1 Data Organization & ER Model Chapter 2 Instructor: Dr. Cynthia Xin Zhang

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Data Organization & ER Model

Chapter 2

Instructor: Dr. Cynthia Xin Zhang

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Data design When we build a new database …

– Relational database design in DBMS When we transform a existing database

…– Data manipulation (merge, clean, format,

etc.)– Information Retrieval

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What Is a DBMS?

A very large, integrated collection of data.

Models real-world enterprise.– Entities (e.g., students, courses)– Relationships (e.g., Madonna is taking CSC

132) A Database Management System

(DBMS) is a software package designed to maintain and utilize databases.

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Why Use a DBMS?

Data independence and efficient access. Reduced application development time. Data integrity and security. Uniform data administration. Concurrent access, recovery from

crashes.

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Why study Database implementation?

Good job market. – Web Developer– SQL Programmer (development DBA)– Database Administrator (production

DBA)– Data Analyst

Graduate school– DBMS encompasses most of CS

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Data Models A data model is a collection of concepts for

describing data. A schema is a description of a particular

collection of data, using the a given data model.

The relational model of data is the most widely used model today.– Main concept: relation, basically a table with rows

and columns.– Every relation has a schema, which describes the

columns, or fields.

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Levels of Abstraction

Many views, single conceptual (logical) schema and physical schema.– Views describe how

users see the data.

– Conceptual schema defines logical structure

– Physical schema describes the files and indexes used.DDL (CREAT, ALTER, DROP); DML (SELECT, INTERT, UPDATE);

DCL (GRANT, REVOKE); TCL (COMMIT, SAVEPOINT, ROLLBACK).

Physical Schema

Conceptual Schema

View 1 View 2 View 3

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Example: University Database

Conceptual schema: – Students (sid: string, name: string, login: string, age:

integer, gpa:real)– Courses (cid: string, cname:string, credits:integer) – Enrolled (sid:string, cid:string, grade:string)

Physical schema:– Relations stored as unordered files. – Index on first column of Students.

External Schema (View): – Course_info(cid:string,enrollment:integer)

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Data Independence

Applications insulated from how data is structured and stored.

Logical data independence: Protection from changes in logical structure of data.

Physical data independence: Protection from changes in physical structure of data.

One of the most important benefits of using a DBMS!

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Object Oriented Programming

Entity Class Property Attribute Cardinality Multiplicity

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Inside a Database

• Tables• Relationship among tables• Operations (queries)

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Overview of db design Requirement analysis

– Data to be stored– Applications to be built– Operations (most frequent) subject to performance requirement

Conceptual db design– Description of the data (including constraints)– By high level model such as ER

Logical db design– Choose DBMS to implement– Convert conceptual db design into database schema

Beyond ER design Schema refinement (normalization) Physical db design

– Analyze the workload– Indexing

Security design

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Conceptual design

Issues to consider: (ER Model is used at this stage.) – What are the entities and relationships in the enterprise?– What information about these entities and relationships

should we store in the database (i.e., attributes)?– What are the integrity constraints or business rules

that hold? Solution:

– A database `schema’ in the ER Model can be represented pictorially (ER diagrams).

– Can map an ER diagram into a relational schema.

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University database

Entities: Students, professors, courses, textbook, classroom, transcript, emails

Attributes: terms, ssn , birthdate, cell phone, account balance, parents, age, gender, gpa, major, classification, grade, name.

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ER Model Basics

Entity: Real-world object distinguishable from other objects. An entity is described (in DB) using a set of attributes.

Entity Set: A collection of similar entities. E.g., all employees. – All entities in an entity set have the same set of

attributes. – Each entity set has a key.– Each attribute has a domain.

Employees

ssnname

lot

What’s should be entities? Attributes?

What’s the key? How many keys one object can have?

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A Universal Data Model for All?

Companies

Employees Departments

Name Business

Name Locationssn Budget

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Key

A key is a minimal set of attributes whose values uniquely identify an entity in the set.

Candidate key. Primary key.

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Entity, Entity Set, Attribute, and Schema

ID or SSN Name UserID Age GPA999-38-4431 John Smith jsmith 21 3.68999-28-3341Miki Jordan mjordan 28 3.45

331-43-4567 David Kim dkim 25 4.00

535-34-5678 Paul Lee plee 26 3.89

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Relationship: Association among 2 or more entities. E.g., Sam works in the Accounting Department.

Relationship Set: Collection of similar relationships. E.g., Many individuals works in many different departments.

