Entity-Relationship (ER) Model Quiz
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Data Modeling Using the Entity-Relationship (ER) Model 21 October 2019 Lecture 4 Dr. Ahmed Alnasheri Dr. Ahmed Alnasheri Objectives  Understand concepts of data modeling and its purpose  Understanding the database design process  Introduce the major components of ER diagram  Learn how relationships between entities are defined  Learn how ERD components affect database design and implementation  Learn how to interpret the modeling symbols Dr. Ahmed Alnasheri 2 Data Model  Model: an abstraction of a real-world object or event – Useful in understanding complexities of the realworld environment  Data model – A diagram that displays a set of tables and the relationships between them – Next Slide: “Restaurant” Access data model using Entity Relationship Diagram (ERD) Dr. Ahmed Alnasheri 3 Access Data Model using ERD Dr. Ahmed Alnasheri 4 What is ER Model. And Why.  ER is modeling tool used to depict graphically a database design before it is actually implemented.  ER Model is used.

Match the following relational model terminology with their definitions:

Relation = A table with columns and rows Attribute = A named column of a relation Cardinality = The number of tuples in a relation Domain = The set of allowable values for an attribute

Match the following characteristics of a relation with their definitions:

Each cell of relation contains exactly one atomic value = Each entry in the table holds a single value Values of an attribute are all from the same domain = All values in a column belong to the same set of allowable values Each tuple is distinct; there are no duplicate tuples = No two rows are identical Order of attributes has no significance = The sequence of columns does not affect the data

Match the following relational database concepts with their descriptions:

<p>Relation schema = Named relation defined by a set of attribute and domain name pairs Relational database schema = Set of relation schemas, each with a distinct name Database Relations = Collection of normalized relations with distinct relation names Relational Keys = Keys that uniquely identify tuples in a relation</p> Signup and view all the answers

Match the following relational database rules with their definitions:

<p>Relation name is distinct from all other relation names in relational schema = Each table has a unique name within the database Each attribute has a distinct name = Every column is uniquely labeled within a table Order of tuples has no significance, theoretically = The sequence of rows does not affect the data Relational Database = A collection of normalized relations with distinct relation names</p> Signup and view all the answers

Match the following relational model terminology with their constraints:

<p>Relation = Each tuple is distinct; there are no duplicate tuples Attribute = Values of an attribute are all from the same domain Cardinality = The number of tuples in a relation Domain = The set of allowable values for an attribute</p> Signup and view all the answers

Study Notes

Data Modeling and ER Model

  • Data modeling is an abstraction of a real-world object or event, useful in understanding complexities of the real-world environment.
  • A data model is a diagram that displays a set of tables and the relationships between them.

ER Model

  • The ER model is a modeling tool used to depict graphically a database design before it is actually implemented.
  • The ER model is used to define the relationships between entities.

Objectives of Data Modeling

  • Understand the concepts of data modeling and its purpose.
  • Understand the database design process.
  • Introduce the major components of the ER diagram.
  • Learn how relationships between entities are defined.
  • Learn how ERD components affect database design and implementation.
  • Learn how to interpret the modeling symbols.

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Test your knowledge of data modeling using the Entity-Relationship (ER) model with this quiz. Assess your understanding of database design concepts, ER diagram components, entity relationships, and their impact on database design and implementation.

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