Entity Relationship Diagrams

11 Key excerpts on "Entity Relationship Diagrams"

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  eBook - PDF

  Systems Analysis and Design

  • Alan Dennis, Barbara Wixom, Roberta M. Roth(Authors)
  • 2021(Publication Date)
  • Wiley

    (Publisher)

  A full-service CASE tool, in which data modeling is one of many capabilities, may be used with many different databases. A benefit of the full-service CASE tool is that it integrates the data model information with other relevant parts of the project. If a CASE tool is not available, there are numerous software drawing tools that support data modeling, including Visio, Visual Paradigm, and Lucid chart. In this chapter, we focus on creating a logical data model. Although there are several ways to model data, we will present one of the most commonly used techniques: entity relationship dia- gramming, a graphic drawing technique developed by Peter Chen 1 that shows all the data compo- nents of a business system. We will first describe how to create an entity relationship diagram (ERD) and discuss some style guidelines. Then, we will present a technique called normalization that helps analysts validate the data models that they draw. The chapter ends with a discussion of how data models balance, or interrelate, with the process models that you learned about in Chapter 4. The Entity Relationship Diagram An entity relationship diagram (ERD) is a picture which shows the information that is created, stored, and used by a business system. An analyst can read an ERD to discover the individual pieces of information in a system and how they are organized and related to each other. On an ERD, similar kinds of information are listed together and placed inside boxes called entities. Lines are drawn between entities to represent relationships among the data, and special symbols are added to the diagram to communicate high-level business rules that need to be supported by the system. The ERD implies no order, although entities that are related to each other are usually placed close together. 1 P. Chen, “The Entity-Relationship Model—Toward a Unified View of Data,” ACM Transactions on Database Systems, 1976, 1, 9–36.

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  Understanding Databases

  Concepts and Practice

  • Suzanne W. Dietrich(Author)
  • 2021(Publication Date)
  • Wiley

    (Publisher)

  The fundamental components of ER diagrams are entities and relationships. An entity represents the type of an object of interest in the enterprise. In an ER diagram, a rectangular box denotes an entity with the name of the entity given within the rectangle. An entity is described by its characteristics, which are called attributes. Attribute names are enclosed within ovals that are linked by edges to the entity it is describing. An attribute is assumed to have a single value unless it is denoted by a double oval, indicating that the attribute can have multiple values. Some attributes are composite attributes, which are made up of simpler components. A composite attribute is linked to its simpler attributes via edges. Canonical examples of composite attributes are full name, which is com- posed of first and last name, and address, which is made up of the street, city, state, and zip. An attribute whose value uniquely identifies an entity instance is a key attribute, which is indicated by underlining its name. The term key attribute here refers to a candidate key, which was intro- duced in Chapter 1 for the relational data model. Figure 2.1 shows an ER diagram of an abstract entity e with descriptive attributes, summarizing the different types of attributes (single-valued, multivalued, composite, key). 2.2 Entity-Relationship Diagrams 23 e eSingleValuedAttr eKey eCompositeAttr eSimpleAttr1 eSimpleAttr2 eMultiValuedAttr FIGURE 2.1 Abstract ER diagram illustrating entity and attributes. Diamonds indicate relationships between entities. A relationship is an association between entities. The name of a relationship is displayed within a diamond that is linked to the entities involved in the relationship. Binary relationships, which involve two entities, are the most common type of relationship encountered in the conceptual database design process. The edges linking entities to relationships are annotated to describe the cardinality ratio of the relationship.

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  Design Methods for Reactive Systems

  Yourdon, Statemate, and the UML

  • R. J. Wieringa(Author)
  • 2003(Publication Date)
  • Morgan Kaufmann

    (Publisher)

  C H A P T E R 8 Entity-Relationship Diagrams W e use an entity-relationship diagram (ERD) to represent the decomposition of the subject domain of a system into entities. An ERD represents two things: ◆ Which types of entities can exist in the subject domain ◆ How many of them can exist In rare cases, we use ERDs to represent components of the SuD, such as the structure of data in the system. Unless otherwise stated, whenever you see an ERD in this book, you can assume that it represents the decomposition of the subject domain into entities. Figure 8.1 shows an ERD of the subject domain of the heating controller. A rectangle in an ERD represents an entity type. Attributes are written in a box com-partment below the entity type name. Lines represent relationships that are used to represent relative cardinality properties. For example, Figure 8.1 says, among other things, that the heating controller subject domain consists of heaters, thermometers, heating tanks, batches, and recipes and that batches have an identifier batchID and are characterized by the amount of fluid in the batch. Each batch is related to one or two heating tanks and at any time, each heating tank is related to at most one batch. In this chapter, we look at the different elements of an ERD in detail. Section 8.1 introduces the concepts entity, entity type, attribute, and cardinality property. Sec-tion 8.2 introduces relationships as a way to express relative cardinality properties and defines the concept of association entity. Section 8.3 defines static and dynamic specialization of entity types. 8.1 Entities and Attributes An entity is a discrete identifiable part of the world; examples are tables, chairs, rocks, kings, presidents, businesses, committees, promises, contracts, traffic signs, and texts. Saying that entities are discrete means that we can collect them in a 77

