Chapter 4
Relational
Databases
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Learning Objectives
• Explain the importance and advantages of databases.
• Describe the difference between database systems and file-based
legacy systems.
• Explain the difference between logical and physical views of a
database.
• Explain fundamental concepts of database systems such as DBMS,
schemas, the data dictionary, and DBMS languages.
• Describe what a relational database is and how it organizes data.
• Create a set of well-structured tables to store data in a relational
database.
• Perform simple queries using the Microsoft Access database.
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Database A set of interrelated, centrally
coordinated data files that are
stored with as little data
redundancy as possible.
A database consolidates records previously stored in
separate files into a common pool and serves a variety of
users and data processing applications.
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Field
Attributes about an entity
Data
Hierarc
hy.
Record
Related group of fields
File
Related group of records
Database
Related group of files
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File-Oriented Systems versus Database
Systems
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Using Data Warehouses for Business Intelligence
A data warehouse is one or more very large databases containing both detailed and
summarized data for a number of years that is used for analysis rather than transaction
processing
OLAP
DATA
MINING
Business Intelligence ===> using Data Warehouse
for strategic decision making
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Database Terminology
Database
Management
System (DBMS)
Interface between software applications
and the data in files.
Database
Administrator
(DBA)
Person responsible for maintaining the
database
Data Dictionary
Information
about the
structure of the
database
Field names,
descriptions, uses
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Advantages of Database Systems
Data Integration
Data Sharing
Minimizing Data Redundancy and Data
Inconsistency
Data Independence
Cross-Functional Analysis
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Logical vs. Physical View of Data
Physical View
• The way data are physically arranged and
stored in the computer system.
• Depends on explicitly knowing:
• How is the data actually arranged in a file
• Where is the data stored on the computer
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Logical View
• How people conceptually organize, view, and
understand the relationships among data items.
• Unnecessary to explicitly know how and where
data is stored.
• For example, a sales manager views all customer
information as being stored in a table.
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A schema is a description of the data elements in a database, the
relationships among them, and the logical model used to organize
and describe the data.
The
the organization-wide view of the entire
conceptual-level database, lists all data elements and the
relationships among them.
schema
The
external-level
schema
an individual user’s view of
portions of a database
The
internal-level
schema
a low-level view of the database,
describes how the data are stored and
accessed, including record layouts,
definitions, addresses, and indexes. 4-13
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Data Dictionary
data dictionary contains information about the structure of the
database.
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DBMS Languages
Data Definition
Language (DDL)
Builds the data dictionary
Creates the database
Describes the subschema
Specifies record or field security constraints
Data Manipulation
Language (DML)
Changes the content in the database
Updates, insertions, and deletions
Data Query
Language (DQL)
Enables the retrieval, sorting, and display of data
from the database
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Relational Database
Relational data model representsconceptual- and
external-level schemas as if data are stored in
two-dimensional tables
Table
• Each row called a tuple, contains data about a
specific item in a database table. This is
equivalent to a record
• Each column contains data about an attribute of of
an entity. This is equivalent to a field
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Row (Record)
A Relational Table
Each row contains multiple attributes
describing an instance of the entity. In
this case, inventory.
Column (Field)
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Type of Attributes – Relational Database System
Primary
Key
the database attribute, or combination of
attributes, that uniquely identifies a specific
row in a table.
Foreign
Key
an attribute in a table that is also a primary
key in another table and is used to link the
two tables.
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Database Design Errors
Update
Anomaly
Changes to existing data are not correctly recorded.
Due to multiple records with the same data attributes
Insert
Anomaly
there is no way to store information about prospective customers
until they make a purchase.
Unable to add a record to the database.
Delete
Anomaly
occurs when deleting a row has unintended
consequences.
removing a record also removes unintended data from
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the database.
Design Requirements for Relational Database
Every column in a row must be single valued.
Primary keys cannot be null
Foreign keys, if not null, must have values that correspond to the
value of a primary key in another table.
All nonkey attributes in a table must describe a characteristic of the
object identified by the primary key
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Two Approaches to Database Design
Normalization
• Following relational database creation rules
to design a relational database that is free
from delete, insert, and update anomalies.
• Decomposed set of tables are in third normal
form (3NF).
semantic
data
modeling
• Using knowledge of business
processes and information needs to
create a diagram that shows what to
include in a fully normalized database
(in 3NF).
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SELESAI