Management Information Systems By Effy Oz & Andy Jones
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Transcript of Management Information Systems By Effy Oz & Andy Jones
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Management Information SystemsBy Effy Oz & Andy Jones
www.cengage.co.uk/oz
Chapter 6: Databases and Data Warehouses
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Objectives
• Explain the difference between traditional file organisation and the database approach to managing digital data
• Explain how relational and object oriented database management systems are used to construct databases, populate them with data, and manipulate the data to produce information
• Enumerate the most important features and operations of a relational database, the most popular database model
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Objectives (continued)
• Understand how data modeling and design creates a conceptual blueprint of a database
• Discuss how databases are used on the Web• List the operations involved in transferring
data from transactional databases to data warehouses
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Managing Digital Data
• Businesses collect and dissect data• Data can be stored in powerful database format
– Easy access and manipulation• Databases have profound impact on business• Database technology integrated with Internet
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
The Traditional File Approach
• Traditional file approach: no mechanism for manipulating data
• Database approach: has mechanism for manipulating data
• Traditional approach inconvenient– High data redundancy– Low data integrity
• Data redundancy: duplication of data• Data integrity: accuracy of data
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
The Traditional File Approach (continued)
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
The Database Approach• Database approach: data organised as entities• Entity: object that has data
– People – Events– Products
• Character: smallest piece of data• Field: single piece of information about entity• Record: collection of fields
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
The Database Approach (continued)
• File: collection of related records• Database management system (DBMS):
program used to build databases– Populates with data– Manipulates data
• Query: message requesting access to data
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
The Database Approach (continued)
• Database has security issues• Database administrator (DBA): limits user
access to database– Requires users to enter codes
• DBMS bundled with fourth-generation languages
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
The Database Approach (continued)
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
The Database Approach (continued)
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
The Database Approach (continued)
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Database Models
• Database model: general logical structure– How records stored in database– Records linked differently in different models– Models constantly changing
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
The Relational Model
• Relational Model: consists of tables• Based on relational algebra
– Tuple: record– Attribute: field– Relation: table– Key: identifier field
• Used to retrieve records
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Relational Model (continued)
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
The Relational Model (continued)
• Primary key: unique key– Uniquely identifies record– Required in table
• Composite key: combination of fields– Serves as primary key
• Foreign key: shared field– Links tables
• Join table: composite of tables
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
The Relational Model (continued)
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
The Relational Model (continued)
• Table relationships with other tables• One-to-many relationship: one item in table
linked to many items in other table• Many-to-many relationship: many items in table
linked to many items of other table
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
The Object-Oriented Model
• Object-Oriented model: uses object-oriented approach
• Encapsulation: combined storage of data and relevant procedures– Allows object to be planted in different data
sets• Inheritance: creates new object by replicating
characteristics of existing (parent) object
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
The Object-Oriented Model (continued)
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Relational Operations• Relational operation: create temporary subset of
table• Create limited list or joined table list
– Select records based on conditions– Project columns– Join tables to create temporary table
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Structured Query Language
• Structured query language: language of choice for DBMSs
• Advantages– Standardised language– Used in many host languages– Portable
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
The Schema and Metadata
• Schema: plan– Describes structure of database– Names and sizes of fields– Identifies primary keys
• Data dictionary: repository of information about data
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
The Schema and Metadata (continued)
• Metadata: data about data– Source of data– Tables related to data– Field information– Usage of data– Population rules
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
The Schema and Metadata (continued)
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Data Modeling
• Databases must be carefully planned• Data modeling: analysis and organisation of
data– Proactive process– Develop conceptual blueprint
• Entity relationship diagram: graphical representation of relationships
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Data Modeling (continued)
• Entity relationship diagram– Boxes identify entities– Lines indicate relationship– Crossbars indicate mandatory fields– Circles indicate optional– Crows feet identify “many”
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Data Modeling (continued)
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By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Data Modeling (continued)
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By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Databases on the Web
• Web dependent on databases• Interface between Web and database required
– CGI– ASP– API
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By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Databases on the Web (continued)
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Data Warehousing
• Data collections used for transactions• Accumulation of transaction data useful• Data warehouse: large database
– Typically relational– Supports decision making– Data copied from transactional database
• Data mart: collection of data focusing on particular subject
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
From Database to Data Warehouse
• Transactional database not suitable for business analysis– Only current data– Not historic
• Data warehouse requires large storage capacity– Mainframe computers used– Scalability issue
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Phases in Building a Data Warehouse
• Begin building data warehouse after equipment secured– Extraction phase
• Create files from transactional database– Transformation phase
• Cleanse and modify data
• Loading phase• Transfer files to data warehouse
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Phases in Building a Data Warehouse (continued)
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Summary• organisations collect vast amounts of data• Database approach has advantages over
traditional approach• Character: smallest piece of data• File: collection of records• Designer must construct schema to construct
database
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Summary (continued)• Database management system enables database
construction and manipulation• Relational and object-oriented database models
have different advantages• Keys used to form links among entities• Object-oriented database maintains links
differently• SQL adopted as international standard
Use with Management Information Systems 1e
By Effy Oz & Andy Jones ISBN 9781844807581 © 2008 Cengage Learning
Summary (continued)
• Designers conduct data modeling to show required tables
• Databases often linked to Web• Data warehouses contain huge collections of historical
data• Data warehouse allows data extraction,
transformation, and loading• Invasion of privacy is exacerbated by database
technology