regional organizations to stop these crimes without the Security Council's authorization, while limiting the risks of abuse and escalation. That is the task for the future.

A parallel scalable infrastructure for OLAP and data mining

Abstract: Decision support systems are important in leveraging information present in data warehouses in businesses like banking, insurance, retail and health care. The multidimensional aspects of a business can be naturally expressed using a multidimensional data model. Data analysis and data mining on these warehouses pose new challenges for traditional database systems. OLAP and data mining operations require summary information on these multidimensional data sets. Query processing for these applications require different views of data for analysis and effective decision making. Data mining techniques can be applied in conjunction with OLAP for an integrated business solution. As data warehouses grow, parallel processing techniques have been applied to enable the use of larger data sets and reduce the time for analysis, thereby enabling evaluation of many more options for decision making. We address: (1) scalability in multidimensional systems for OLAP and multidimensional analysis; (2) integration of data mining with the OLAP framework; and (3) high performance by using parallel processing for OLAP and data mining. We describe our system PARSIMONY-Parallel and Scalable Infrastructure for Multidimensional Online analytical processing. This platform is used both for OLAP and data mining. Sparsity of data sets is handled by using sparse chunks using a bit encoded sparse structure for compression. Techniques for effectively using summary information available in data cubes for data mining are presented for mining association rules and decision tree based classification. These take advantage of the data organization provided by the multidimensional data model. Performance results for high dimensional data sets on a distributed memory parallel machine (IBM SP-2) show good speedup and scalability.