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  Database Management System

  An Evolutionary Approach

  • Jagdish Chandra Patni, Hitesh Kumar Sharma, Ravi Tomar, Avita Katal(Authors)
  • 2022(Publication Date)
  • Chapman and Hall/CRC

    (Publisher)

  CHAPTER 4

  Entity-Relationship Model

  DOI: 10.1201/9780429282843-4

  The relationship between entity sets is depicted in an entity-relationship (ER) model. An entity set is a collection of related entities having a set of attributes, but in some cases, an entity may not have the attributes [1 ]. In relational database management systems, a relation will have the set of records and the set of attributes that are depicted by a logical structure called ER diagram.

  4.1 ER Diagram

  Student and college are two entity sets in the following ER diagram. studyIn is the relationship between these two entity sets and this is many-to-one as a college has many students, but a student cannot study in multiple colleges at a particular time. Stu_Id, Stu_Name, and Stu_Addr are the attributes form the student entity set, and col_Id and Col_name are the attributes for the college entity set (Figure 4.1 ).

  FIGURE 4.1

  University ER diagram.

  Here in the ER diagram, the following notations are used

  Rectangle: Entity sets.

  Ellipses: Attributes

  Diamonds: Relationship set

  Lines: Link between one entity set to the relationship and between the entity set to the attributes.

  Double Ellipses: Multivalued attributes

  Dashed Ellipses: Derived attributes

  Double Rectangles: Weak entity sets

  Double Lines: Total participation of an entity in a relationship set

  4.2 Components of an ER Diagram

  An ER diagram has three main components:

  1. Entity set
  2. Attributes
  3. Relationship

  4.2.1 Entity Set

  An entity is a data object or component, and an entity set is a collection of similar entities. In an ER diagram, an entity set is represented by a rectangle. We have two entity sets in the following ER diagram: Student and College, and these two entity sets have a many-to-one relationship because many students attend a single college. There are two forms of entity sets: weak and strong [2 ] (Figure 4.2

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  Information Structure Design for Databases

  A Practical Guide to Data Modelling

  • Andrew J. Mortimer(Author)
  • 2014(Publication Date)
  • Butterworth-Heinemann

    (Publisher)

  CHAPTER 4 ENTITY RELΑΉΟΝ8ΗΙΡ MODEL BASICS • What is an Entity Relationship Model? — El-ements of the ERM — Types of entity — Attributes — Relationships between entities — Degree and membership — Relationship rules — Steps in ER modelling What is an Entity Relationship Model? An Entity Relationship Model (ERM) is a logical (abstract) model of a set of entities and their relationships. Entity relationship modelling is used widely in industry as a part of the process of data design for databases. It is not normally used in isolation from other techniques and methods of data modelling, although it is taught and understood as a technique or method in its own right. An entity, as will be explained in more detail very shortíy, is something of interest about which we wish to store information, such as a car, a person, an invoice, a machine, a part or stock item. An Entity Relationship Model (or ERM for short) is a diagram composed of rectangular boxes, representing entities, connected by lines, representing the relationships between the entities. The diagram is a simple and clear way of representing the analyst's understanding of the data structures being studied. The ERM is, however, much more than just a documentation tool. Because of its graphical nature, it is used by data analysts to communicate and confirm 31 INFORMATION STRUCTURE DESIGN FOR DATABASES their understanding of the data structures with the users in the organisation. Although producing an ERM which can be transformed into a working and effective database is a long process, the ERM can be understood quite quickly. Within a few sessions, the users are able to explain and understand what the ERM is saying in terms of their own information environment. Look at the diagram in Figure 4-1. This diagram is an ERM. In the diagram you will see four rectangular boxes, each uniquely and clearly labelled with a singular noun.

