Topic
Data mart
About: Data mart is a research topic. Over the lifetime, 559 publications have been published within this topic receiving 8550 citations.
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TL;DR: The idea of using statistical methods to model federated data marts is presented and advantages include: quick query responses without accessing external servers; user-defined accuracy of the approximate query answers and network-efficient method for periodical updates.
Abstract: The global business deals with a large amount of business data that are stored in potentially hundreds of distributed systems. It is challenging to allow end-users issue online analytical processing (OLAP) queries to retrieve suitable information through a worldwide network. This article presents the idea of using statistical methods to model federated data marts. Once data marts are modelled, reduced sets of distributed data can be imported and used to approximately reconstruct a federated data mart. Approximate queries can then be obtained from the reconstructed federated data mart. Advantages of this design include: quick query responses without accessing external servers; user-defined accuracy of the approximate query answers and network-efficient method for periodical updates. A proof of concept is presented using large data sets used for marketing analysis purposes.
2 citations
16 Nov 2013
TL;DR: This research uses student data from three faculties in Maranatha Christian University and lecturer data from the same university to create data mart schema, which builds lecturer fact constellation schema data warehouse.
Abstract: The growth in the university can be seen with number of student that increase from time to time, which is called student body. The growth in student body results a big data of student's academic. Besides students, other important component in the university is a lecturer. The growth in the number of student should be accompanied by an increase of lecturer, both in quality and quantity. Data set of student and lecturer in such amount contain information or knowledge that can be analyzed. Based on the knowledge which is resulted from the analyze of student data and lecturer data, university can make a strategic plan for the future work plan. Data warehouse is used to analyze that studnet data and lecturer data. As a study case, this research using student data from three faculties in Maranatha Christian University and lecturer data from the same university. As the result, data mart schema are created for two parts, data mart schema for student and data mart schema for lecturer. There are three star schema for student, new student schema, active student schema, and graduated student schema. For lecturer, there are also three schema, lecturer education schema, lecturer research schema, and lecturer community service schema. Integration of three star schema of student builds student fact constellation schema data warehouse. There is also integration of three star schema of lecturer, which builds lecturer fact constellation data warehouse.
2 citations
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01 Jan 2013
TL;DR: Business Intelligence link to an EDA (Event Driven Architecture) for a “Zero Latency Organization” (ZLO) that automates the very labor-intensive and therefore time-heavy and expensive process of planning and executing an event-driven architecture.
Abstract: Business Intelligence link to an EDA (Event Driven Architecture) for a “Zero Latency Organization”
2 citations
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16 Aug 2006TL;DR: An intelligent prototype with object-oriented methodology is designed and an agent-based algorithm to process the special information in data mining on data warehousing, together with the corresponding rule for mathematic model is introduced.
Abstract: In this paper, we intend to do research and implementation of an intelligent object-oriented prototype for data warehouse. We design an intelligent prototype with object-oriented methodology, also we summarize some basic requirements and data model constructing for applying data warehouse in population fields. Finally, we introduce the research of an agent-based algorithm to process the special information in data mining on data warehousing, together with the corresponding rule for mathematic model. It is fitful to be used especially on statistic field.
2 citations
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01 Jan 2000
TL;DR: This article discusses how the use of data marts can help you to implement the traditional enterprise data warehouse.
Abstract: This article discusses how the use of data marts can help you to implement the traditional enterprise data warehouse.
2 citations