Showing papers on "Data mart published in 1997"

Understanding and Implementing Successful Data Marts

Abstract: Data marts are beginning to emerge from the shadow of their all-encompassing, enterprise-scale cousins, data warehouses, as a more timely and cost-effective approach to organizing and accessing critical business data. Easier, quicker, and less expensive to design and implement, data marts can be designed to meet the specific needs ental concepts and guides you step-by-step through the entire data mart process, from the initial planning stages through implementation and maintenance. With an emphasis on "success," the author draws from his many years of real-world experience to reveal potential pitfalls and offer helpful tips that can make the difference between success and failure in the implementation of a working data mart. You will find thorough coverage of available technologies, fundamental design, specific methodologies, and industry trends. The two major types of data marts are covered: the subset data mart and the increasingly popular incremental data mart, with a special emphasis placed on integration issues.The book also details each step involved in the creation of a data mart: identifying business drivers, forming a team, surveying users, choosing among tools and design options, working with meta data, incorporating company culture into implementation strategy, and even training and support. In the process, you will learn about the different types of data mart designs and architectures, virtual data warehouses, data islands, decision dupport system tools, and much more. Acknowledging that plans don't always proceed smoothly, the author "reality checks"--highlighted sections that discuss what happens when data mart theory meets the reality of the workplace, where sponsors disappear, budgets shrink, and specifications change midstream. 0201183803B04062001

The Data Mart: A New Approach to Data Warehousing

Abstract: (1997). The Data Mart: A New Approach to Data Warehousing. International Review of Law, Computers & Technology: Vol. 11, No. 2, pp. 251-262.

Comparison of the decision support systems and the transaction support system development methodologies

Abstract: There is a substantial difference between the development methodologies of the following two Information Systems: Transaction Support System (TSS) and Decision Support System (DSS). The central concern of the Transaction Support System that supports the operational world in organizations is transaction processing. The retrieval of information for analytical purposes is in the very focus of the Decision Support System. The DSS provoked a series of changes in RDBMS technology. In 1995 the data warehousing was recognized as a new concept. Multi-dimensional architecture of a data model emerged beside the existing relational one. The following year brought an explosion of the OLAP tools. Now the time has come for the full recognition of the DSS development methodology as a separate discipline. This methodology is presented on the following pages. There are obstacles that make it difficult to accept or have a clear view of it. These obstacles are highlighted through the comparison to the TSS developmentmethodology that represents the traditional point of view. Tasks, deliverables, techniques, approaches, differences, similarities and analogies are discussed for each development activity. It is irrelevant for the discussion whether the DSS comprises data warehouse or/and some other store of data of the similar type, e.g. data mart or/and operational data store (ODS). This paper tries to reveal why it is so hard to accept the Decision Support System development methodology.