Perbandingan Pengaruh Teknik Pemodelan Entity-relationship Model dan Resources-events-agents Model Atas Perancangan Database Perusahaan

Databases are an important part of most computer-based information systems. As such, the design of a database has also gained importance because a bad design will compromise data integrity as well as make it inefficient in its use of resources. This paper compares the effect of two data modeling approaches on the design of a database, specifically the Entity-Relationship Model (ER Model) and the Resources-Events -Agents Model (REA Model). First, the sales/collection cycle of a fictional case study is described. Then, an ER Model and a REA Model are independently created based on this case study. Finally, one database design is created based on the ER Model, and another database design is created based on the REA Model. The outcome of this experiment shows that both approaches produced similar database designs, but the design processes were different in their complexity, structurally, and completeness. A significant difference is that the ER Model closely followed those aspects that were already laid out by the case study, while the REA Model started out by building a most complete data model, over and above the one described in the case study

Perbandingan Pengaruh Teknik Pemodelan Entity-relationship Model dan Resources-events-agents Model Atas Perancangan Database Perusahaan

Databases are an important part of most computer-based information systems. As such, the design of a database has also gained importance because a bad design will compromise data integrity as well as make it inefficient in its use of resources. This paper compares the effect of two data modeling approaches on the design of a database, specifically the Entity-Relationship Model (ER Model) and the Resources-Events -Agents Model (REA Model). First, the sales/collection cycle of a fictional case study is described. Then, an ER Model and a REA Model are independently created based on this case study. Finally, one database design is created based on the ER Model, and another database design is created based on the REA Model. The outcome of this experiment shows that both approaches produced similar database designs, but the design processes were different in their complexity, structurally, and completeness. A significant difference is that the ER Model closely followed those aspects that were already laid out by the case study, while the REA Model started out by building a most complete data model, over and above the one described in the case study

UML Class Diagram or Entity Relationship Diagram : An Object Relational Impedance Mismatch

It is now nearly 30 years since Peter Chen’s watershed paper “The Entity-Relationship Model –towards a Unified View of Data”. [1] The entity relationship model and variations and extensions to ithave been taught in colleges and universities for many years. In his original paper Peter Chen looked at converting his new ER model to the then existing data structure diagrams for the Network model. In recent years there has been a tendency to use a Unified Modelling Language (UML) class diagram forconceptual modeling for relational databases, and several popular course text books use UMLnotation to some degree [2] [3]. However Object and Relational technology are based on different paradigms. In the paper we argue that the UML class diagram is more of a logical model (implementation specific). ER Diagrams on theother hand, are at a conceptual level of database design dealing with the main items and their relationships and not with implementation specific detail. UML focuses on OOAD (Object Oriented Analysis and Design) and is navigational and program dependent whereas the relational model is set based and exhibits data independence. The ER model provides a well-established set of mapping rules for mapping to a relational model. In this paper we look specifically at the areas which can cause problems for the novice databasedesigner due to this conceptual mismatch of two different paradigms. Firstly, transferring the mapping of a weak entity from an Entity Relationship model to UML and secondly the representation of structural constraints between objects. We look at the mixture of notations which students mistakenly use when modeling. This is often the result of different notations being used on different courses throughout their degree. Several of the popular text books at the moment use either a variation of ER,UML, or both for teaching database modeling. At the moment if a student picks up a text book they could be faced with either; one of the many ER variations, UML, UML and a variation of ER both covered separately, or UML and ER merged together. We regard this problem as a conceptual impedance mismatch. This problem is documented in [21] who have produced a catalogue of impedance mismatch problems between object-relational and relational paradigms. We regard the problems of using UML class diagrams for relational database design as a conceptual impedance mismatch as the Entity Relationship model does not have the structures in the model to deal with Object Oriented concepts Keywords: EERD, UML Class Diagram, Relational Database Design, Structural Constraints, relational and object database impedance mismatch. The ER model was originally put forward by Chen [1] and subsequently extensions have been added to add further semantics to the original model; mainly the concepts of specialisation, generalisation and aggregation. In this paper we refer to an Entity-Relationship model (ER) as the basic model and an extended or enhanced entity-relationship model (EER) as a model which includes the extra concepts. The ER and EER models are also often used to aid communication between the designer and the user at the requirements analysis stage. In this paper when we use the term “conceptual model” we mean a model that is not implementation specific.ISBN: 978-84-616-3847-5 3594Peer reviewe

