Chapter 5 Data
Resource Management
James A. O'Brien, and George Marakas.
Management Information Systems with MISource
2007, 8th
ed. Boston, MA: McGraw-Hill, Inc.,
2007. ISBN: 13 9780073323091
Chapter 5 Data Resource ManagementChapter 5 2
Logical Data Elements
Chapter 5 Data Resource ManagementChapter 5 3
Logical Data Elements
 Character
 A single alphabetic, numeric, or other symbol
 Field or data item
 Represents an attribute (characteristic or quality)
of some entity (object, person, place, event)
 Example: salary, job title
 Record
 Grouping of all the fields used to describe the attributes of an
entity
 Example: payroll record with name, SSN, pay rate
 File or table
 A group of related records
 Database
 An integrated collection of logically related
data elements
Chapter 5 Data Resource ManagementChapter 5 4
Electric Utility Database
Chapter 5 Data Resource ManagementChapter 5 5
Database Structures
 Common database structures…
Hierarchical
Network
Relational
Object-oriented
Multi-dimensional
Chapter 5 Data Resource ManagementChapter 5 6
Hierarchical Structure
 Early DBMS structure
 Records arranged in tree-
like structure
 Relationships are one-to-
many
Chapter 5 Data Resource ManagementChapter 5 7
Network Structure
 Used in some mainframe DBMS packages
 Many-to-many relationships
Chapter 5 Data Resource ManagementChapter 5 8
Relational Structure
 Most widely used structure
 Data elements are stored in tables
 Row represents a record; column is a field
 Can relate data in one file with data in another,
if both files share a common data element
Chapter 5 Data Resource ManagementChapter 5 9
Relational Operations
 Select
Create a subset of records that meet a stated
criterion
 Example: employees earning more than
$30,000
 Join
Combine two or more tables temporarily
Looks like one big table
 Project
Create a subset of columns in a table
Chapter 5 Data Resource ManagementChapter 5 10
Multidimensional Structure
 Variation of relational model
Uses multidimensional structures to
organize data
Data elements are viewed as being in cubes
Popular for analytical databases that support
Online Analytical Processing (OLAP)
Chapter 5 Data Resource ManagementChapter 5 11
Multidimensional Model
Chapter 5 Data Resource ManagementChapter 5 12
Object-Oriented Structure
 An object consists of
Data values describing the attributes of an
entity
Operations that can be performed on the data
 Encapsulation
Combine data and operations
 Inheritance
New objects can be created by replicating
some or all of the characteristics of parent
objects
Chapter 5 Data Resource ManagementChapter 5 13
Object-Oriented Structure
Source: Adapted from Ivar Jacobsen, Maria Ericsson, and Ageneta Jacobsen, The Object
Advantage: Business Process Reengineering with Object Technology (New York: ACM Press,
1995), p. 65.
Copyright @ 1995, Association for Computing Machinery. By permission.
Chapter 5 Data Resource ManagementChapter 5 14
Object-Oriented Structure
 Used in object-oriented database management
systems (OODBMS)
 Supports complex data types more efficiently
than relational databases
Example: graphic images, video clips,
web pages
Chapter 5 Data Resource ManagementChapter 5 15
Evaluation of Database Structures
 Hierarchical
Works for structured, routine transactions
Can’t handle many-to-many relationship
 Network
More flexible than hierarchical
Unable to handle ad hoc requests
 Relational
Easily responds to ad hoc requests
Easier to work with and maintain
Not as efficient/quick as hierarchical or network
Chapter 5 Data Resource ManagementChapter 5 16
Database Development
 Database Administrator (DBA)
In charge of enterprise database development
Improves the integrity and security of
organizational databases
Uses Data Definition Language (DDL) to
develop and specify data contents,
relationships, and structure
Stores these specifications in a data
dictionary or a metadata repository
Chapter 5 Data Resource ManagementChapter 5 17
Data Dictionary
 A data dictionary
Contains data about data (metadata)
Relies on specialized software component to
manage a database of data definitions
 It contains information on..
