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• The database approach to data management provides
significant advantages over the traditional file-based
approach
• Define general data management concepts and terms,
highlighting the advantages and disadvantages of the
database approach to data management
• Describe the relational database model and outline its basic
features
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• A well-designed and well-managed database is an
extremely valuable tool in supporting decision making
• Identify the common functions performed by all database
management systems and identify popular end-user
database management systems
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• The number and types of database applications will
continue to evolve and yield real business benefits
• Identify and briefly discuss current database applications
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Introduction
• Database management system (DBMS): group of
programs that manipulate database and provide interface
between database and users
• Database administrator (DBA): a skilled information
systems professional who directs all activities related to
organization’s database
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Data Management: The Hierarchy of Data
• A bit (a binary digit) represents a circuit that is either on
or off
• A byte is typically 8 bits
• Character: each byte represents a character, the basic
building block of information
• Field: typically a name, number, or combination of
characters that describes an aspect of a business object or
activity
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The Hierarchy of Data (continued)
• Record: a collection of related data fields
• File: a collection of related records
• Database: a collection of integrated and related files
• Hierarchy of data: formed by bits, characters, fields,
records, files, and databases
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Figure 5.1: The Hierarchy of Data
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Data Entities, Attributes, and Keys
• Entity: a generalized class of people, places, or things
(objects) for which data is collected, stored, and
maintained
• Attribute: a characteristic of an entity
• Data item: the specific value of an attribute
• Key: a field or set of fields in a record that is used to
identify the record
• Primary key: a field or set of fields that uniquely
identifies the record
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Figure 5.2: Keys and Attributes
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The Traditional Approach Versus the
Database Approach
• Traditional approach: separate data files are created and
stored for each application program
• Results in data redundancy: duplication of data in separate
files
• Data redundancy conflicts with data integrity (the degree to
which the data in any one file is accurate)
• Database approach: approach whereby a pool of related
data is shared by multiple application programs; offers
significant advantages over traditional file-based approach
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Figure 5.3: The Traditional Approach to
Data Management
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Figure 5.4: The Database Approach to
Data Management
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Table 5.1: Advantages of the
Database Approach
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Table 5.1: Advantages of the Database
Approach (continued)
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Table 5.2: Disadvantages of the
Database Approach
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Data Modeling and the Relational
Database Model
• When building a database, an organization must consider:
• Content: What data should be collected and at what cost?
• Access: What data should be provided to which users and
when?
• Logical structure: How should data be arranged so that it
makes sense to a given user?
• Physical organization: Where should data be physically
located?
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Data Modeling
• Building a database requires two types of designs:
• Logical design: shows an abstract model of how the data
should be structured and arranged to meet an organization’s
information needs
• Physical design: starts from the logical database design
and fine-tunes it for performance and cost considerations
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Data Modeling (continued)
• Data model: a diagram of data entities and their
relationships
• Entity-relationship (ER) diagrams: data models that
use basic graphical symbols to show the organization of
and relationships between data
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Figure 5.5: An Entity-Relationship (ER)
Diagram for a Customer Order Database
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The Relational Database Model
• Relational model: describes data in which all data
elements are placed in two-dimensional tables, called
relations, that are the logical equivalent of files
• In the relational model:
• Each row of a table represents a data entity
• Columns of the table represent attributes
• Domain: the allowable values for data attributes
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Figure 5.6: A Relational Database Model
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Manipulating Data
• Selecting: eliminates rows according to certain criteria
• Projecting: eliminates columns in a table
• Joining: combines two or more tables
• Linking: combines two or more tables using common
data attributes to form a new table with only the unique
data attributes
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Database Management Systems
(DBMS)
• A group of programs used as an interface between a
database and application programs or a database and user
• Database types
• Flat file
• Single user
• Multiple users
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Providing a User View
• Schema: a description of the entire database
• User view: the portion of the database a user can access
• Subschemas are used to create different user views
• Subschema: a file that contains a description of a subset
of the database and identifies which users can view and
modify the data items in the subset
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Figure 5.10: The Use of Schemas
and Subschemas
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Creating and Modifying the Database
• Data definition language (DDL)
• A collection of instructions and commands used to define
and describe data and data relationships in a specific
database
