Transcript Chapter 7 -- Managing Data Resources

Essentials of Management Information Systems, 6e
Chapter 7
Chapter 7 Managing Data Resources
Managing Data Resources
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Essentials of Management Information Systems, 6e
Chapter 7 Managing Data Resources
Objectives
1. Why do businesses have trouble finding the
information they need in their information
systems?
2. How does a database management system help
businesses improve the organization of their
information?
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Objectives
3. How do the principal types of database models
affect the way businesses can access and use
information?
4. What are the managerial and organizational
requirements of a database environment?
5. What new tools and technologies can make
databases more accessible and useful?
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Management Challenges
1. Organizational obstacles to a database
environment
2. Cost/benefit considerations
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Organizing Data in a Traditional File Environment
File Organization Terms and Concepts
• Bit: Smallest unit of data; binary digit (0,1)
• Byte: Group of bits that represents a single
character
• Field: Group of words or complete number
• Record: Group of related fields
• File: Group of records of the same type
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Organizing Data in a Traditional File Environment
File Organization Terms and Concepts
• Database: Group of related files
• Entity: Person, place, thing, or event about which
information must be kept
• Attribute: A piece of information describing a
particular entity
• Key field: Field that uniquely identifies every
record in a file
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Organizing Data in a Traditional File Environment
The data hierarchy
Figure 7-1
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Organizing Data in a Traditional File Environment
Entities and attributes
Figure 7-2
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Organizing Data in a Traditional File Environment
Problems with the Traditional File Environment
• Data redundancy
• Program-data dependence
• Lack of flexibility
• Poor security
• Lack of data-sharing and availability
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Organizing Data in a Traditional File Environment
Traditional file processing
Figure 7-3
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The Database Approach to Data Management
Database Management Systems
Database
• Collection of centralized data
• Controls redundant data
• Data stored so as to appear to users in one location
• Services multiple application
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The Database Approach to Data Management
The contemporary database environment
Figure 7-4
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The Database Approach to Data Management
Database Management Systems
Database Management System (DBMS)
• Creates and maintains databases
• Eliminates requirement for data definition
statements
• Acts as interface between application programs
and physical data files
• Separates logical and physical views of data
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The Database Approach to Data Management
Database Management Systems
Three Components to a DBMS
1. Data definition language: Formal language
programmers use to specify structure of database
2. Data manipulation language: For extracting data
from database, e.g. SQL
3. Data dictionary: Tool for storing, organizing
definitions of data elements and data
characteristics
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The Database Approach to Data Management
Sample data dictionary report
Figure 7-5
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The Database Approach to Data Management
Database Management Systems
How a DBMS Solves Problems of a
Traditional File Environment
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Reduces data redundancy
Eliminates data inconsistency
Uncouples programs from data
Increases access and availability of data
Allows central management of data, data use, and
security
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The Database Approach to Data Management
Types of Databases
Relational DBMS
• Represents data as two-dimensional tables called
relations
• Relates data across tables based on common data
element
• Examples: DB2, Oracle, MS SQL Server
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The Database Approach to Data Management
The relational data model
Figure 7-6
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The Database Approach to Data Management
Types of Databases
Three Basic Operations in a Relational
Database
• Select: Creates subset of rows that meet specific
criteria
• Join: Combines relational tables to provide users
with information
• Project: Enables users to create new tables
containing only relevant information
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The Database Approach to Data Management
The three basic operations of a relational DBMS
Figure 7-7
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Types of Databases
Hierarchical DBMS
• Older system presenting data in tree-like structure
• Models one-to-many parent-child relationships
• Found in large legacy systems requiring intensive highvolume transactions: Banks; insurance companies
• Examples: IBMs IMS
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The Database Approach to Data Management
A hierarchical database for a human resources system
Figure 7-8
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Types of Databases
Network DBMS
• Older logical database model
• Models many-to-many parent-child relationships
• Example: Student – course relationship: Each
student has many courses; each course has many
students
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The Database Approach to Data Management
The network data model
Figure 7-9
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Types of Databases
Disadvantages of Hierarchical and
Network DBMS
• Outdated
• Less flexible compared to RDBMS
• Lack support for ad-hoc and English language-like
queries
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Types of Databases
Object-Oriented Databases (OODBMS)
• Stores data and procedures as objects
• Better able to handle graphics and recursive data
• Data models more flexible
• Slower than RDBMS
• Hybrid: object-relational DBMS
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Creating a Database Environment
Designing Databases
Two Design Exercises in Creating Database
• Conceptual (logical) design: Abstract model of
