03. Design.pptx, it is a very helpful material.

Chapter 9 Copyright © 2017 Pearson Education, Ltd. 9-1
Designing Databases
Modern Systems Analysis
and Design
Eighth Edition, Global Edition
Joseph S. Valacich
Joey F. George

Learning Objectives
 Describe the database design process, its outcomes,
and the relational database model.
 Describe normalization and the rules for second and
third normal form.
 Transform an entity-relationship (E-R) diagram into an
equivalent set of well-structured (normalized) relations.
 Merge normalized relations from separate user views
into a consolidated set of well-structured relations.

Learning Objectives (Cont.)
 Describe physical database design concepts:
 Choose storage formats for fields in database tables.
 Translate well-structured relations into efficient
database tables.
 Explain when to use different types of file
organizations to store computer files.
 Describe the purpose of indexes and the important
considerations in selecting attributes to be indexed.

Introduction
FIGURE 9-1
Systems development
life cycle with design
phase highlighted

Database Design
 File and database design occurs in two steps.
1. Develop a logical database model, which describes
data using notation that corresponds to a data
organization used by a database management
system.
 Relational database model
2. Prescribe the technical specifications for computer
files and databases in which to store the data.
 Physical database design provides specifications
 Logical and physical database design in parallel
with other system design steps

The Process of Database Design
FIGURE 9-2
Relationship between data modeling and the systems development life cycle

The Process of Database
Design (Cont.)
 Four key steps in logical database modeling
and design:
1. Develop a logical data model for each known user interface for
the application using normalization principles.
2. Combine normalized data requirements from all user interfaces
into one consolidated logical database model (view integration).
3. Translate the conceptual E-R data model for the application into
normalized data requirements.
4. Compare the consolidated logical database design with the
translated E-R model and produce one final logical database
model for the application.

Physical Database Design
 Key physical database design decisions include:
 Choosing a storage format for each attribute from the
logical database model.
 Grouping attributes from the logical database model
into physical records.
 Arranging related records in secondary memory
(hard disks and magnetic tapes) so that records can
be stored, retrieved and updated rapidly.
 Selecting media and structures for storing data to
make access more efficient.

Relational Database Model
 Relational database model: data
represented as a set of related tables or
relations
 Relation: a named, two-dimensional
table of data; each relation consists of a
set of named columns and an arbitrary
number of unnamed rows

FIGURE 9-3 (d)
Conceptual data
model and
transformed relations

Relational Database Model (Cont.)
 Relations have several properties that
distinguish them from nonrelational tables:
 Entries in cells are simple.
 Entries in columns are from the same set of
values.
 Each row is unique.
 The sequence of columns can be interchanged
without changing the meaning or use of the
relation.
 The rows may be interchanged or stored in any
sequence.

Well-Structured Relation and
Primary Keys
 Well-Structured Relation (or table)
 A relation that contains a minimum amount of redundancy
 Allows users to insert, modify, and delete the rows without
errors or inconsistencies
 Primary Key
 An attribute whose value is unique across all occurrences of
a relation
 All relations have a primary key.
 This is how rows are ensured to be unique.
 A primary key may involve a single attribute or be composed
of multiple attributes.

Well-Structured Relation and
Foreign Keys
 Foreign Key: an attribute that appears as a nonprimary key
attribute (or part of a primary key) in one relation and as a
primary key attribute in another relation

Normalization and Rules of
Normalization
 Normalization: the process of converting
complex data structures into simple, stable
data structures
 The result of normalization is that every
nonprimary key attribute depends upon the
whole primary key.

Normalization and Rules of
Normalization (Cont.)
 First Normal Form (1NF)
 Unique rows, no multivalued attributes
 All relations are in 1NF
 Second Normal Form (2NF)
 Each nonprimary key attribute is identified by the whole
primary key (called full functional dependency)
 Third Normal Form (3NF)
 Nonprimary key attributes do not depend on each other (i.e.
no transitive dependencies)
15

Functional Dependencies and
Primary Keys
 Functional Dependency: a particular
relationship between two attributes
For a given relation, attribute B is functionally
dependent on attribute A if, for every valid
value of A, that value of A uniquely
determines the value of B.
The functional dependence of B on A is
represented by A→B.

