scholarly journals A Star Schema for Utility Network Analysis and Visualisation in a Geo-Business Intelligence Environment

Author(s):  
Sasha Sadegholvaad ◽  
◽  
Rohan Wickramasuriya ◽  
Jun Ma ◽  
Pascal Perez ◽  
...  
2019 ◽  
Vol 11 (2) ◽  
pp. 353
Author(s):  
Luciano Moraes da Luz Brum ◽  
Vinícius do Nascimento Lampert ◽  
Sandro da Silva Camargo

Business Intelligence with Data Warehouse technologies are known in the literature as solutions that allow access to business data dynamically and analytical operations on them. Scientific literature lacks works that investigate the current use of these technologies in the agrarian sector, at the international level in the last 10 years. This work presents a bibliometric analysis, which was done through the ProKnow-C methodology, of the application of Business Intelligence and Data Warehouse technologies in the agrarian sector. The objective is to investigate the dissemination of such technologies in this sector in national and international scale. The main findings were the following: number of papers in last years are increasing. Majority of papers were found in the journal named Computers and Eletronics in Agriculture, with a great number of colaborations between authors of France. Few colaborations between authors from different countries were found. Sandro Bimonte was the most cited author. France and India highlight in researches approaching Data Warehouse and Business Intelligence usage in agrarian sciences. The majority of references from Bibliographic Portfolio were from 2001-2010. 66% of papers use some open source technology. Star schema is the most used modelling technique and the use of Unified Modeling Language by authors of France in agricultural Data Warehouse modelling is encouraged. The main limitations were the impossibility of free access in some databases, absence of research on proprietary solutions of technology market in the rural sector and few number of keyword searches.


CCIT Journal ◽  
2012 ◽  
Vol 5 (3) ◽  
pp. 233-250
Author(s):  
Henderi Henderi ◽  
Indri Handayani ◽  
Meta Amalia Dewi

Nowdays, implemented the information systems that are integrated to business processes in the organization has become a primary necessity. Information systems in the organization are mostly used to assist the implementation of enterprise business process. In the generally, the systems have not been able to provide strategic information and assist management for evaluating of the enterprise’s performance. This problems occurs because the most of the information system is built using the data warehouse concept. This problem occurs also in the information system in most universities in the city of Tangerang as the study sample. The solutions for this problem is build information systems that apply the concepts and ways of working with business intelligence using star schema methodologies that can be presented as an enterprise’s performance measurement tools. Business intelligence can also be used as a basis in conducting surveillance for business intelligence can also provide: 1. early information (alert) if there are deviations between performance with a pre-determined goals, 2. Provided a report was automation (automated-feedback), 3. Memonitoring to key performance index (KPI) in real-time. The system development methodology in this reseach using the star schema. Through this approach created an information system with the concept of business intellegence with star schemas methologies that can produce information that is strategic, as needed, and as tools implement enterprise performance measurement. The end result of research is a business intelligence system with a star schema as enterprise performance measurement tools on Higher Education Raharja as a prototype implementation.


2011 ◽  
pp. 136-256 ◽  
Author(s):  
Nikos Karayannidis ◽  
Aris Tsois ◽  
Timos Sellis

Star queries are the most prevalent kind of queries in data warehousing, OLAP and business intelligence applications. Thus, there is an imperative need for efficiently processing star queries. To this end, a new class of fact table organizations has emerged that exploits path-based surrogate keys in order to hierarchically cluster the fact table data of a star schema. In the context of these new organizations, star query processing changes radically. In this chapter, we present a complete abstract processing plan that captures all the necessary steps in evaluating such queries over hierarchically clustered fact tables. Furthermore, we realize the abstract operations in terms of physical operations over the CUBE File data structure. Finally we discuss star query optimization issues over the presented abstract plan.


2004 ◽  
Vol 171 (4S) ◽  
pp. 502-503
Author(s):  
Mohamed A. Gomha ◽  
Khaled Z. Sheir ◽  
Saeed Showky ◽  
Khaled Madbouly ◽  
Emad Elsobky ◽  
...  

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