Exploring E-Commerce, Global E-Business, and E-Societies

Abstract: I. WHAT IS E-COMMERCE? 1. E-commerce: An Historical Perspective. The Internet Used for Business. Internet History. The Internet's potential for e-commerce. 2. The Internet Evolution and Social Changes. A Fifth Paradigm in Computing. Industrial Changes with the Internet. 3. The Distinction: E-commerce and E-business. E-Business within a World of E-commerce. E-business Design Quality Aspects. Building e-business, Increasing Business Values. Building an e-business. Network Planning. Systems Management Planning. Performance and Capacity on Demand. Hacker-Proof e-businesses. Scalable, Reliable, and Secure e-business Sites. Customer Retention. Customer Care in e-business Environments. Business Continuity Requirements: An Imperative for E-businesses. 4. The Importance of Advanced Research. Experimental Epistemology. The Practitioner's Viewpoint. 5. Businesses That Leverage E-commerce. Significant Research of e-commerce Contenders. The Costs of Internet Trading. Industrial E-commerce Market Share Increases. 6. E-commerce, Management, and Organizations. Transforming Business. Managing and Leveraging Knowledge. Infrastructure Management. Building Internet Commerce Applications. 7. New Channels That Intensify Competition. Conducting E-business and E-commerce. E-business Factors to Consider. Global E-commerce Communities. II. E-COMMERCE CHANNELS TO GENERATE PROFITABLE REVENUES. 8. E-business Life-Cycle Patterns. Life-Cycle Strategies Will Be Challenged. Virtual Commerce. Business Change. 9. Challenges Surrounding E-banking. e-banking Leverages e-commerce. Notion of Mass-Market and E-banking. e-banking Competition. Content Aggregators. E-banking Dependencies on Technologies. Established Brands. E-banking within the Community Interest Site. 10. E-business Enablers. e-business Catalyst. Lead from the Front. The E-business Effect. Market Dynamics. Internet Thought Continuum. A White-Heat Pace. III. STRUCTURED TRANSFORMATIONS THROUGH E-COMMERCE. 11. Manufacturing: E-commerce, E-societies, and E-governments. e-governments and e-commerce. Business Intelligence Models. Manufacturing Strategies Leverage e-commerce. Information as a Commodity. Business-to-Business Growth. Virtual Intermediary Communities. 12. E-business Sites That Enhance the User Experience. Few Internet Site Owners Measure Usability. Quantify Your Internet Site's Design Quality. Design Challenges for the Effective Site. Focusing and Holding the Customer's Attention. Site Redesign for Design Excellence. 13. Utilizing the Internet to Extend Market Reach. Business Partners Linked via Technologies. Distribution Channels Linked via Technologies. Maintain Unique Relationships. 14. E-business in Financial Industries. e-commerce and Insurance Companies. e-commerce, Insurance, and Business Change. Cross-Channel Selling-Another Shift. Subsidiaries versus Agent Selling. Open-Finance Specialists. 15. E-commerce Crossing Several Dimensions. Internet Service Providers. The Global E-commerce Theater. Global E-business Services Add Value. Speed is a Barrier. Internet Electronic Bill Presentment and Payment. Banc One. First Union and TransPoint Announce Internet-Based Bill Delivery and Payment. First Union. TransPoint. Mellon Bank. CheckFree to Provide Processing for EDS' Electronic Bill Paying Service. IV. GLOBAL SEGMENTATION. 16. Customer Relationships: E-contracts, E-bills, E-payments, E-care, E-trust. e-bill Presentment. Online Contracting: e-contracts. Financial Services-Trusted Authentication. 17. Examples of E-business Solutions. Background on Boeing's Spare Parts e-business. A Few of the E-business Challenges. Boeing's E-business Solution. 18. Automotive Industry E-business Solutions. Background on the Manufacturer's Problem. The Automotive Business Problem. The Automotive E-business Solution. E-business Solution Results. 19. Internet E-business Value Chain Management. Procurement e-business Solutions. E-procurement Business Problems. e-procurement Business Solutions. E-business Solution Results. 20. E-business Enhances the Supply Chain. Supply Chain e-business Challenge. Supply Chain E-business Problem. Supply Chain E-business Solution. Supply Chain e-business Solution Results. V. UNIQUE MANAGEMENT AND ORGANIZATIONAL CHALLENGES. 21. E-insurance: Reduces Costs and Increases Revenue. E-business Challenge Overview. Background on the E-business Problem. The E-insurance E-business Problem. The E-business Solution. Critical Issues in the E-business Path. The E-business Solution Results. 22. Security and Privacy. Digital Signatures. Establishing Security Policies. 23. The Extended E-business Enterprise. Travelocity's e-commerce Design Overview. The Travelocity Logical Architecture. Legacy and Internet Engines Are Complementary. Transactions: The Internet to Legacy Systems. Performance and Speed. Testing. Firewall Systems. System Reliability and Availability. 24. Conclusion. Appendix A. Appendix B. Appendix C. Index.

Erp Packages: What's Next?

Abstract: The traditional focus of IT operations no longer meets the challenges of tomorrow's fast-changing business environment. in the new millennium, CIOs will be required to shift their focus from internal information processing to external information processing. By taking on the role of “corporate antenna” and generating the business intelligence that matters, IT will, for the first time in history, start to exercise its true strategic role on corporate operations.

Application of intelligent agent technology for managerial data analysis and mining

Abstract: Data analysis and mining technologies help bring business intelligence into organizational decision support systems (DSS). While a myriad of data analysis and mining technologies are commercially available today, organizations are seeing a growing gap between powerful storage (data warehouse) systems and the business users' ability to analyze and act effectively on the information they contain. We contend that to narrow this gap effectively, a data analysis and mining environment is needed that can bring together and make available for use many of these technologies, that can support business users with different backgrounds, and with which the users can work comfortably.This paper illustrates the design and construction of such an environment, called the Intelligent Data Miner. IDM is Web-based and it is intended to provide an organization-wide decision support capability for business users. Intelligent agent technology is used as the basis for IDM design. IDM provides several types of data access capabilities to access and analyze the data contained in a data warehouse to obtain the critical information needed by business decision-makers. It supports both predefined and ad hoc data access, data analysis, data presentation, and data mining requests from non-technical users.An operational prototype of IDM, implemented using Java and JATLite (Java Agent Template, Lite from Stanford University), allowed us to examine the feasibility of having the "agents" automatically control and coordinate activities and tasks on the business users' behalf. These agents proved to hide the complexity of data analysis and mining activities, techniques, and methods from the business users, for effective use of the warehouse data.