database from business perspective
• Physical design: How the database is actually
arranged on direct access storage devices
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Designing Databases
Conceptual Database Design
• Identifies relationships between data elements
• Identifies most efficient way to group data
elements
• Identifies redundant data elements
• Identifies grouping of data elements needed for
specific applications
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Creating a Database Environment
Designing Databases
Entity-Relationship Diagram
A methodology for documenting databases that
illustrates the relationship between various
elements in the database
Normalization
The process of creating small, stable, and adaptive
data structures from complex groups of data when
designing a relational database
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An entity-relationship diagram
Figure 7-10
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Creating a Database Environment
An unnormalized relation for ORDER
Figure 7-11
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A normalized relation for ORDER
Figure 7-12
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Distributing Databases
Distributed Database
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Partitioned or replicated to more than one location
Increases service and responsiveness
Reduces vulnerability of single, massive central site
Depend on telecommunication lines
Pose security risks through distribution of sensitive data
Central data must be updated or justified with local data
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Creating a Database Environment
Distributed databases
Figure 7-13
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Key organizational elements in the database environment
Figure 7-14
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Management Requirements for Database Systems
Data Administration
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Develop information policy
Define information requirements
Plan for data
Oversee logical database design and database
dictionary development
• Monitor use of information
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Management Requirements for Database Systems
Data Planning and Modeling Methodology
• Enterprise-wide planning for data
• Identify key entities, attributes, and relationships
that constitute the organization’s data
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Creating a Database Environment
Management Requirements for Database Systems
Database Technology, Management,
and Users
• Databases require DBMS software and staff
• Database design group defines and organizes
structure and content of database
• Database administration: establish physical
database, logical relations, access rules
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Database Trends
Multidimensional Data Analysis
Online Analytical Processing (OLAP)
• Multidimensional data analysis
• Enables users to view the same data in different
ways using multiple dimensions
• Each aspect of information – product, price,
region – represents a different dimension
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Database Trends
Multidimensional data model
Figure 7-15
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Database Trends
Data Warehouses and Datamining
• Data warehouse: Stores current and historical data
for reporting, analysis
• Data mart: Subset of data warehouse with
summary of data for specific users
• Datamining: Techniques to find hidden patterns,
relationships in large pools of data to infer rules
for predicting future trends
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Database Trends
Components of a data warehouse
Figure 7-16
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Database Trends
Data Warehouses and Datamining
Benefits of Data Warehouses
• Improved information and accessibility
• Ability to model and remodel data
• Enable access to data without affecting
performance of underlying operational legacy
systems
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Database Trends
Window on Management
Data Reveal New Sales Opportunities
• How did the use of data warehouses and
datamining help management at these companies
make better decisions?
• What value do these systems provide?
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Database Trends
Data Warehouses and Datamining
Hypermedia database
• Organizes data as network of nodes
• Links nodes in pattern specified by user
• Supports text, graphic, sound, video and
executable programs
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Database Trends
A hypermedia database
Figure 7-17
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Database Trends
Databases and the Web
Linking Internal Databases to the Web
• Database server:
– Hosts DBMS
– Receives SQL requests
– Provides required data
• Middleware:
– Works between Web server and DBMS to take requests
– Handles connectivity to database
– Can be application server or CGI scripts
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Database Trends
Linking internal databases to the Web
Figure 7-18
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Databases and the Web
Advantages to Web Access to Databases
• Browser software easy to use; little training
• Web interface requires no changes to internal
database
• Costs less than custom interfaces
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Database Trends
Window on Technology
Web Access for Royal Bank Statements
Pays Off
• What are the business benefits of providing a Web
interface for the Bankbook Reconstruct
application?
• What value does this application provide the
company and its customers?
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Chapter 7 Case Study
Database Woes Plague Homeland Security and Law Enforcement
1. Briefly summarize why it is important to
connect much of the data in many of the federal,
state, and local information systems.
2. Describe the major data management problems
in bringing these data together.
3. Describe the management, organization, and
technology issues that need to be addressed to
make these data easily available to those who
need it.
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Chapter 7 Case Study
Database Woes Plague Homeland Security and Law Enforcement
4. Suppose you are a consultant to the federal
government. Based on what you have read in
this chapter, suggest and describe three
approaches you might recommend for making
this massive amount of data easily and quickly
available when needed.
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