ER Model Basics (Contd.)

lot

dname

budgetdid

sincename

Works_In DepartmentsEmployees

ssn

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Entity vs. Entity Set

Example: Student

John Smith (999-21-3415, jsmith@, John Smith, 18, 3.5)

Students in CSC439

999-21-3415, jsmith@, John Smith, 18, 3.5999-31-2356, jzhang@, Jie Zhang, 20, 3.0999-32-1234, ajain@, Anil Jain, 21, 3.8

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Example of Keys


Primary key Candidate key

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Relationship vs. Relationship Set

John Smith

ITCS3160

(999-21-3415, jsmith@, John Smith, 18, 3.5)

(3160, ITCS, DBMS, J. Fan, 3, Kenn. 236)

Relationship

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3160, ITCS, DBMS, J. Fan, 3, Kenn. 2366157, ITCS, Visual DB, J. Fan, 3, Kenn. 236

Relationship set(“Enrolled in”)

Students

Courses

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Students

Name Login

Id

Age

GPACourses

Id Name Credit

Enrolled_In

Grade


Room

Descriptive attribute

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Example 1

Build an ER-diagram for a university database:– Students

Have an Id, Name, Login, Age, GPA– Courses

Have an Id, Name, Credit Hours– Students enroll in courses

Receive a grade

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Example 2

Build an ER Diagram for a hospital database:– Patients

Name, Address, Phone #, Age– Drugs

Name, Manufacturer , Expiration Date– Patients are prescribed of drugs

Dosage, # Days

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Constraints

Key constraints Participation constraints

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Many-to-Many1-to-1 1-to Many Many-to-1

Potential Relationship Types

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Mary studies in the CS Dept. Tom studies in the CS Dept. Jack studies in the CS Dept. … The CS Dept has lots of students. No student in the CS Dept works in other else Dept

at the same time.

Students CS DeptIN? ?

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Mary is taking the ITCS3160,ITCS2212. Tom is taking the ITCS3160, ITCS2214. Jack is taking the ITCS1102, ITCS2214. … 61 students are taking ITCS3160. 120 students are taking ITCS2214.

Students Coursestake? ?

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lot

dname

budgetdid

sincename


ssn

Key Constraints

Consider Works_In: An employee can work in many departments; A dept can have many employees.

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lot

dname

budgetdid

sincename


ssn

Key Constraints

Consider Works_In: An employee can work in at most one department; A dept can have many employees.

Why "work-in" is not "key constraint"??

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Key Constraints

In contrast, each dept has at most one manager, according to the key constraint on Manages.

dname

budgetdid

since

lot

name

ssn

ManagesEmployees Departments

Key Constraint

(time constraint)

At most one!!!

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Participation Constraints

Does every department have a manager?– If so, this is a participation constraint: the

participation of Departments in Manages is said to be total (vs. partial).

Every did value in Departments table must appear in a row of the Manages table (with a non-null ssn value!)lot

name dnamebudgetdid

sincename dname

budgetdid

since

Manages

since

DepartmentsEmployees

ssn

Works_In

Total w/keyconstraint

Partial

TotalTotal

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lot

name dnamebudgetdid

sincename dname

budgetdid

since

Manages

since


ssn

Works_In

Total & keyconstraint

Total

TotalTotal

What are the policies behind this ER model?

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lot

name dnamebudgetdid

sincename dname

budgetdid

since

Manages

since


ssn

Works_In

Total w/keyconstraint

Partial

TotalTotal

dname

budgetdid

since

lot

name

ssn

ManagesEmployees Departments

Works_InAny Difference?

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Weak Entities vs. Owner Entities

A weak entity can be identified uniquely only by considering the primary key of another (owner) entity.– Owner entity set and weak entity set must

participate in a one-to-many relationship set (1 owner, many weak entities).

– Weak entity set must have total participation in this identifying relationship set.

lot

name

agepname

DependentsEmployees

ssn

Policy

cost

Weak EntityIdentifying Relationship

Primary Keyfor weak entity

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dnamebudgetdid

name

Departments

ssn lot

Employees Works_In3

Durationfrom to

Ternary Relationship

lot

dname

budgetdid

sincename


ssn

Why?

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ISA (`is a’) Hierarchies

Contract_Emps

namessn

Employees

lot

hourly_wages

ISA

Hourly_Emps

contractid

hours_workedAs in C++, or other PLs, attributes are inherited.If we declare A ISA B, every A entity is also considered to be a B entity. Overlap constraints: Can Joe be an Hourly_Emps as well

as a Contract_Emps entity? (Allowed/disallowed) Covering constraints: Does every Employees entity also

have to be an Hourly_Emps or a Contract_Emps entity? (Yes/no)

Reasons for using ISA: – To add descriptive attributes specific to a subclass.

– To identify entitities that participate in a relationship.

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Aggregation Used when we have

to model a relationship involving (entitity sets and) a relationship set.– Aggregation allows

us to treat a relationship set as an entity set for purposes of participation in (other) relationships.

