scholarly journals A UML Profile for Modeling Data Warehouse Usage

2007 ◽  
pp. 137-147 ◽  
Author(s):  
Veronika Stefanov ◽  
Beate List
Keyword(s):  
Data Warehouse ◽  
Uml Profile ◽  
Modeling Data

On Modeling Data for IoT Agroecology Applications by means of a UML Profile

2021 ◽  
Author(s):  
Amina Belhassena ◽  
Sandro Bimonte ◽  
Pietro Battistoni ◽  
Christophe Cariou ◽  
Gerard Chalhoub ◽  
...  
Keyword(s):  
Uml Profile ◽  
Modeling Data

scholarly journals Modelling of Data Warehouse on Food Distribution Center and Reserves in the Ministry of Agriculture

2015 ◽  
Vol 6 (3) ◽  
pp. 422
Author(s):  
Edi Purnomo Putra ◽  
Fifilia Fifilia ◽  
Lay Christian ◽  
Hantze Sudarma
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Design Method ◽  
Food Distribution ◽  
Distribution Center ◽  
Top Management ◽  
Activity Diagram ◽  
Modeling Data ◽  
Entity Relationship ◽  
Entity Relationship Diagram

The purpose of this study is to perform database’s planning that supports Prototype Modeling Data Warehouse in the Ministry of Agriculture, especially in the Distribution Center and Reserves in the field of distribution, reserve and price. With the prototype of Data Warehouse, the process of data analysis anddecision-making process by the top management will be easier and more accurate. Research’s method used was data collection and design method. Data warehouse’s design method was done by using Kimball’s nine stepsmethodology. Database design was done by using the ERD (Entity Relationship Diagram) and activity diagram. The data used for the analysis was obtained from an interview with the head of Distribution, Reserve and Food Price. The results obtained through the analysis incorporated into the Data Warehouse Prototype have been designed to support decision-making. To conclude, Prototype Data Warehouse facilitates the analysis of data, the searching of history data and decision-making by the top management.

Design and Implementation of Active Stream Data Warehouses

2021 ◽  
pp. 288-311
Author(s):  
Sandro Bimonte ◽  
Omar Boussaid ◽  
Michel Schneider ◽  
Fabien Ruelle
Keyword(s):  
Data Warehouse ◽  
Conceptual Modeling ◽  
Data Warehouses ◽  
Stream Data ◽  
Modeling Tools ◽  
Uml Profile ◽  
Classical Information ◽  
Design And Implementation ◽  
Eca Rules

In the era of Big Data, more and more stream data is available. In the same way, Decision Support Systems (DSS) tools, such as data warehouses and alert systems, become more and more sophisticated, and conceptual modeling tools are consequently mandatory for successfully DSS projects. Formalisms such as UML and ER have been widely used in the context of classical information and data warehouse systems, but they have not been investigated yet for stream data warehouses to deal with alert systems. Therefore, in this article, the authors introduce the notion of Active Stream Data Warehouse (ASDW) and this article proposes a UML profile for designing Active Stream Data Warehouses. Indeed, this article extends the ICSOLAP profile to take into account continuous and window OLAP queries. Moreover, this article studies the duality of the stream and OLAP decision-making process and the authors propose a set of ECA rules to automatically trigger OLAP operators. The UML profile is implemented in a new OLAP architecture, and it is validated using an environmental case study concerning the wind monitoring.

scholarly journals Ontological Re-engineering of Medical Databases

2009 ◽  
Vol 63 (4-5) ◽  
pp. 156-158 ◽  
Author(s):  
Guntis Bārzdiņš ◽  
Sergejs Rikačovs ◽  
Marta Veilande ◽  
Mārtiņš Zviedris
Keyword(s):  
Data Warehouse ◽  
Relational Databases ◽  
Query Language ◽  
Medical Data ◽  
Uml Profile ◽  
Medical Databases ◽  
Owl Ontology ◽  
Rdf Database ◽  
Graphical Query Language

Ontological Re-engineering of Medical Databases This paper describes data export from multiple medical databases (relational databases) into a single shared Medical Data Warehouse (RDF database structured according to an integrated OWL ontology). The exported data is conveniently accessible via SPARQL or via graphical query language ViziQuer based on UML profile for OWL. The approach is illustrated on one of Latvian Medical databases - Injury Register.