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  Introduction to DBMS

  Designing and Implementing Databases from Scratch for Absolute Beginners

  • Dr. Hariram Chavan, Prof. Sana Shaikh(Authors)
  • 2022(Publication Date)
  • BPB Publications

    (Publisher)

  A database model defines the logical schema of the data. The model describes the relationships between different parts of the data. For a database design, many models have been in use. They are listed as follows:

  • Hierarchical model
  • Network model
  • ER model
  • Relational model

  A hierarchical database model is the oldest data model and uses a tree-like data structure to organize the data. The hierarchical model is useful to the data which has inherent hierarchies such as an organizational chart. It has a single parent and can have one or more children, that is, the parent:child has 1:N relationship. A network database model was formalized by the Database Task Group for flexible representation of objects and their relationships. It uses the graph data structure and can be visualized as a superset of the hierarchical model. In the late ’70's, hierarchical models and network models were used. But with the proliferation of ER model and relational model, it becomes almost absolute. So, let's discuss the ER model in-depth in this chapter.

  Entity-Relationship Model

  The Entity-Relationship (ER) model was introduced by Chen in 1976. It is a popular high-level conceptual data model. An ER model is a conceptual design of the database. In the ER model, the main components are entity, attribute, and relationship. For designing an ER Model, we will follow Chen’s notations.

  Let us describe the process for designing the ER models by illustrating all concepts of it through the college database example. Draw an ER diagram for the engineering college database. Problem statement for engineering college database

  Let us assume that the requirement gathering and analysis phase is already taken care of. And now, the database designer’s job is to design the conceptual model for this application. So, the following are the detailed description of the engineering college database:

  • Department

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  Database

  Principles Programming Performance

  • Patrick O'Neil(Author)
  • 2014(Publication Date)
  • Morgan Kaufmann

    (Publisher)

  The faithful representation of the table key is maintained by the database system. Also a number of other clauses of the Create Table statement serve a comparable purpose of limiting possible table content, and we refer to these as integrity constraints for a table. The interrelation-ships between columns in relational tables must be understood at a rea-sonably deep level in order to properly appreciate some constraints. Although not all concepts of logical design can be faithfully represented in the SQL of today, SQL is moving in the direction of modeling more and more such concepts. In any event, many of the ideas of logical design can be useful as an aid to systematic database definition even in the absence of direct system support. In the following sections, we first introduce a number of definitions of the E-R model. The process of normalization is introduced after some E-R intuition has been developed. ^ ^ ^ | Introduction to E-R Concepts The entity-relationship approach attempts to define a number of data clas-sification objects; the database designer is then expected to classify data items by intuitive recognition as belonging in some known classification. Three fundamental data classification objects introduced in this section are entities, attributes, and relationships. Entities, Attributes, and Simple E-R Diagrams We begin with a definition of the concept of entity. DEFINITION 5.1.1 Entity. An entity is a collection of distinguishable real-world objects with common properties. (A somewhat older nomenclature referred to an entity as an entity set, in the sense that it contains a collec-tion of real-world objects, but we will use the more modern terminology.)« For example, in a college registration database we might have the fol-lowing entities: S t u d e n t s , I n s t r u c t o r s , C l a s s _ r o o m s , C o u r s e s , C o u r s e _ s e c t i ons, Cl a s s _ p e r i ods, etc. (Entity names are capitalized,

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  Introduction to Environmental statistics

  • Akansha Singh, Esha Rami, Akansha Singh, Esha Rami(Authors)
  • 2023(Publication Date)
  • Delve Publishing

    (Publisher)

  Examples of database entities are tables and the characteristics associated with them. The ER graph is a diagram that illustrates the links between tables and the attributes of those tables. Its purpose is to show that the architecture of a database is sound. • Database entities can be of many different types, including people, places, things, and events. The utilization of a rectangle shape denotes the presence of an entity within the bounds of a connection outline. An excellent instance of this would be the use of entities, such as managers. One of two techniques can be used to characterize entities. Due to the fact that it possesses a distinguishing quality, this powerful entity may be used to identify each item in the database. In ER diagrams, it is often shown as a single rectangle in most cases. Because it is lacking in a significant basic quality, this entity must rely on the superficial characteristics of another powerful entity. On the ER diagram, a weak entity is often denoted by the presence of a double rectangle. • Attributes – when developing an Entity-Relationship Model, often known as an ERM, properties are what are utilized to represent the attributes of an entity. It is shown as either a circle or an oval in the ER diagram. It is abundantly clear that each oval shape represents quality and is connected to the rectangle with which it is affiliated in some kind. A wide range of an object’s properties can be considered in order to establish what kind of manager the item represents. The following is a statement made regarding an attribute in the ER model: A simple property is one that cannot have any of its atomic components broken down into smaller Introduction to Environmental Statistics 166 pieces in any additional way.