• Allows the database’s creator to describe the data and the
data relationships that are to be contained in the schema
and subschemas
• Data dictionary: a detailed description of all the data
used in the database
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Figure 5.11: Using a Data Definition
Language to Define a Schema
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Figure 5.12: A Typical Data
Dictionary Entry
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Storing and Retrieving Data
• When an application program request data from DBMS,
the application program follows a logical access path
• When the DBMS goes to a storage device to retrieve the
requested data, it follows a path to the physical location
(physical access path) where the data is stored
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Figure 5.13: Logical and Physical Access
Paths
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Manipulating Data and
Generating Reports
• Data manipulation language (DML): the commands
that are used to manipulate the data in a database
• Structured Query Language (SQL): adopted by the
American National Standards Institute (ANSI) as the
standard query language for relational databases
• Once a database has been set up and loaded with data, it
can produce reports, documents, and other outputs
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Table 5.6: Examples of SQL Commands
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Popular Database Management
Systems
• Popular DBMSs for end users include Microsoft’s Access
and Corel’s Paradox
• The complete database management software market
includes databases by IBM, Oracle, and Microsoft
• Examples of open-source database systems: PostgreSQL
and MySQL
• Many traditional database programs are now available on
open-source operating systems
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Selecting a Database Management
System
• Important characteristics of databases to consider:
• Size of the database
• Number of concurrent users
• Performance
• The ability of the DBMS to be integrated with other
systems
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Selecting a Database Management
System (continued)
• Important characteristics of databases to consider
(continued):
• Features of the DBMS
• Vendor considerations
• Cost of the system
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Database Applications: Linking the
Company Database to the Internet
• Corporate databases can be accessed by customers,
suppliers, and company employees through:
• The Internet
• Intranets
• Extranets
• Semantic Web: a seamless integration of traditional
databases with the Internet
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Data Warehouses, Data Marts, and
Data Mining
• Data warehouse: a database that collects business
information from many sources in the enterprise, covering
all aspects of the company’s processes, products, and
customers
• Data mart: a subset of a data warehouse
• Data mining: an information-analysis tool that involves
the automated discovery of patterns and relationships in a
data warehouse
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Figure 5.17: Elements of a
Data Warehouse
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Table 5.8: Common Data-Mining
Applications
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Business Intelligence
• Business intelligence (BI): the process of gathering
enough of the right information in a timely manner and
usable form and analyzing it to have a positive impact on
business strategy, tactics, or operations
• Knowledge management: the process of capturing a
company’s collective expertise wherever it resides and
distributing it wherever it can help produce the biggest
payoff
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Distributed Databases
• Distributed database
• A database in which the data may be spread across several
smaller databases connected via telecommunications
devices
• Corporations get more flexibility in how databases are
organized and used
• Replicated database: a database that holds a duplicate
set of frequently used data
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Online Analytical Processing (OLAP)
• Software that allows users to explore data from a number
of different perspectives
Table 5.9: Comparison of OLAP and Data Mining
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Open Database Connectivity (ODBC)
• Standards that ensure that software can be used with any
ODBC-compliant database
• Can be used to export, import, or link tables between
different applications
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Figure 5.19: Advantages of ODBC
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Object-Oriented and Object-Relational
Database Management Systems
• Object-oriented database
• Stores both data and its processing instructions
• Method: a procedure or action
• Message: a request to execute or run a method
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Object-Oriented and Object-Relational
Database Management Systems
(continued)
• Object-oriented database management system
(OODBMS): group of programs that manipulate an
object-oriented database and provide a user interface and
connections to other application programs
• Object-relational database management system
(ORDBMS): DBMS capable of manipulating audio,
video, and graphical data
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Summary
• Hierarchy of data: bits, characters, fields, records, files,
and databases
• Entity: a generalized class of things (objects) for which
data is collected, stored, and maintained
• Attribute: characteristic of an entity
• Data model: diagram of entities and relationships
• Relational model: describes data in which all elements
are placed in two-dimensional tables called relations
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Summary (continued)
• Selecting: eliminates rows according to certain criteria
• Projecting: eliminates columns in a table
• Database management system (DBMS): group of
programs used as an interface
• Between a database and application programs
• Database and the user
• Data dictionary: detailed description of all the data used
in the database
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Summary (continued)
• Data warehouse: database that collects business
information from all aspects of a company’s processes,
products, and customers
• Data mining: an information-analysis tool for the
automated discovery of patterns and relationships in a
data warehouse
• Open database connectivity (ODBC) standards: ensure
that software can be used with any ODBC-compliant
database
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