Physical Data Warehouse Design

2014 ◽  
pp. 233-284
Author(s):  
Alejandro Vaisman ◽  
Esteban Zimányi
Keyword(s):  
Data Warehouse ◽  
Physical Data ◽  
Warehouse Design

scholarly journals Guest editorial: special issue on physical data warehouse design

2009 ◽  
Vol 25 (1-2) ◽  
pp. 1-3
Author(s):  
Ladjel Bellatreche
Keyword(s):  
Data Warehouse ◽  
Guest Editorial ◽  
Special Issue ◽  
Physical Data ◽  
Editorial Special Issue ◽  
Warehouse Design

Physical Data Warehouse Design

2016 ◽  
pp. 195-228
Author(s):  
Daniel Linstedt ◽  
Michael Olschimke
Keyword(s):  
Data Warehouse ◽  
Physical Data ◽  
Warehouse Design

scholarly journals Physical Data Warehouse Design Using Neural Network

2010 ◽  
Vol 1 (3) ◽  
pp. 99-107 ◽  
Author(s):  
Mayank Sharma ◽  
Navin Rajpal ◽  
B.V.R. Reddy
Keyword(s):  
Neural Network ◽  
Data Warehouse ◽  
Physical Data ◽  
Warehouse Design

Physical Data Warehouse Design on NoSQL Databases - OLAP Query Processing over HBase

2016 ◽  
Author(s):  
Lucas C. Scabora ◽  
Jaqueline J. Brito ◽  
Ricardo Rodrigues Ciferri ◽  
Cristina Dutra de Aguiar Ciferri
Keyword(s):  
Query Processing ◽  
Data Warehouse ◽  
Nosql Databases ◽  
Physical Data ◽  
Warehouse Design

scholarly journals BioStar models of clinical and genomic data for biomedical data warehouse design

2005 ◽  
Vol 1 (1) ◽  
pp. 63 ◽  
Author(s):  
Liangjiang Wang ◽  
Aidong Zhang ◽  
Murali Ramanathan
Keyword(s):  
Data Warehouse ◽  
Genomic Data ◽  
Biomedical Data ◽  
Warehouse Design

scholarly journals Perancangan Data Warehouse Rumah Sakit Berbasis Online Analytical Processing (OLAP)

2021 ◽  
Vol 8 (5) ◽  
pp. 1077
Author(s):  
Joko Purwanto ◽  
Renny Renny
Keyword(s):  
Information Technology ◽  
Health Services ◽  
Data Warehouse ◽  
Data Extraction ◽  
Online Analytical Processing ◽  
Data Source ◽  
Analytical Processing ◽  
Quality Of Health Services ◽  
Warehouse Design

<p class="BodyCxSpFirst">Pemanfaatan teknologi informasi sangat penting bagi rumah sakit, karena berpengaruh pula terhadap kualitas pelayanan kesehatan yang secara manual diubah menjadi digital dengan menggunakan teknologi informasi.Dalam penelitian ini penulis menggunakan metodologi <em>Nine step</em> sebagai acuan dalam merancang suatu <em>data warehouse</em><em>,</em> untuk pemodelan menggunakan skema konstelasi fakta dengan 3 tabel fakta dan 11 tabel dimensi. Perbedaan penelitian ini dengan penelitian sebelumnya terletak pada sumber data yang diekstrak langsung dari <em>database</em> SIMRS yang digunakan rumah sakit, sehingga tidak ada ekstraksi data secara manual.Penelitian ini bertujuan untuk menghasilkan desain data warehouse berbasis Online Analytical Processing (OLAP) sebagai sarana penunjang kualitas pelayanan kesehatan rumah sakit. OLAP yang dihasilkan akan berupa desain data warehouse dengan berbagai dimensi yang akan menghasilkan tampilan informasi berupa Chart maupun Grafik sehingga informasinya mudah dibaca dan dipahami oleh berbagai pihak.</p><p class="BodyCxSpFirst"> </p><p class="BodyCxSpFirst"><em><strong>Abtract</strong></em></p><p class="BodyCxSpFirst"><em>The use of information technology is very important for hospitals, because it also affects the quality of health services, which manualy changed to digital using information technology. In this study, the authors used the Nine step methodology as a reference in designing a data warehouse for modeling using a fact constellation schema with 3 fact tables and 11 dimension tables. the different in this study from previous research is that the data source was taken directly from the SIMRS database used by the hospital, so there is no manual data extraction.</em><em>The aim of this research is to be able to produce a Data Warehouse design based on Online Analytical Processing (OLAP) as a means of supporting the quality of hospital health services. The resulting OLAP will be a data warehouse design with various dimensions will produce the displays information in the form of a graph or chart so that the information is easy to read and understand by various parties.</em></p><p class="BodyCxSpLast"><em> </em></p><p class="BodyCxSpFirst"><em><strong><br /></strong></em></p>

HYPAD: Hyper-Graph-Driven Approach for Parallel Data Warehouse Design

2015 ◽  
pp. 770-783 ◽  
Author(s):  
Ahcene Boukorca ◽  
Ladjel Bellatreche ◽  
Soumia Benkrid
Keyword(s):  
Data Warehouse ◽  
Parallel Data ◽  
Warehouse Design
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