Data mining: new arsenal for strategic decision-making

Abstract: During the early years of database management the contemporary wisdom was to store only ‘useful data.’ In large part, this philosophy was encouraged because of the then-limited storage capacity offered by the prevailing technology. Then along came the microprocessor revolution, enormously expanding the scope of data storage. Subsequent advancement in information technology and recognition of potential business opportunities thereof, resulted in enormous expansion of data storage. Although the future is unknown and unpredictable, it often provides new business opportunities. Thus, new management strategies emerged which encouraged the massive accumulation of data and thus the advent of data warehousing. These massive data depositories are now providing both challenges and opportunities for strategic decision-making concerned with improving existing businesses and exploring new business opportunities. Data mining is an essential part of the process involved in locating relevant information from data warehouses for use in making such strategic decisions. Naturally, business leaders everywhere are willing to make investments in corporate data warehouses to enhance their access to information. The return on such investment is by no means guaranteed but all business activities include a certain amount of risk.

Practical lessons in supporting large-scale computational science

Abstract: Business needs have driven the development of commercial database systems since their inception. As a result, there has been a strong focus on supporting many users, minimizing the potential corruption or loss of data, and maximizing performance metrics such as transactions-per-second and benchmark results [Gra93]. These goals have little to do with supporting business intelligence needs such as the decision support and data mining activities common in on-line analytic processing (OLAP) applications. As a result, business data are typically off-loaded to secondary systems before these activities occur. In addition, they have little to do with the needs of the scientific community, which typically revolve around a great deal of compute and I/O intensive analysis, often over large data with high dimensionality. For scientific data, in many cases the data was never collected in a DBMS in the first place, and so the analysis and visualization take place over specialized flat-file formats. This is a painful solution, because a DBMS has much to offer in the overall process of managing and exploring data.

CRM Definitions — Defining customer relationship marketing and management

Abstract: There is no universally agreed definition of customer relationship management. Find out how leading experts define the term — and what the corporate world makes of the concept.

Data analysis and mining environment: a distributed intelligent agent technology application

Abstract: There is a tremendous explosion in the amount of data that organizations generate, collect and store. Managers are beginning to recognize the value of this asset, and are increasingly relying on intelligent systems to access, analyze, summarize, and interpret information from large and multiple data sources. These systems help them make critical business decisions faster or with a greater degree of confidence. Data mining is a promising new technology that helps bring business intelligence into these systems. While there is a plethora of data mining techniques and tools available, they present inherent problems for end‐users such as complexity, required technical expertise, lack of flexibility and interoperability, etc. These problems can be mitigated by deploying software agents to assist end‐users in their problem solving endeavors. This paper presents the design and development of an intelligent software agent based data analysis and mining environment called IDM, which is utilized in decision making activities.

The WarRoom Guide to Competitive Intelligence

Abstract: The article presents a review of the book “The WarRoom Guide to Competitive Intelligence,” by Steven M. Shaker and Mark P. Gembicki.

Business intelligence : the IBM solution

Abstract: Introduction Do You Need Business Intelligence Installation Creating a Data Warehouse Making a Connection to the Data Warehouse Business Views More about Business Views Business Views for Data Transformation The Work in Progress Window Data from Disparate Sources Security DataGuide Overview of Visual Warehouse Components OLAP Concepts and Terminology Installing DB2 Server Using the Ready-Built Samples More About the Outline Editor Creating Your First Cube Data Load Rules Anchor Dimensions, and a Few More Concepts and Pointers Visual Warehouse and DB2 OLAP Server Symbiosis Appendix 1: Overview of Data Warehousing Appendix 2: IBM's Other Business Intelligence Solutions.