SI 654 Database Application Design Winter 2003 Dragomir R. Radev 1 © 2002 by Prentice Hall Database Processing Eighth Edition The EntityRelationship Model 2 Chapter 3 David M. Kroenke © 2002 by Prentice Hall Data Modeling • Process of creating a logical representation of the structure of the database • The most important task in database development 3 © 2002 by Prentice Hall Entity-Relationship Model (E-R Model) • An Entity-Relationship Model (E-R Model) consists of: – Entities – Attributes – Identifiers – Relationships 4 © 2002 by Prentice Hall An Entity • An entity is an object that can be identified in the users’ work environment & that users want to track. • Entities of a given type are grouped into entity classes. 5 © 2002 by Prentice Hall An Entity Example 6 © 2002 by Prentice Hall Attributes • An attribute describes a characteristic of an entity • For example – An entity: Employee – Has attributes: • EmployeeName • Extension • DateOfHire 7 © 2002 by Prentice Hall Identifier • An identifier uniquely identifies a row in a table. • For an Employee, the SocialSecurityNumber may serve as the Indentifier. 8 © 2002 by Prentice Hall Relationships • A relationship describes how one or more entities are related with each other. 9 © 2002 by Prentice Hall Relationship Cardinality • Entity-Instance Participation in relationships is shown by – maximum cardinality – minimum cardinality 10 © 2002 by Prentice Hall Maximum Cardinality • The maximum cardinality indicates/depicts the maximum number of instances involved in a relationship. • Alternatives include – 1:1 (one-to-one) – 1:N (one-to-many) – N:M (many-to-many) 11 © 2002 by Prentice Hall Relationship Examples Showing Maximum Cardinality Alternatives 12 © 2002 by Prentice Hall Minimum Cardinality • The minimum cardinality indicates/depicts whether participation in the relationship is mandatory or optional. • Alternatives include – 0 (optional) – 1 (mandatory) 13 © 2002 by Prentice Hall A Relationship Example Showing Minimum and Maximum Cardinality 14 © 2002 by Prentice Hall A Recursive Relationship • A recursive relationship is when an entity has a relationship with itself. 15 © 2002 by Prentice Hall Entity-Relationship Diagram (E-R Diagram) • An entity-relationship diagram (E-R Diagram) is a graphical representation of the E-R model using a set of ‘somewhat’ standardized conventions 16 © 2002 by Prentice Hall An Entity-Relationship Diagram (E-R Diagram) Example 17 © 2002 by Prentice Hall Weak Entity • A weak entity is an entity whose instance survival depends (logically) on an associated instance in another entity 18 © 2002 by Prentice Hall Subtype Entities • Some entities may have many common attributes and a few unique attributes. • The common attributes may be grouped together in a supertype entity and the unique attributes may be grouped together in a subtype entity. 19 © 2002 by Prentice Hall CLIENT with Subtype Entities 20 © 2002 by Prentice Hall E-R Diagram Computer Assisted Software Engineering (CASE) Tools • Several Computer Assisted Software Engineering (CASE) Tools exist to help create E-R Diagrams and the resulting physical database elements. Products include: – IEW – IEF – DEFT – ER-WIN – Visio 21 © 2002 by Prentice Hall E-R Diagram Example: Jefferson Dance Club 22 © 2002 by Prentice Hall E-R Diagram Example: San Juan Charters 23 © 2002 by Prentice Hall Database Processing Eighth Edition The Relational Model and Normalization 24 Chapter 5 David M. Kroenke © 2002 by Prentice Hall The Relational Model • Broad, flexible model • Basis for almost all DBMS products • E.F. Codd defined well-structured “normal forms” of relations, “normalization” 25 © 2002 by Prentice Hall Components of the Relational Model • Relation – A two-dimensional table consisting of rows and columns • Tuples – The rows (or records) in a relation • Attributes – The columns (or fields) in a relation 26 © 2002 by Prentice Hall