Transcript Chapter 3 - School of Business Administration

What it’s all about
Core Concepts
• Data – the source of information 
• Databases – where information is found 
• Database management – how information is
maintained and used 
• Database applications – matching information with
business needs. 

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Principles and Learning Objectives
• 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 of the database
approach to data management.
– Describe the relational database model and outline its
basic features. 
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Principles and Learning Objectives -2
• 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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Principles and Learning Objectives -3
• 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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What is DATA?
• Machine “experience”, what a machine makes of its
environment
Hmmmm. That
feels just like “3”
or maybe a “4”
but definitely not a
5
THREE
POINT FIVE
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What is INFORMATION?
• Human experience of Data: telling us something we
didn’t know or weren’t able to predict.
Was it Jones or
Smith we
promised the
stock to? Gotta
find out. Should
be Smith, but…
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Hey,
Schmoey,
Jones is
here for
his stock
OK, and thanks
for the
INFORMATION!
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The Organizational Data “Shadow”
Actual Event
Data “Impression”
Real
World
Sources
of Error
Error:
Spurious
Data
Data
“World”
Error:
Lost
Data
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Error:
Incorrect
Data
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Events as Data
• Each event generates some data
• The data are about the objects that play roles in the
event
• The data describe the objects and perhaps how
they relate to one another
• The events, too, relate to one another in various
ways.
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Data Events
• Consider a sales “event”
• It involves a number of objects: items sold,
salesperson, act of selling, customer, money
(objects are also called “entities”)
• Each event generates data that describe each of the
objects….
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Describing Objects
•
•
•
•
Items sold: No. of items, item description or number
Salesperson: Employee number, commission rate
Act of selling: Time, date, counter
Customer: Name and address or membership
number
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Data Representation: The Hierarchy
of Data
• Bit (a binary digit): a circuit that is either on or off
• Byte: 8 bits
• Character: each byte represents a character; the
basic building block of information
• Field: name, number, or characters that describe 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
– Bits, characters, fields, records, files, and databases
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The Hierarchy of Data (continued)
Figure 3.1: 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: a value of an attribute
• Key: field(s) that identify a record
• Primary key: field(s) that uniquely identify a record
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Data Entities, Attributes, and Keys
(continued)
Each
record is
an object
or event
Figure 3.2: Keys and Attributes
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The Traditional Approach Versus the
Database Approach
• Traditional approach: separate data files are created
for each application, i.e., each business problem
– Results in data redundancy (duplication)
– Data redundancy conflicts with data integrity
• Database approach: pool of related data is shared
by multiple applications
– Significant advantages over traditional approach
– Besides, all elements of business are related
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The Traditional Approach
Figure 3.3: The Traditional Approach to Data Management
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The Database Approach
Figure 3.4: The Database Approach to Data Management
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Advantages of the Database Approach
Table 3.1: Advantages of the Database Approach
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Advantages of the
Database Approach - 2
Table 3.1: Advantages of the Database Approach (continued)
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Disadvantages of the Database
Approach

Table 3.2: Disadvantages of the Database Approach
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Data Modeling and the Relational
Database Model
• When building a database, consider:
– Content: What data should be collected, at what cost?
– Access: What data should be provided to which
users, and when?
– Logical structure: How should data be arranged to
make 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 design
– Logical design
• Shows an abstract model of how data should be
structured and arranged to meet an organization’s
information needs
– Physical design
• Fine-tunes the logical database design for performance
and cost considerations
* What is a model? What does it do? For whom is it useful?
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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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ER Diagrams Tell a Story
Entity
Relationship
It reads
like a
story…
“Once upon a time
there was a
customer order
database. In this
database were
salespeople, each
of whom serviced
one or more
customers. Each
customer could
place one or more
orders, each of
which included
one or more line
items. Many of
these line items
could specify the
same product.
Each order
generated one and
only one invoice”
Figure 3.5: An Entity-Relationship (ER) Diagram for a Customer
Order Database
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The Relational Database Model
• Relational model: all data elements are placed in
two-dimensional tables (relations), which are the
logical equivalent of files
• In the relational model:
– Each row of a table represents a data entity
(descriptive of an object or event)
– Columns of the table represent attributes
• Domain: the allowable values for a given data
attribute (eg. 1-9 or “Any six-character word” or “true
or false”)
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The Relational Database Model
(continued)
Figure 3.6: A Relational Database Model
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Manipulating Data
•
•
•
•
Selecting: eliminates rows according to criteria
Projecting: eliminates columns in a table
Joining: combines two or more tables
Linking: relates or links two or more tables using
common data attributes
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Manipulating Data (continued)

Figure 3.8: Linking Data Tables to Answer an Inquiry
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Database Management Systems
(DBMS)
• Interface between
– Database and application programs
– Database and the user
• Database types
– Flat file
– Single user
– Multiple users
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Database Administration
• Database administrator (DBA): directs or performs
all activities to maintain a database environment
– Designing, implementing, and maintaining the
database system and the DBMS
– Establishing policies and procedures
– Training employees
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Popular Database Management
Systems
• Popular DBMSs for end users: Microsoft Access and
Corel 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
Ability to be integrated with other systems
Features of the DBMS
Vendor considerations
Cost of the system
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Using Databases with Other Software
• Database management systems are often used with
other software packages or the Internet
• A database management system can act as a frontend application or a back-end application
– Front-end application: interacts with users
– Back-end application: interacts with applications

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Data Warehouses, Data Marts, and
Data Mining
• Data warehouse: collects business information
from many sources in the enterprise
• Data mart: a subset of a data warehouse
• Data mining: an information-analysis tool for
discovering patterns and relationships in a data
warehouse or a data mart
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Data Warehouses, Data Marts, and
Data Mining (continued)
Figure 3.17: Elements of a Data Warehouse
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Data Warehouses, Data Marts, and
Data Mining (continued)
Table 3.3: Common Data-Mining Applications
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Business Intelligence
• Business intelligence (BI): gathering the right
information in a timely manner and usable form and
analyzing it to have a positive impact on business
• Knowledge management: capturing a company’s
collective expertise and distributing it wherever it
can help produce the biggest payoff
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Distributed Databases
• Distributed database
– 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
– 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 3.4: Comparison of OLAP and Data Mining
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Visual, Audio, and Other Database
Systems
•
•
•
•
Visual database systems
Audio database systems
Virtual database systems
Spatial data technology
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Summary
• Hierarchy of data: bits, characters, fields, records,
files, and databases
• An entity is 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 criteria
• Projecting eliminates columns in a table
• A database management system (DBMS) is a group
of programs used as an interface between:
– The database and application programs
– The 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
discovering patterns and relationships in a data
warehouse
• An object-oriented database stores both data and its
processing instructions
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