– Monitors mapped to table like any other relationship set.

budgetdidpid

started_on

pbudgetdname

until

DepartmentsProjects Sponsors

Employees

Monitors

lotname

ssn

Aggregation

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Real Database Design

Build an ER Diagram for the following information:– Walmart Stores

Store Id, Address, Phone #

– Products Product Id, Description, Price

– Manufacturers Name, Address, Phone #

– Walmart Stores carry products Amount in store

– Manufacturers make products Amount in factory/warehouses

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Conceptual Design Using the ER Model

Design choices:

– Should a concept be modeled as an entity or an attribute?

– Should a concept be modeled as an entity or a relationship?

– Identifying relationships: Binary or Ternary? Aggregation?

Always follow the requirements.

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Entity vs. Attribute

Should address be an attribute of Employees or an entity (connected to Employees by a relationship)?

Depends upon the use we want to make of address information, and the semantics of the data:

If we have several addresses per employee, address must be an entity (since attributes cannot be set-valued).

If the structure (city, street, etc.) is important, e.g., we want to retrieve employees in a given city, address must be modeled as an entity (since attribute values are atomic).

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Entity vs. Attribute (Contd.)

Works_In2 does not allow an employee to work in a department for two or more periods.

Similar to the problem of wanting to record several addresses for an employee: we want to record several values of the descriptive attributes for each instance of this relationship.

name

Employees

ssn lot

Works_In2

from todname

budgetdid

Departments

dnamebudgetdid

name

Departments

ssn lot

Employees Works_In3

Durationfrom to

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Entity vs. Relationship First ER diagram OK if

a manager gets a separate discretionary budget for each dept.– Redundancy of

dbudget, which is stored for each dept managed by the manager.

– Misleading: suggests dbudget tied to managed dept.

What if a manager gets a discretionary budget that covers all managed depts?

Manages2

name dnamebudgetdid

Employees Departments

ssn lot

dbudgetsince

Employees

since

name dnamebudgetdid

Departments

ssn lot

Manager

Manages3

dbudget

IsA

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Binary vs. Ternary Relationships

Requirements: A policy not to be owned by more than one

employee. Every policy must be owned by some employee. Dependents is a weak entity set. Each identified

by pname +policyid

agepname

DependentsCovers

name

Employees

ssn lot

Policies

policyid cost

Bad design

*

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Binary vs. Ternary Relationships

If each policy is owned by just 1 employee:– Key

constraint on Policies would mean policy can only cover 1 dependent!

agepname

DependentsCovers

name

Employees

ssn lot

Policies

policyid cost

Bad design

Beneficiary

agepname

Dependents

policyid cost

Policies

Purchaser

name

Employees

ssn lot

Better design

*

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Binary vs. Ternary Relationships (Contd.)

Previous example illustrated a case when binary relationships were better than one ternary relationship.

An example in the other direction: a ternary relation Teaches relates entity set Students, Professors and Courses, and has descriptive attributes term and year. No combination of binary relationships is an adequate substitute:– P teaches S, S takes C, P teaches C, do not necessarily

imply that P indeed teaches S of C!– How do we record term and year?

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Students

Professors Courses

Teaches

term year

Professors Courses Students

Teaches Takes

term year term year

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Summary of Conceptual Design

Conceptual design follows requirements analysis, – Yields a high-level description of data to be stored

ER model popular for conceptual design– Constructs are expressive, close to the way people

think about their applications. Basic constructs: entities, relationships, and

attributes (of entities and relationships). Some additional constructs: weak entities,

ISA hierarchies, and aggregation. Note: There are many variations on ER model.

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Summary of ER (Contd.)

Several kinds of integrity constraints can be expressed in the ER model: key constraints, participation constraints, and overlap/covering constraints for ISA hierarchies. Some foreign key constraints are also implicit in the definition of a relationship set.– Some constraints (notably, functional dependencies)

cannot be expressed in the ER model.– Constraints play an important role in determining

the best database design for an enterprise.

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Summary of ER (Contd.)

ER design is subjective. There are often many ways to model a given scenario! Analyzing alternatives can be tricky, especially for a large enterprise. Common choices include:– Entity vs. attribute, entity vs. relationship, binary or

n-ary relationship, whether or not to use ISA hierarchies, and whether or not to use aggregation.

Ensuring good database design: resulting relational schema should be analyzed and refined further. FD information and normalization techniques are especially useful.

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Example 1 Answer

Students

Name Login

Id

Age

GPACourses

Id Name Credit

Enrolled_In

Grade

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Example 2 Answer

Patients

Name Addr Phone

AgeDrugs

Name Manuf Exp

Prescribed

Dosage #days

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1 Data Organization & ER Model Chapter 2 Instructor: Dr. Cynthia Xin Zhang