Metamodeling the enhanced entity-relationship model

[EN] A metamodel provides an abstract syntax to distinguish between valid and invalid models. That is, a metamodel is as useful for a modeling language as a grammar is for a programming language. In this context, although the Enhanced Entity-Relationship (EER) Model is the de facto standard modeling language for database conceptual design, to the best of our knowledge, there are only two proposals of EER metamodels, which do not provide a full support to Chen s notation. Furthermore, neither a discussion about the engineering used for specifying these metamodels is presented nor a comparative analysis among them is made. With the aim at overcoming these drawbacks, we show a detailed and practical view of how to formalize the EER Model by means of a metamodel that (i) covers all elements of the Chen s notation, (ii) defines well-formedness rules needed for creating syntactically correct EER schemas, and (iii) can be used as a starting point to create Computer Aided Software Engineering (CASE) tools for EER modeling, interchange metadata among these tools, perform automatic SQL/DDL code generation, and/or extend (or reuse part of) the EER Model. In order to show the feasibility, expressiveness, and usefulness of our metamodel (named EERMM), we have developed a CASE tool (named EERCASE), which has been tested with a practical example that covers all EER constructors, confirming that our metamodel is feasible, useful, more expressive than related ones and correctly defined. Moreover, we analyze our work against the related ones and present our final remarks.Fidalgo, RN.; Alves, E.; España Cubillo, S.; Castro, J.; Pastor López, O. (2013). Metamodeling the enhanced entity-relationship model. Journal of Information and Data Management. 4(3):406-420. http://hdl.handle.net/10251/47949S4064204

The Use of UML Class Diagrams To Teach Database Modelling and Database Design

It is now nearly 30 years since Peter Chen’s watershed paper “The Entity-Relationship Model – towards a Unified View of Data”. [1] The entity relationship model and variations and extensions to it have been taught in colleges and universities for many years. In his original paper Peter Chen looked at converting his new ER model to the then existing data structure diagrams for the Network model. In recent years there has been a tendency to use a Unified Modelling Language (UML) class diagram for conceptual modelling for relational databases, and several popular course text books use UML notation to some degree [2] [3]. This paper looks at the usefulness of using UML class diagrams for teaching database design in undergraduate courses. In this paper we look specifically at two concepts which can cause problems for the novice database designer. Firstly transferring the concept of a weak entity from an Entity Relationship model to UML and secondly the notation for structural constraints in different diagramming notations. We also look at the mixture of notations which students mistakenly use when modelling. This is often the result of different notations being used on different courses throughout their degree. Peter Chen wrote in his original paper “The entity-relationship model can be used as a tool in the structured design of databases using the network model” today we could write “the UML class diagram can be used as a tool in the structured design of databases using the relational model”. Or can we

Software Cost Estimation through Entity Relationship Model

Abstract: Software Cost Estimation is essential for efficient control and management of the whole software development process. Today, Constructive Cost Model (COCOMO 11) is very popular for estimating software cost. In Constructive Cost Model lines of code and function, points are used to calculate the software size. Actually, this work represents the implementation stages but in early stages in software development, it was not easy to estimate software cost. The entity relationship model (ER Model) is very useful in requirement analysis for data concentrated systems. This paper highlights the use of Entity Relationship Model for software cost estimation. Pathway Density is ushered in. By using the Pathway Density and other factors, many regression models are built for estimating the software cost. So in this paper, Entity Relationship Model is based on estimated cost of software

Relational Databases,Logical Databases and the Entity-Relationships Approach

A comparison of relational databases, as known in Data Management, and logical databases, as used in Artificial Intelligence is made. This comparison is then used to examine certain semantic issues raised by the Entity-Relationship Model

ENTITY-RELATIONSHIP MODEL OF “CALCULATION OF TEACHING LOAD”

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