Chapter 5
Organizing Data &
Information
Data & Databases
Data consists of raw facts that when organized
may be transformed into information
A Database is a collection of data organized to
meet users’ needs
A Database Management System (DBMS) is
a group of programs that manipulate the database &
provide an interface between the database & the
user of the database or other application programs
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The Hierarchy of Data (Figure 5.1)
Database Management System
Database
File (table)
Record (entity, row)
Field (characteristic, column)
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Byte3 (character)
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Data Entities, Attributes, & Keys
 Entity: A generalized class of people, places, or
things for which data is collected, stored, &
maintained
• Examples: customers, employees
 Attribute: A characteristic of an entity;
something the entity is identified by
• Examples: customer name, employee name
 Key: A field or set of fields in a record that is a
unique identifier of a record
• Examples: social insurance number, customer
number
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Keys & Attributes (Figure 5.2)
<-------------------------------------Attributes------------------------------------>
Employee
Number
Last Name
First Name
Hire Date
Department
Number
005-10-6321 Johns
Francine
10-7-65
257
549-77-1001 Buckley
Bill
2-17-79
650
098-40-1370 Fiske
Steven
1-5-85
598
Key Field
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The Traditional Approach
(Figure 5.3)
Separate files are
created &
stored for each
application
program
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Drawbacks to the Traditional
Approach
 Data redundancy
– Duplication of data in separate files
 Lack of data integrity
– The degree to which the data in any one file is accurate
 Program-data dependence
– A situation in which programs & data organized for one
application are incompatible with programs & data
organized differently for another application
 Inability to Link Data
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The Database Approach (Figure 5.4)
A pool of related data is
shared by multiple
applications. Rather
than having separate
data files, each
application uses a
collection of data that is
either joined or related
in the database.
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Advantages to the Database Approach
 Improved strategic use of corporate data
 Reduced data redundancy
 Improved data integrity
 Easier modification & updating
 Data & program independence
 Better access to data & information
 Standardization of data access
 A framework for program development
 Better overall protection of the data
 Shared data & information resources
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Disadvantages to the Database
Approach
 Relatively high cost of purchasing & operating a
DBMS in a mainframe operating environment
 Increased cost of specialized staff
 Increased vulnerability
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Database Design
 Logical design precedes physical design
– Abstract model of how data should be structured &
arranged
– Users should assist in creating logical design
 Physical design starts with the logical design
– What specific hardware/software will be used
– Fine-tuning of logical design for performance/cost
considerations
– Planned Data Redundancy
• A way of organizing data in which the logical database design
is altered so that certain data entities are combined
– Summary totals are carried in the data records rather than
calculated from elemental data
– Some data attributes are repeated in more than one data
entity to improve database performance
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Data Modeling
 Data Model
– A map or diagram of entities & their relationships
 Enterprise data modeling
– Data modeling done at the level of the entire
organization
 Entity-Relationship (ER) diagrams
– A data model that uses basic graphical symbols to show
the organization of & relationships between data
(Figure 5.5)
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Database Models
 Hierarchical (Figure 5.6): A data model in which the
data is organized in a top-down or inverted tree
structure
 Network (Figure 5.7): An expansion of the hierarchical
database model with an owner-member relationship in
which a member may have many owners
 Relational (Figure 5.8): All data elements are placed
in two-dimensional tables, called relations, that are
the logical equivalent of files
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A Relational Database (3 tables)
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Relational Database Terminology
 Domain: Allowable values for attributes
 Selecting: Data manipulation that eliminates rows
(records) according to user-defined criteria
 Projecting: Data manipulation that eliminates
columns (attributes) in a table
 Joining: Data manipulation that combines two or
more tables
 Linking: Relating tables in a relational database
together by a common attribute(s)
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Schemas & Subschemas
 Schema
– View of the entire database
– Includes logical & physical structure & relationships
among all data
 Subschema
– User view of a portion of the database
– Can have many subschemas for one database
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Data Definition Language & Dictionary
 Data Definition Language (DDL)
– A collection of instructions & commands used to define
& describe data & data relationships in a database
 Data Dictionary
– A detailed description of all data used in the database
•
•
•
•
•
•
•
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Provides a standard definition of terms & data elements
Assists programmers in designing & writing programs
Simplifies database modification
Reduces data redundancy
Increases data reliability
Faster program development
Easier modification of data & information
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Logical & Physical Access Paths (Figure
5.14)
Physical Access Path
DBMS accesses a storage device
to retrieve data
Data on
Storage
Device
DBMS
Logical Access Path
Application requires
information from the
DBMS
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inquiries
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Other
Software
Application
Programs
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Manipulating Data
 Concurrency Control
– A method of dealing with a situation in which two or
more people need to access the same record in a
database at the same time
 Data Manipulation Language (DML)
– The commands that are used to manipulate the data in a
database
 Structured Query Language (SQL)
– A standardized data manipulation language for
querying a database
– Most modern databases are SQL compliant
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DBMS Selection Criteria
 Database size
 Number of concurrent users
 Performance
 Integration
 Features
 Vendor
 Cost
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Database Developments (1)
 Distributed Database
– A database in which the actual data may be spread
across several smaller databases connected via
telecommunications devices
– Transparent to user (user does not know where data is)
 Replicated Database
– Duplicate of original database (saves telecom time/$$)
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Database Developments (2)
 Data Warehouse
– A relational database management system designed
specifically to support management decision making
 Data Mart
– A subset of a data warehouse for small & medium-size
businesses or departments within larger companies
 Data Mining
– Automated discovery of patterns & relationships in a
data warehouse
– Built-in analysis tools
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Database Developments (3)
 On-line Transaction Processing (OLTP)
– TP happens at time of transaction
 On-line Analytical Processing (OLAP)
– Supports high speed analysis of data involving complex
relationships
 Multidimensional Databases
– Data can include graphics, photographs, sound files,
etc.
 Open Database Connectivity (ODBC)
– Software written in compliance with ODBC standards
can be used with any ODBC-compliant database
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Object-Relational Database
Management Systems
Can manipulate audio, video, & graphical data
 Hypertext: Users can search & manipulate
alphanumeric data in an unstructured way
 Hypermedia: Users can search & manipulate
multimedia forms of data
 Spatial Data Technology: Use of an objectrelational database to store & access data
according to the location it describes & to
permit spatial queries & analysis
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Case
 US West
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