The names and descriptions of all types of
data records and their interrelationships
Requirements for end users’ access and use
of application programs
Database maintenance
Security
Chapter 5 Data Resource ManagementChapter 5 18
Database Development
Chapter 5 Data Resource ManagementChapter 5 19
Data Planning Process
 Database development is a top-down process
Develop an enterprise model that defines the
basic business process of the enterprise
Define the information needs of end users in
a business process
Identify the key data elements that are
needed to perform specific business activities
(entity relationship diagrams)
Chapter 5 Data Resource ManagementChapter 5 20
Entity Relationship Diagram
Chapter 5 Data Resource ManagementChapter 5 21
Database Design Process
 Data relationships are represented in a data model that
supports a business process
 This model is the schema or subschema on which to
base…
 The physical design of the database
 The development of application programs to support
business processes
 Logical Design
 Schema - overall logical view of relationships
 Subschema - logical view for specific end users
 Data models for DBMS
 Physical Design
 How data are to be physically stored and
accessed on storage devices
Chapter 5 Data Resource ManagementChapter 5 22
Logical and Physical Database Views
Chapter 5 Data Resource ManagementChapter 5 23
Data Resource Management
 Data resource management is a managerial activity
 Uses data management, data warehousing,
and other IS technologies
 Manages data resources to meet the information
needs of business stakeholders
 Data stewards
 Dedicated to establishing and maintaining the
quality of data
 Need business, technology, and diplomatic skills
 Focus on data content
 Judgment is a big part of the job
Chapter 5 Data Resource ManagementChapter 5 24
Types of Databases
Chapter 5 Data Resource ManagementChapter 5 25
Operational Databases
 Stores detailed data needed to support business
processes and operations
Also called subject area databases (SADB),
transaction databases, and production
databases
Database examples: customer, human
resource, inventory
Chapter 5 Data Resource ManagementChapter 5 26
Distributed Databases
 Distributed databases are copies or parts of databases stored on
servers at multiple locations
 Improves database performance at worksites
 Advantages
 Protection of valuable data
 Data can be distributed into smaller databases
 Each location has control of its local data
 All locations can access any data, any where
 Disadvantages
 Maintaining data accuracy
 Replication
 Look at each distributed database and find changes
 Apply changes to each distributed database
 Very complex
 Duplication
 One database is master
 Duplicate the master after hours, in all locations
 Easier to accomplish
Chapter 5 Data Resource ManagementChapter 5 27
External Databases
 Databases available for a fee from commercial
online services, or free from the Web
Example: hypermedia databases, statistical
databases, bibliographic and full text
databases
Search engines like Google or Yahoo are
external databases
Chapter 5 Data Resource ManagementChapter 5 28
Hypermedia Databases
 A hypermedia database contains
Hyperlinked pages of multimedia
Interrelated hypermedia page elements,
rather than interrelated data records
Chapter 5 Data Resource ManagementChapter 5 29
Components of Web-Based
System
Chapter 5 Data Resource ManagementChapter 5 30
Data Warehouses
 Stores static data that has been extracted from
other databases in an organization
Central source of data that has been cleaned,
transformed, and cataloged
Data is used for data mining, analytical
processing, analysis, research, decision support
 Data warehouses may be divided into data marts
Subsets of data that focus on specific aspects
of a company (department or business process)
Chapter 5 Data Resource ManagementChapter 5 31
Data Warehouse Components
Chapter 5 Data Resource ManagementChapter 5 32
Applications and Data Marts
Chapter 5 Data Resource ManagementChapter 5 33
Data Mining
 Data in data warehouses are analyzed to reveal
hidden patterns and trends
Market-basket analysis to identify new
product bundles
Find root cause of qualify or manufacturing
problems
Prevent customer attrition
Acquire new customers
Cross-sell to existing customers
Profile customers with more accuracy
Chapter 5 Data Resource ManagementChapter 5 34
Traditional File Processing
 Data are organized, stored, and processed in
independent files
Each business application designed to use
specialized data files containing specific
types of data records
 Problems
Data redundancy
Lack of data integration
Data dependence (files, storage devices,
software)
Lack of data integrity or standardization
Chapter 5 Data Resource ManagementChapter 5 35
Traditional File Processing