Terminology 27 © 2002 by Prentice Hall Functional Dependency • Functional dependencies are the relationships among the attributes within a relation. • If attribute A functional depends on attribute B, then for every instance of B you will know the respective value of A. 28 © 2002 by Prentice Hall Functional Dependency Notation • Major is functionally dependent on SID • SID Major • Grade is functionally dependent on the combination of SID and ClassID • (SID, ClassID) Grade 29 © 2002 by Prentice Hall Functional Dependency – an Example • EmployeeNumber Name • EmployeeNumber Age • EmployeeNumber Sex 30 © 2002 by Prentice Hall A Key • A key is a group of one or more attributes that uniquely identifies a tuple 31 © 2002 by Prentice Hall A Combination Key • Sometimes more than one attribute will be required to uniquely identify a tuple. • If a key consists of more than one attribute, it is called a combination (or composite) key. 32 © 2002 by Prentice Hall Example of a Combination Key 33 © 2002 by Prentice Hall Normalization • Normalization is a process of evaluating and converting a relation to reduce modification anomalies • Essentially, normalization detects and eliminates data redundancy 34 © 2002 by Prentice Hall An Anomaly • An anomaly is an undesirable consequence of a data modification. 35 © 2002 by Prentice Hall Normal Forms • Normal forms are state-classes of relations which identify the level of anomaly-avoidance 36 © 2002 by Prentice Hall Normal Forms Levels • • • • • • • 37 1NF –First Normal Form 2NF –Second Normal Form 3NF –Third Normal Form BCNF –Boyce-Codd Normal Form 4NF –Fourth Normal Form 5NF –Fifth Normal Form DK/NF –Domain/Key Normal Form © 2002 by Prentice Hall First Normal Form (1NF) • To be in First Normal Form (1NF) a relation must have only single-valued attributes -- neither repeating groups nor arrays are permitted 38 © 2002 by Prentice Hall Second Normal Form (2NF) • To be in Second Normal Form (2NF) the relation must be in 1NF and each nonkey attribute must be dependent on the whole key (not a subset of the key) 39 © 2002 by Prentice Hall Third Normal Form (3NF) • To be in Third Normal Form (3NF) the relation must be in 2NF and no transitive dependencies may exist within the relation. • A transitive dependency is when an attribute is indirectly functionally dependent on the key (that is, the dependency is through another nonkey attribute) 40 © 2002 by Prentice Hall Violation of 3NF 41 © 2002 by Prentice Hall Boyce-Codd Normal Form (BCNF) • To be in Boyce-Codd Normal Form (BCNF) the relation must be in 3NF and every determinant must be a candidate key. 42 © 2002 by Prentice Hall Fourth Normal Form (4NF) • To be in Fourth Normal Form (4NF) the relation must be in BCNF and the relation may not contain multi-valued dependencies. 43 © 2002 by Prentice Hall Fifth Normal Form (5NF) • The Fifth Normal Form concerns dependencies that are obscure and beyond the scope of this text. 44 © 2002 by Prentice Hall Domain/Key Normal Form (DK/NF) • To be in Domain/Key Normal Form (DK/NF) every constraint on the relation must be a logical consequence of the definition of keys and domains. 45 © 2002 by Prentice Hall DK/NF Terminology • Constraint – A rule governing static values of attributes • Key – A unique identifier of a tuple • Domain – A description of an attribute’s allowable values 46 © 2002 by Prentice Hall DK/NF Example Domain/Key Definition of Example Above 47 © 2002 by Prentice Hall DK/NF Example 48 © 2002 by Prentice Hall DK/NF Example 49 © 2002 by Prentice Hall Summary of Normal Forms 50 © 2002 by Prentice Hall Synthesis of Relations A B and B A A B but B not A A not B and B not A 51 one-to-one many-to-one many-to-many © 2002 by Prentice Hall Summary of Attribute Relationships 52 © 2002 by Prentice Hall Optimization • De-Normalization (a.k.a., Controlled Redundancy) 53 © 2002 by Prentice Hall
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