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  Functional Requirements for Authority Data

  A Conceptual Model

  • Glenn E. Patton(Author)
  • 2009(Publication Date)
  • De Gruyter Saur

    (Publisher)

  17 3. Entity-Relationship Diagram and Definitions 3.1 Entity-Relationship Methodology The methodology used to build this conceptual model is the same entity analysis technique used in the Functional Requirements for Bibliographic Records (FRBR) 3 . As described in section 2.3 of FRBR , the first step is the identification of the key objects that are of interest to users of information in a particular domain. Each of these key objects, or entities , then serves as the focal point for a cluster of data. A model developed using these techniques also depicts the relationships be-tween one type of entity and another type of entity. Once the high-level structure for the model has been laid out by identifying the entities and the relationships between those entities, the next step is to identify the primary characteristics or attributes of each entity. At a more detailed level, the model can also depict the relationships that may exist between instances of enti-ties. The entity-relationship model described in the following section has been used in this study to assess the relevance of each attribute and relationship to the set of user tasks defined later in this document. Entity versus Attribute: In designing any conceptual model, a key decision in-volves whether to make something an attribute or a separate entity. The outcome of this decision depends on the future use that is to be made of the attribute or en-tity. The developers of the FRBR model saw significant advantages in declaring persons and corporate bodies to be separate entities that could then be related to the other entities laid out in that model. Cataloguers have traditionally thought of controlling the names for persons and corporate bodies through authority data. Declaring persons and corporate bodies as entities enables much more flexibility in the controlled naming and eliminates redundancies that would occur if they were modeled as attributes.

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  Accounting Information Systems

  Connecting Careers, Systems, and Analytics

  • Arline A. Savage, Danielle Brannock, Alicja Foksinska(Authors)
  • 2022(Publication Date)
  • Wiley

    (Publisher)

  The type of ERD used is determined by its intended purpose: • CPA Conceptual ERDs and logical ERDs are used by business ana- lysts to model the plans for the database. • Physical ERDs are elaborate blueprints for the database designer who implements the structure by creating the database. To identify the connections between a pair of tables, we turn them into statements of relationships based on the business events that will happen: • A customer places an order. • An order is placed for a product. • An order is placed at a store. • A store sells products. 6-22 CHAPTER 6 Designing Systems and Databases Customers Orders Products Stores ILLUSTRATION 6.12 Lines connecting the four tables demonstrate how tables are related to one another in a conceptual ERD. The Logical ERD: Adding Details CPA Next, the conceptual ERD is enhanced by adding field names for each table. All fields in a table must describe the appropriate records. For example, if there is a Phone_Number field, the phone number for each record must belong to the individual named in that record. Illustration 6.13 shows a logical ERD used by the Julia’s Cookies Accounting department to finalize its portion of the data modeling. Consider what fields from other entities would be stored in a table. For example, the Orders table needs to include the customer who placed the order. For the logical ERD at Julia’s Cookies, Customer_Name is added as a field name to the Orders table. Also note that the Products table contains Selling_Price, while the Orders table also contains Price. These repetitions will be turned into a relationship by the core develop- ment team when the physical ERD is created. Currently, the field names are conversational terms. As the database design project progresses, they will be replaced with system field names. For example, Purchase_Price in the Products table may be called Price_1, and Selling_Price in the same table may be called Price_2.

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  Fundamentals of Database Management Systems

  • Mark L. Gillenson(Author)
  • 2012(Publication Date)
  • Wiley

    (Publisher)

  Thus, this chapter on the logical design of relational databases will proceed in three parts: first, the conversion of E-R diagrams into relational tables, then the data normalization technique, and finally the use of the data normalization technique to test the tables resulting from the E-R diagram conversions. CONVERTING E-R DIAGRAMS INTO RELATIONAL TABLES Introduction Converting entity-relationship diagrams to relational tables is surprisingly straight- forward, with just a few simple rules to follow. Basically, each entity will convert to a table, plus each many-to-many relationship or associative entity will convert to a table. The only other issue is that during the conversion, certain rules must be followed to ensure that foreign keys appear in their proper places in the tables. We will demonstrate these techniques by methodically converting the E-R diagrams of Chapter 2 into relational tables. Converting a Simple Entity Figure 7.1 repeats the simple entity box in Figure 2.1. Figure 7.2 shows a relational table that can store the data represented in the entity box. The table simply contains the attributes that were specified in the entity box. Notice that Salesperson Number is underlined to indicate that it is the unique identifier of the entity, and the primary key of the table. Clearly, the more interesting issues and rules come about when, as almost always happens, entities are involved in relationships with other entities. Converting E-R Diagrams into Relational Tables 159 CONCEPTS IN ACTION 7-A E COLAB Ecolab is a $3-billion-plus developer and marketer of cleaning, sanitizing, pest elimination, and industrial maintenance and repair products and services that was founded in 1923. Its customers include restaurants, hotels, hospitals, food and beverage plants, laundries, schools, and other retail and commercial facilities.

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