Design and Implementation of Active Stream Data Warehouses

2019 ◽  
Vol 15 (2) ◽  
pp. 1-21 ◽  
Author(s):  
Sandro Bimonte ◽  
Omar Boussaid ◽  
Michel Schneider ◽  
Fabien Ruelle
Keyword(s):  
Data Warehouse ◽  
Conceptual Modeling ◽  
Decision Making Process ◽  
Data Warehouses ◽  
Stream Data ◽  
Modeling Tools ◽  
Uml Profile ◽  
Classical Information ◽  
Eca Rules

In the era of Big Data, more and more stream data is available. In the same way, Decision Support Systems (DSS) tools, such as data warehouses and alert systems, become more and more sophisticated, and conceptual modeling tools are consequently mandatory for successfully DSS projects. Formalisms such as UML and ER have been widely used in the context of classical information and data warehouse systems, but they have not been investigated yet for stream data warehouses to deal with alert systems. Therefore, in this article, the authors introduce the notion of Active Stream Data Warehouse (ASDW) and this article proposes a UML profile for designing Active Stream Data Warehouses. Indeed, this article extends the ICSOLAP profile to take into account continuous and window OLAP queries. Moreover, this article studies the duality of the stream and OLAP decision-making process and the authors propose a set of ECA rules to automatically trigger OLAP operators. The UML profile is implemented in a new OLAP architecture, and it is validated using an environmental case study concerning the wind monitoring.

CIM for data warehouse requirements using an UML profile

IET Software ◽  
2017 ◽  
Vol 11 (4) ◽  
pp. 181-194 ◽  
Author(s):  
Omar El Beggar ◽  
Khadija Letrache ◽  
Mohammed Ramdani
Keyword(s):  
Data Warehouse ◽  
Uml Profile

scholarly journals Pemodelan Data Warehouse Distribusi Produk di PT. X

2019 ◽  
Vol 3 (2) ◽  
pp. 196
Author(s):  
Rani Susanto ◽  
Tati Harihayati M
Keyword(s):  
Data Warehouse ◽  
Product Distribution ◽  
Data Sources ◽  
Product Data ◽  
Initial Stage ◽  
Monitoring Process ◽  
Storage Area ◽  
Modeling Data ◽  
Branch Office ◽  
Diverse Data

The purpose of this study is to provide an overview of the Head of Distribution of PT. X to support product distribution monitoring activities in terms of the number of products to be distributed to each branch office as needed. The problem that occurs is the large number and diversity of products required where each branch office is located far apart, cause the company difficulty in collecting product data that functions for the monitoring process. The solution to this problem is there needs a model that can be used to collect all the necessary data for monitoring product distribution using the Data warehouse method. This method is used to collect diverse data into a storage area so that users can quickly analyze the data needed. OLTP is part of the Data Warehouse, which is the initial stage of modeling data sources, then with ETL processes, which are the basis for modeling data warehouse schemes. So, this model can be used as a reference to produce useful information for managerial parties PT. X in the next study.

Improving Expressive Power in Modeling Data Warehouse and OLAP Applications

2010 ◽  
pp. 16-40
Author(s):  
Elzbieta Malinowski
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Data Warehouse ◽  
Real World ◽  
Expressive Power ◽  
Relational Model ◽  
Complex Queries ◽  
Modeling Data ◽  
Abstraction Levels ◽  
Decision Support Process

Data warehouse and OLAP systems are widely required during the decision-support process, since they provide integrated data in a form that facilitates the expression of complex queries. In order to exploit both systems to their full capabilities, dimensions with hierarchies must be clearly defined. Dimensions can be of different types and they allow users to see quantified data from different perspectives. Hierarchies are important in analytical applications, since they give users the possibility of representing data at different abstraction levels. However, even though there are different kinds of hierarchies in real-world applications and some of them are already implemented in commercial tools, there is still a lack of a well-accepted conceptual model that allows decision-making users to express their analysis needs. In this chapter, we show how the conceptual multidimensional model can be used to facilitate the representation of complex hierarchies and different kinds of dimensions in comparison to their representation in the relational model and commercial OLAP tools, using as an example Microsoft Analysis Services.

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