Data mart

About: Data mart is a research topic. Over the lifetime, 559 publications have been published within this topic receiving 8550 citations.

Method and apparatus for processing business information from multiple enterprises

Abstract: A method for processing business information generated by multiple enterprises is provided. Initially, a data warehouse is provided that has the capability of holding business information. The data warehouse is populated with business information received from a first enterprise and a second enterprise. The business information is associated with the first and second enterprise based upon a set of standardized categories used in the data warehouse. Metastore information describing the organization of business information in the data warehouse is used to develop rules for extracting a portion of the business information from the data warehouse. This portion of business information extracted from the data warehouse is then stored in the data mart. Using at least one such data mart, a multiple dimension database is created wherein each dimension of the multiple dimension database corresponds to variables derived from business rules established in an industry. Using the multiple dimension database, metrics for measuring business performance from the multiple dimension databases are then generated.

Analysing users' access logs in Moodle to improve e learning

Abstract: In this work the UFSC (Federal University of Santa Catarina) and the FGV-RJ (Fundacao Getulio Vargas do Rio de Janeiro) jointly propose the use of a data mining tool to support the analysis of trends, students profiles, as well as to estimate or foresee the usability level of courses being offered, via Moodle, in the Education area. The study carried out by UFSC on the Moodle database allowed a deep understanding of its database, thus making it easier for the Moodle community to execute important tasks, such as the maintenance of the Moodle database, its adaptation following an institutional customization, and, also, a data mart project by the FGV-Online Program to make the necessary analysis possible. In the end of this paper, an example on its applicability is presented, using the association rules technique. Once a data mart oriented to the analysis of the system's usability is developed, various analyses with different objectives can be executed using the database. Some may use the method proposed here or others, including different data mining approaches, such as clustering, neural networks etc. As such, a new contribution is given to the Moodle community.

Relational Modeling and Data Warehouse Design

Abstract: From the Publisher: At last, a balanced approach to data warehousing that leverages the techniques pioneered by Ralph Kimball and Bill Inmon Since its groundbreaking inception, the approach to understanding data warehousing has been split into two mindsets: Ralph Kimball, who pioneered the use of dimensional modeling techniques for building the data warehouse, and Bill Inmon, who introduced the Corporate Information Factory and leads those who believe in using relational modeling techniques for the data warehouse. Mastering Data Warehouse Design successfully merges Inmon’s data ware- house design philosophies with Kimball’s data mart design philosophies to provide you with a compelling and complete overview of exactly what is involved in designing and building a sustainable and extensible data warehouse. Most data warehouse managers, designers, and developers are familiar with the open letter written by Ralph Kimball in 2001 to the data warehouse community in which he challenged those in the Inmon camp to answer some tough questions about the effectiveness of the relational approach. Cowritten by one of the best-known experts of the Inmon approach, Claudia Imhoff, this team of authors addresses head-on the challenging questions raised by Kimball in his letter and offers a how-to guide on the appropriate use of both relational and dimensional modeling in a comprehensive business intelligence environment. In addition, you’ll learn the authors’ take on issues such as: Which approach has been found most successful in data warehouse environments at companies spanning virtually all major industrial sectors The pros and cons of relational vs. dimensional modeling techniques so developers can decide on the best approach for their projects Why the architecture should include a data warehouse built on relational data modeling concepts The construction and utilization of keys, the historical nature of the data warehouse, hierarchies, and transactional data Technical issues needed to ensure that the data warehouse design meets appropriate performance expectations Relational modeling techniques for ensuring optimum data warehouse performance and handling changes to data over time * A cutting-edge response to Ralph Kimball's challenge to the data warehouse community that answers some tough questions about the effectiveness of the relational approach to data warehousing * Written by one of the best-known exponents of the Bill Inmon approach to data warehousing * Addresses head-on the tough issues raised by Kimball and explains how to choose the best modeling technique for solving common data warehouse design problems * Weighs the pros and cons of relational vs. dimensional modeling techniques * Focuses on tough modeling problems, including creating and maintaining keys and modeling calendars, hierarchies, transactions, and data quality Author Biography: CLAUDIA IMHOFF (CImhoff@Intelsols.com) is President and Founder of Intelligent Solutions, a leading consultancy on analytic CRM and BI technologies and strategies. She is a popular speaker, an internationally recognized expert, and coauthor of five books. NICHOLAS GALEMMO (ngalemmo@yahoo.com) was Information Architect at Nestle USA. He has twenty-seven years’ experience as a practitioner and consultant involved in all aspects of application systems design and development. He is currently an independent consultant. JONATHAN G. GEIGER (JGeiger@IntelSols.com) is Executive Vice President at Intelligent Solutions, Inc. In his thirty years as a practitioner and consultant, he has managed or performed work in virtually every aspect of information management.

Business and e-government intelligence for strategically leveraging information retrieval

Abstract: The purpose of this paper is to provide practitioners of information exploration of the need for Business and e-Government Intelligence Systems (BGIS), the role such intelligence plays in competitive market research, industry, through the comparison of vendors, advantages and disadvantages, comparing the costs and benefits and some future insights. A review of the applied literature on topics that focus is on utilising Business Intelligence (BI) as a competitive tool in an online retrieval environment. The growth for BI systems may be dramatic [actual (2004, $5.3 billion; 2004, $5.6 billion) and predicted growth (2005, $6 billion; 2006, $6.5 billion; 2007, $7 billion and in 2008, $7.3 billion)], its associated costs may be equally stunning, especially in end-user query, reporting, analysis, data-mining applications and packaged data mart and/or warehousing applications. However, the figures reported in the paper should support the notion that BGIS-related systems' applications are potentially a good investment and worthy of considerable research in the knowledge management fields.

Automatic construction of multidimensional schema from OLAP requirements

Abstract: Summary form only given. The manual design of data warehouse and data mart schemes can be a tedious, error-prone, and time-consuming task. In addition, it is a highly complex engineering task that calls for methodological support. This paper lays the grounds for an automatic generation approach of multidimensional schemes. It first defines a tabular format for OLAP requirements. Secondly, it presents a set of algebraic operators used to transform automatically the OLAP requirements, specified in the tabular format, to data mart modelled either as star or constellation schemes. Our approach is illustrated with an example.