Chapter 5 Data Resource ManagementChapter 5 36
Database Management
Approach
 The foundation of modern methods of managing
organizational data
Consolidates data records formerly in
separate files into databases
Data can be accessed by many different
application programs
A database management system (DBMS) is
the software interface between users and
databases
Chapter 5 Data Resource ManagementChapter 5 37
Database Management
Approach
Chapter 5 Data Resource ManagementChapter 5 38
Database Management System
 In mainframe and server computer systems, a
software package that is used to…
Create new databases and database
applications
Maintain the quality of the data in an
organization’s databases
Use the databases of an organization to
provide the information needed by end users
Chapter 5 Data Resource ManagementChapter 5 39
Common DBMS Software
Components
 Database definition
Language and graphical tools to define
entities, relationships, integrity constraints,
and authorization rights
 Nonprocedural access
Language and graphical tools to access data
without complicated coding
 Application development
Graphical tools to develop menus, data entry
forms, and reports
Chapter 5 Data Resource ManagementChapter 5 40
Common DBMS Software
Components
 Procedural language interface
Language that combines nonprocedural access
with full capabilities of a programming language
 Transaction processing
Control mechanism prevents interference from
simultaneous users and recovers lost data after
a failure
 Database tuning
Tools to monitor, improve database performance
Chapter 5 Data Resource ManagementChapter 5 41
Database Management System
 Database Development
Defining and organizing the content,
relationships, and structure of the data needed
to build a database
 Database Application Development
Using DBMS to create prototypes of queries,
forms, reports, Web pages
 Database Maintenance
Using transaction processing systems and
other tools to add, delete, update, and correct
data
Chapter 5 Data Resource ManagementChapter 5 42
DBMS Major Functions
Chapter 5 Data Resource ManagementChapter 5 43
Database Interrogation
 End users use a DBMS query feature or report
generator
Response is video display or printed report
No programming is required
 Query language
Immediate response to ad hoc data requests
 Report generator
Quickly specify a format for information you
want to present as a report
Chapter 5 Data Resource ManagementChapter 5 44
Database Interrogation
 SQL Queries
Structured, international standard query
language found in many DBMS packages
Query form is SELECT…FROM…WHERE…
Chapter 5 Data Resource ManagementChapter 5 45
Database Interrogation
 Boolean Logic
Developed by George Boole in the mid-1800s
Used to refine searches to specific
information
Has three logical operators: AND, OR, NOT
 Example
Cats OR felines AND NOT dogs OR
Broadway
Chapter 5 Data Resource ManagementChapter 5 46
Database Interrogation
 Graphical and Natural Queries
It is difficult to correctly phrase SQL and other
database language search queries
Most DBMS packages offer easier-to-use,
point-and-click methods
Translates queries into SQL commands
Natural language query statements are similar
to conversational English
Chapter 5 Data Resource ManagementChapter 5 47
Graphical Query Wizard
Chapter 5 Data Resource ManagementChapter 5 48
Database Maintenance
 Accomplished by transaction processing
systems and other applications, with the support
of the DBMS
Done to reflect new business transactions and
other events
Updating and correcting data, such as
customer addresses
Chapter 5 Data Resource ManagementChapter 5 49
Application Development
 Use DBMS software development tools to
develop custom application programs
Not necessary to develop detailed data-
handling procedures using conventional
programming languages
Can include data manipulation language
(DML) statements that call on the DBMS to
perform necessary data handling

Chapter 5 data resource management

  • 1.
    Chapter 5 Data ResourceManagement James A. O'Brien, and George Marakas. Management Information Systems with MISource 2007, 8th ed. Boston, MA: McGraw-Hill, Inc., 2007. ISBN: 13 9780073323091
  • 2.
    Chapter 5 DataResource ManagementChapter 5 2 Logical Data Elements
  • 3.
    Chapter 5 DataResource ManagementChapter 5 3 Logical Data Elements  Character  A single alphabetic, numeric, or other symbol  Field or data item  Represents an attribute (characteristic or quality) of some entity (object, person, place, event)  Example: salary, job title  Record  Grouping of all the fields used to describe the attributes of an entity  Example: payroll record with name, SSN, pay rate  File or table  A group of related records  Database  An integrated collection of logically related data elements
  • 4.
