Practical Approaches of Transforming ER Diagram into Tables (original) (raw)
Related papers
International Journal of Database Management Systems, 2010
In this paper an Articulated Entity Relationship (AER) diagram is proposed, which is an extension of Entity Relationship (ER) diagram to accommodate the Functional Dependency (FD) information as its integral part for complete automation of normalization. In current relational databases (RDBMS) automation of normalization by top down approach is possible using ER diagram as an input, provided the FD information is available independently, meanwhile, through user interaction. Such automation we call partial and conditional automation. To avoid this user interaction, there is a strong need to accommodate FD information as an element of ER diagram itself. Moreover, ER diagrams are not designed by taking into account the requirements of normalization. However, for better automation of normalization it must be an integral part of conceptual design (ER Diagram). The prime motivation behind this paper to design a system that need only proposed AER diagram as a sole input and normalize the database up to a given normal form in one go. This would allow more amount of automation than the current approach. Such automation we call as total and unconditional automation, which is better and complete in true sense. As the proposed AER diagram is designed by taking in to account the normalization process, normalization up to Boyce Codd Normal Form (BCNF) becomes an integral part of conceptual design. Additional advantage of AER diagram is that any modifications (addition, deletion or updation of attributes) made to the AER diagram will automatically be reflected in its FD information. Thus description of schema and FD information is guaranteed to be consistent. This cannot be assured in current approach using ER diagrams, as schema and FD information are provided to the system at two different times, separately.
Relational Database Design: A Review
International Journal of Computer Applications, 2017
Relational Database Designing and Normalization approach is an essential work for the designing of relation up to higher normal form in the field of Database designer. Database Relation stored information into two dimensional matrix form i.e. rows and column. The task of Normalization is to remove data redundancy, data inconstancy and maintain atomicity within the database relation. Key is an attribute of a relation that indentifies the tuple within a database relation, uniquely. This key attribute is generated by applying the closure operations on a given set of functional dependency. Functional dependency of a relation shows the various relations between the attributes and entity relationship diagram shows the prototype of the relation from which designer derived the functional dependency. Relational Database Designing has been spaciously studied and reviewed by many researchers previously; still the works is going on in this area. This paper review the various researches works do...
A Proposal for Constructing Relational Database from Class Diagram
2010
Database system is important to ensure the data can be stored, updated and retrieved for future use. Data modelling using the Entity Relationship Model has been introduced more than thirty years. However, designing a good database system is still an attractive issue particularly in system analysis and design because of very hard to do consistency checking between system design and database design. In this paper, a proposal for designing a relational database system based on Object Oriented Analysis and Design is presented. The database system is created by the schema table that extract from class diagram. The rules applying in this paper is following the object oriented concept. It is based on the relationships among the classes, multiplicity, attributes name, class name, data type and the behaviours of the classes. Beside that the user is required to insert record to accomplish a good designing the schema tables to avoid redundancy data. Finally, an automatic editor called CDGeST is proposed in order to automate the process.
Design Theory of Relational Databases
2015
69. Where we are. Over the last few weeks we have looked at conceptual design via entity relationship diagrams, and last lecture we discussed how such a diagram can be translated into actual tables. If the conceptual model was sufficiently accurate and adequate, then the resulting tables will constitute a very good starting point for the logical design. It is unlikely, however, that the tables are already in the optimal shape for representing the real-world data. Indeed, it is very common that certain redundancies remain; such redundancies will lead to inefficiencies and are sources of potential errors. As part of the logical design phase, therefore, we should have a close look at each table that results from ER modelling. The single most effective technique for doing so is to check the tables for potential functional dependencies. Once these have been established, the tables can be optimized in a fairly mechanical procedure, called normalisation. This will be the topic of the next ...
A Comparative Analysis of Entity-Relationship Diagrams
1995
The purpose of this article is to collect widely used entity-relationship diagram (ERD) notations and so their features can be easily compared, understood, and converted from one notation to another. We collected ten different ERD notations from text books and CASE tools. Each notation is depicted using a common problem and includes a discussion of each characteristic and notation. According to our investigation, we have found that ERD features and notations are different in seven features: whether they allow n-ary relationships, whether they allow attributes in a relationship, how they represent cardinality and participation constraints, the place where they specify constraints, whether they depict overlapping and disjoint subclass entity-types, whether they show total/partial specialization, and whether they model the foreign key at the ERD level. We conclude that many of the ER diagrams we studied are different in how they depict the criteria listed above. In order to convert one...
