scholarly journals A layered meta-data approach to the design of joint experimentation data warehouse

Keyword(s):  
Author(s):  
Claudio Jossen ◽  
Lukas Blunschi ◽  
Magdalini Mori ◽  
Donald Kossmann ◽  
Kurt Stockinger
Keyword(s):  

Author(s):  
Hadrian Peter

Data warehouses have established themselves as necessary components of an effective IT strategy for large businesses. To augment the streams of data being siphoned from transactional/operational databases warehouses must also integrate increasing amounts of external data to assist in decision support. Modern warehouses can be expected to handle up to 100 Terabytes or more of data. (Berson and Smith, 1997; Devlin, 1998; Inmon 2002; Imhoff et al, 2003; Schwartz, 2003; Day 2004; Peter and Greenidge, 2005; Winter and Burns 2006; Ladley, 2007). The arrival of newer generations of tools and database vendor support has smoothed the way for current warehouses to meet the needs of the challenging global business environment ( Kimball and Ross, 2002; Imhoff et al, 2003; Ross, 2006). We cannot ignore the role of the Internet in modern business and the impact on data warehouse strategies. The web represents the richest source of external data known to man ( Zhenyu et al, 2002; Chakrabarti, 2002; Laender et al, 2002) but we must be able to couple raw text or poorly structured data on the web with descriptions, annotations and other forms of summary meta-data (Crescenzi et al, 2001). In recent years the Semantic Web initiative has focussed on the production of “smarter data”. The basic idea is that instead of making programs with near human intelligence, we rather carefully add meta-data to existing stores so that the data becomes “marked up” with all the information necessary to allow not-sointelligent software to perform analysis with minimal human intervention. (Kalfoglou et al, 2004) The Semantic Web builds on established building block technologies such as Unicode, URIs(Uniform Resource Indicators) and XML (Extensible Markup Language) (Dumbill, 2000; Daconta et al, 2003; Decker et al, 2000). The modern data warehouse must embrace these emerging web initiatives. In this paper we propose a model which provides mechanisms for sourcing external data resources for analysts in the warehouse.


2011 ◽  
Vol 215 ◽  
pp. 77-82 ◽  
Author(s):  
B.Y. Xu ◽  
H.M. Cai ◽  
C. Xie

Data warehouse (DW) is a powerful and useful technology for decision making in manufacturing enterprises. Because that the operational data often comes from distributed units for manufacturing enterprises, there exits an urgent need to study on the methods of integrating heterogonous data in data warehouse. In This paper, an ontology approach is proposed to eliminate data source heterogeneity. The approach is based on the exploitation of the application of domain ontology methods in data warehouse design, representing the semantic meanings of the data by ontology at database level and pushing the data as data resources to manufacturing units at data warehouse access level. The foundation of our approach is a meta-data model which consists of data, concept, ontology and resource repositories. The model is used in a shipbuilding enterprise data warehouse development project. The result shows that with the guide of the meta-data model, our ontology approach could eliminate the data heterogeneity.


KURVATEK ◽  
2018 ◽  
Vol 3 (1) ◽  
pp. 63-69
Author(s):  
Siti Jamilah Tarigan ◽  
Wing Wahyu Winarno ◽  
Henderi Safei
Keyword(s):  

Pengambilan keputusan dan perencanaan bidang akademik sering kali tidak berdasarkan pada informasi yang lengkap. Jajaran pengambil keputusan (rektorat atau tingkat eksekutif) hanya bisa melihat sebuah data dalam satu dimensi. Pengambil keputusan akan lebih baik jika informasi dapat disajikan dari berbagai dimensi. Perguruan tinggi telah memiliki data operasional yang lengkap dari kegiatan akademik, kepegawaian, dan penerimaan mahasiswa yang telah dikumpulkan lebih dari 4 tahun. Data warehouse adalah suatu koleksi optimasi database untuk mendukung keputusan. Konsep ini mengintegrasikan antara sistem lama dan sistem baru sehingga tidak terjadi duplikasi data. Data yang telah diintegrasikan dapat diolah dalam berbagai bentuk laporan sesuai dengan kebutuhan.Tujuan dari penelitian ini adalah bagaimana data yang ada bisa menghasilkan informasi yang akurat dan multidimensi sehingga pengambilan keputusan lebih cepat dan akurat. Penelitian ini menggunakan analisis data OLAP, dan skema bintang. Kesimpulan dari penelitian ini adalah rancangan yang dihasilkan bisa membantu pihak akademik dalam membuat keputusan berdasarkan data dan informasi yang mulitidimensi.


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