    Chapter 5 DataResource ManagementChapter 5 4 Electric Utility Database
  • 5.
    Chapter 5 DataResource ManagementChapter 5 5 Database Structures  Common database structures… Hierarchical Network Relational Object-oriented Multi-dimensional
  • 6.
    Chapter 5 DataResource ManagementChapter 5 6 Hierarchical Structure  Early DBMS structure  Records arranged in tree- like structure  Relationships are one-to- many
  • 7.
    Chapter 5 DataResource ManagementChapter 5 7 Network Structure  Used in some mainframe DBMS packages  Many-to-many relationships
  • 8.
    Chapter 5 DataResource ManagementChapter 5 8 Relational Structure  Most widely used structure  Data elements are stored in tables  Row represents a record; column is a field  Can relate data in one file with data in another, if both files share a common data element
  • 9.
    Chapter 5 DataResource ManagementChapter 5 9 Relational Operations  Select Create a subset of records that meet a stated criterion  Example: employees earning more than $30,000  Join Combine two or more tables temporarily Looks like one big table  Project Create a subset of columns in a table
  • 10.
    Chapter 5 DataResource ManagementChapter 5 10 Multidimensional Structure  Variation of relational model Uses multidimensional structures to organize data Data elements are viewed as being in cubes Popular for analytical databases that support Online Analytical Processing (OLAP)
  • 11.
    Chapter 5 DataResource ManagementChapter 5 11 Multidimensional Model
  • 12.
    Chapter 5 DataResource ManagementChapter 5 12 Object-Oriented Structure  An object consists of Data values describing the attributes of an entity Operations that can be performed on the data  Encapsulation Combine data and operations  Inheritance New objects can be created by replicating some or all of the characteristics of parent objects
  • 13.
    Chapter 5 DataResource ManagementChapter 5 13 Object-Oriented Structure Source: Adapted from Ivar Jacobsen, Maria Ericsson, and Ageneta Jacobsen, The Object Advantage: Business Process Reengineering with Object Technology (New York: ACM Press, 1995), p. 65. Copyright @ 1995, Association for Computing Machinery. By permission.
  • 14.
    Chapter 5 DataResource ManagementChapter 5 14 Object-Oriented Structure  Used in object-oriented database management systems (OODBMS)  Supports complex data types more efficiently than relational databases Example: graphic images, video clips, web pages
  • 15.
    Chapter 5 DataResource ManagementChapter 5 15 Evaluation of Database Structures  Hierarchical Works for structured, routine transactions Can’t handle many-to-many relationship  Network More flexible than hierarchical Unable to handle ad hoc requests  Relational Easily responds to ad hoc requests Easier to work with and maintain Not as efficient/quick as hierarchical or network
  • 16.
    Chapter 5 DataResource ManagementChapter 5 16 Database Development  Database Administrator (DBA) In charge of enterprise database development Improves the integrity and security of organizational databases Uses Data Definition Language (DDL) to develop and specify data contents, relationships, and structure Stores these specifications in a data dictionary or a metadata repository
  • 17.
    Chapter 5 DataResource ManagementChapter 5 17 Data Dictionary  A data dictionary Contains data about data (metadata) Relies on specialized software component to manage a database of data definitions  It contains information on.. The names and descriptions of all types of data records and their interrelationships Requirements for end users’ access and use of application programs Database maintenance Security
  • 18.
    Chapter 5 DataResource ManagementChapter 5 18 Database Development
  • 19.
    Chapter 5 DataResource ManagementChapter 5 19 Data Planning Process  Database development is a top-down process Develop an enterprise model that defines the basic business process of the enterprise Define the information needs of end users in a business process Identify the key data elements that are needed to perform specific business activities (entity relationship diagrams)
  • 20.
    Chapter 5 DataResource ManagementChapter 5 20 Entity Relationship Diagram
  • 21.