The translation of star schema into entity-relationship diagrams
Database and Expert Systems Applications. 8th International Conference, DEXA '97. Proceedings, 1997
The star schema is widely accepted as a proper underlying table structure for data warehouses, but enterprise data is frequently defined in terms of entity-relationship diagrams. A key issue for data warehouse designers is how to move from legacy OLTP designs into the star schema. In this paper, we examine the semantics and constraints of the star schema in some of its different forms and translate them into analogous ERDs. These different forms include the simple, multi-star, and snowflaked star schema, and several variations on facts and dimensions such as associative, multple fact and outboard dimension tables. We outline transformation rules for each case and show a series of examples. We believe that these heuristics can be used in mapping and maintaining consistency between OLTP databases and data warehouses.
Entity-Relationship Modeling Re-revisited
Lecture Notes in Computer Science, 2004
Since its introduction, the Entity-Relationship (ER) model has been the vehicle of choice in communicating the structure of a database schema in an implementation-independent fashion. Part of its popularity has no doubt been due to the clarity and simplicity of the associated pictorial Entity-Relationship Diagrams ("ERD's") and to the dependable mapping it affords to a relational database schema. Although the model has been extended in different ways over the years, its basic properties have been remarkably stable. Even though the ER model has been seen as pretty well "settled," some recent papers, notably [4] and [2 (from whose paper our title is derived)], have enumerated what their authors consider serious shortcomings of the ER model. They illustrate these by some interesting examples. We believe, however, that those examples are themselves flawed. In fact, while not claiming that the ER model is perfect, we do believe that the overhauls hinted at are probably not necessary and possibly counterproductive.
ADDS: A system for automatic database schema design based on the Binary-Relationship model
Data & knowledge engineering, 1987
This paper presents the system ADDS that has been developed to assist the database designer designing a database schema. A distinction is made between the stage of information structure analysis, in which the information structure of the system is defined according to its user information needs, and the stage of database schema design, in which the record types of the database and the relationships between them are defined. In the first stage a conceptual schema is obtained, represented as an information structure diagram (ISD), and in the later stage the ISD is used to derive the database schema in the form of a data structure diagram (DSD). ADDS automatically creates the database schema out of a conceptual schema which is expressed as an ISD of the binary-relationship data mode. The resulting schema consists of normalized record types, according to the relational model, along with hierarchical/set relationships between ‘owner’ and ‘member’ record types. ADDS applies algorithms to convert the conceptual schema into the relational database schema.
WSEAS Transactions on Information …, 2004
Conceptual modeling is one of the most important phases in designing database applications. The success of this design relies heavily on how clearly the real world requirements are represented in the conceptual model. To date, the Extended Entity Relationship (EER) model extended from the traditional Entity Relationship (ER) model is a widely used modeling technique during the phase of conceptual modeling. This paper identifies semantic ambiguities that are still present in the EER model leading to incorrect knowledge representation and eventually to incorrect design of relational database schema. These ambiguities are identified in case of many-to-many relationships which have their own attributes. This paper shows that mapping such relationships to a relational database schema generates relations having primary keys which cannot guarantee unique tuples for real world data thus violating the definition of a primary key. In addition, it shows that these relations may not satisfy second normal form. A number of such cases are elaborated and a new concept of multi-valued relationship attribute is introduced that can successfully represent these real world constraints. For this concept, a diagrammatic notation to use in ER diagram is introduced. A mapping algorithm to transform the corresponding EER model to a relational database schema is also defined. This concept of multi-valued relationship attribute and its mapping to relational schema generate relations which satisfy higher normal forms.
Improving database design through the analysis of relationships
ACM Transactions on Database Systems, 1999
Much of the work on conceptual modeling involves the use of an entity-relationship model in which binary relationships appear as associations between two entities. Relationships involving more than two entities are considered rare and, therefore, have not received adequate attention. This research provides a general framework for the analysis of relationships in which binary relationships simply become a special case. The framework helps a designer to identify ternary and other higher-degree relationships that are commonly represented, often inappropriately, as either entities or binary relationships. Generalized rules are also provided for representing higher-degree relationships in the relational model. This uniform treatment of relationships should significantly ease the burden on a designer by enabling him or her to extract more information from a real-world situation and represent it properly in a conceptual design.