Functional Dependencies and
Primary Keys (Cont.)
 Functional dependency is not a mathematical
dependency.
 Instances (or sample data) in a relation do
not prove the existence of a functional
dependency.
 Knowledge of problem domain is most
reliable method for identifying functional
dependency.

Emp_ID  Name,Dept,Salary (partial dependency)
Emp_ID,Course  Date_Completed (complete
depencency)

Binary 1:N and 1:1Relationships
(Cont.)
 Binary or Unary 1:1 Relationship is
represented by any of the following
choices:
Add the primary key of A as a foreign key of B.
Add the primary key of B as a foreign key of A.
Both of the above

Binary and Higher-Degree M:N
Relationships
 Create another relation and include
primary keys of all relations as primary
key of new relation

Transforming E-R Diagrams into
Relations
 It is useful to transform the conceptual
data model into a set of normalized
relations.
 Steps
Represent entities.
Represent relationships.
Normalize the relations.
Merge the relations.

Representing Entities
 Each regular entity is transformed into a
relation.
 The identifier of the entity type becomes
the primary key of the corresponding
relation.

Representing Entities
 The primary key must satisfy the
following two conditions.
 The value of the key must uniquely identify
every row in the relation.
 The key should be nonredundant.
 The entity type label is translated into a
relation name.

 The procedure for representing relationships
depends on both the degree of the
relationship—unary, binary, ternary—and the
cardinalities of the relationship.
 Binary 1:N Relationship is represented by
adding the primary key attribute (or attributes)
of the entity on the one side of the
relationship as a foreign key in the relation
that is on the many side of the relationship.

(Cont.)
 Binary or Unary 1:1 Relationship is
represented by any of the following
choices:
Add the primary key of A as a foreign key of B.
Add the primary key of B as a foreign key of A.
Both of the above

Physical File and Database Design
 The following information is required:
 Normalized relations, including volume estimates
 Definitions of each attribute
 Descriptions of where and when data are used,
entered, retrieved, deleted, and updated
(including frequencies)
 Expectations or requirements for response time
and data integrity
 Descriptions of the technologies used for
implementing the files and database

Designing Fields
 Field: the smallest unit of named
application data recognized by system
software
Attributes from relations will be represented as
fields
 Data Type: a coding scheme recognized
by system software for representing
organizational data

Choosing Data Types
 Selecting a data type balances four
objectives:
Minimize storage space.
Represent all possible values of the field.
Improve data integrity of the field.
Support all data manipulations desired on the
field.

File Organizations
 File organization: a technique for
physically arranging the records of a file
 Physical file: a named set of table rows
stored in a contiguous section of
secondary memory

File Organizations (Cont.)
 Three common file organizations:
1. Sequential: rows are stored in sequence
according to a primary key value
2. Indexed: rows can be stored sequentially or
nonsequentially; an index allows quick access
to rows
3. Hashed file organization: rows usually stored
nonsequentially; the address for each row is
determined using an algorithm

Figure 9-20 Comparison of file organizations
(c) Hashed
(a) Sequential
(b) Indexed

Summary
 In this chapter you learned how to:
 Describe the database design process, its outcomes,
and the relational database model.
 Describe normalization and the rules for second and
third normal form.
 Transform an entity-relationship (E-R) diagram into
an equivalent set of well-structured (normalized)
relations.
 Merge normalized relations from separate user
views into a consolidated set of well-structured
relations.

Summary (Cont.)
 Describe physical database design concepts:
 Choose storage formats for fields in database tables.
 Translate well-structured relations into efficient
database tables.
 Explain when to use different types of file
organizations to store computer files.
 Describe the purpose of indexes and the important
considerations in selecting attributes to be indexed.

03. Design.pptx, it is a very helpful material.

More Related Content

Similar to 03. Design.pptx, it is a very helpful material. (20)

Recently uploaded (20)

03. Design.pptx, it is a very helpful material.

Editor's Notes