scholarly journals A Data Model Validation Approach for Relational Database Design Courses

10.28945/780 ◽  
2004 ◽  
Vol 1 ◽  
pp. 0813-0825
Author(s):  
Kevin R. Parker
Keyword(s):  
Model Validation ◽  
Relational Database ◽  
Data Model ◽  
Database Design

scholarly journals A Data Model Validation Approach for Relational Database Design Courses

10.28945/2797 ◽  
2004 ◽  
Author(s):  
Kevin R. Parker
Keyword(s):  
Model Validation ◽  
Relational Database ◽  
Data Model ◽  
Database Design ◽  
Instructional Method ◽  
Design Data ◽  
Critical Step

This paper presents an instructional method for validating a relational database design. Data model validation is often overlooked in course projects involving relational database design, in part because while most database texts stress the importance of validation, few provide an instructional method for performing validation. Validation is a critical step, especially for students. A flawed data model may omit non-key attributes or even the foreign keys required to join tables. This can make the design of SQL queries, forms, and reports a frustrating experience. This approach requires the designer to determine which attributes account for the field values on forms and reports, which entities are associated with those attributes, and how those entities are linked to an integral or primary entity. Such an approach serves to validate the completeness of the data model.

scholarly journals Using the REA Data Model in Order to Reduce Design Complexity in an Inventory Management Relational Database, and the Need for a Relational Database Complexity Metric.

2021 ◽  
Vol 9 (7) ◽  
pp. 71-78
Author(s):  
Ian Adamson
Keyword(s):  
Inventory Management ◽  
Relational Database ◽  
Data Model ◽  
Relational Databases ◽  
Database Design ◽  
Business Environment ◽  
Design Complexity ◽  
Data Inconsistency ◽  
A Company

With the extensive use of relational databases in the business environment there is a need to reduce database complexity in order to avoid data inconsistency and redundancy, which can provide a company with unreliable and/or meaningless data and information. The use of the REA Data Model in database design can significantly help with this problem.  The model can eliminate the need for unnecessary data artifacts which should only be generated by the system when needed. This paper also addresses the need for a Relational Database Complexity Metric. A simple and easy to understand metric is presented.

Formalized Approach in Relational Database Design

2016 ◽  
Vol 685 ◽  
pp. 930-933 ◽  
Author(s):  
Victoria V. Osipova ◽  
Igor L. Chudinov ◽  
Aysel S. Seidova
Keyword(s):  
Relational Database ◽  
Data Model ◽  
Database Design ◽  
Domain Model ◽  
Relational Data ◽  
Conceptual Information ◽  
Suggested Approach ◽  
Database Development ◽  
Relational Data Model ◽  
Information Domain

Design of the conceptual information domain model is a significant and complicated stage in database development that influences its quality and can be considered as a skill. The suggested approach is based on analysis of attribute domains and relationships between them and uses the relational data model to determine the availability and the type of relationships between model entities.

scholarly journals Using ontology merging for the integration of information systems and the production capacity planning system

2019 ◽  
pp. 401-408
Author(s):  
N Yarushkina ◽  
A Romanov ◽  
A Filippov ◽  
A Dolganovskaya ◽  
M Grigoricheva
Keyword(s):  
Information System ◽  
Information Systems ◽  
Relational Database ◽  
Data Model ◽  
Capacity Planning ◽  
Production Capacity ◽  
Semantic Integration ◽  
Data Sources ◽  
Planning System ◽  
Ontology Merging

This article describes the method of integrating information systems of an aircraft factory with the production capacity planning system based on the ontology merging. The ontological representation is formed for each relational database (RDB) of integrated information systems. The ontological representation is formed in the process of analyzing the structure of the relational database of the information system (IS). Based on the ontological representations merging the integrating data model is formed. The integrating data model is a mechanism for semantic integration of data sources.

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