    Chapter 5 DataResource ManagementChapter 5 21 Database Design Process  Data relationships are represented in a data model that supports a business process  This model is the schema or subschema on which to base…  The physical design of the database  The development of application programs to support business processes  Logical Design  Schema - overall logical view of relationships  Subschema - logical view for specific end users  Data models for DBMS  Physical Design  How data are to be physically stored and accessed on storage devices
  • 22.
    Chapter 5 DataResource ManagementChapter 5 22 Logical and Physical Database Views
  • 23.
    Chapter 5 DataResource ManagementChapter 5 23 Data Resource Management  Data resource management is a managerial activity  Uses data management, data warehousing, and other IS technologies  Manages data resources to meet the information needs of business stakeholders  Data stewards  Dedicated to establishing and maintaining the quality of data  Need business, technology, and diplomatic skills  Focus on data content  Judgment is a big part of the job
  • 24.
    Chapter 5 DataResource ManagementChapter 5 24 Types of Databases
  • 25.
    Chapter 5 DataResource ManagementChapter 5 25 Operational Databases  Stores detailed data needed to support business processes and operations Also called subject area databases (SADB), transaction databases, and production databases Database examples: customer, human resource, inventory
  • 26.
    Chapter 5 DataResource ManagementChapter 5 26 Distributed Databases  Distributed databases are copies or parts of databases stored on servers at multiple locations  Improves database performance at worksites  Advantages  Protection of valuable data  Data can be distributed into smaller databases  Each location has control of its local data  All locations can access any data, any where  Disadvantages  Maintaining data accuracy  Replication  Look at each distributed database and find changes  Apply changes to each distributed database  Very complex  Duplication  One database is master  Duplicate the master after hours, in all locations  Easier to accomplish
  • 27.
    Chapter 5 DataResource ManagementChapter 5 27 External Databases  Databases available for a fee from commercial online services, or free from the Web Example: hypermedia databases, statistical databases, bibliographic and full text databases Search engines like Google or Yahoo are external databases
  • 28.
    Chapter 5 DataResource ManagementChapter 5 28 Hypermedia Databases  A hypermedia database contains Hyperlinked pages of multimedia Interrelated hypermedia page elements, rather than interrelated data records
  • 29.
    Chapter 5 DataResource ManagementChapter 5 29 Components of Web-Based System
  • 30.
    Chapter 5 DataResource ManagementChapter 5 30 Data Warehouses  Stores static data that has been extracted from other databases in an organization Central source of data that has been cleaned, transformed, and cataloged Data is used for data mining, analytical processing, analysis, research, decision support  Data warehouses may be divided into data marts Subsets of data that focus on specific aspects of a company (department or business process)
  • 31.
    Chapter 5 DataResource ManagementChapter 5 31 Data Warehouse Components
  • 32.
    Chapter 5 DataResource ManagementChapter 5 32 Applications and Data Marts
  • 33.
    Chapter 5 DataResource ManagementChapter 5 33 Data Mining  Data in data warehouses are analyzed to reveal hidden patterns and trends Market-basket analysis to identify new product bundles Find root cause of qualify or manufacturing problems Prevent customer attrition Acquire new customers Cross-sell to existing customers Profile customers with more accuracy
  • 34.
    Chapter 5 DataResource ManagementChapter 5 34 Traditional File Processing  Data are organized, stored, and processed in independent files Each business application designed to use specialized data files containing specific types of data records  Problems Data redundancy Lack of data integration Data dependence (files, storage devices, software) Lack of data integrity or standardization
  • 35.
    Chapter 5 DataResource ManagementChapter 5 35 Traditional File Processing
  • 36.
    Chapter 5 DataResource ManagementChapter 5 36 Database Management Approach  The foundation of modern methods of managing organizational data Consolidates data records formerly in separate files into databases Data can be accessed by many different application programs A database management system (DBMS) is the software interface between users and databases
  • 37.
    Chapter 5 DataResource ManagementChapter 5 37 Database Management Approach
  • 38.
    Chapter 5 DataResource ManagementChapter 5 38 Database Management System  In mainframe and server computer systems, a software package that is used to… Create new databases and database applications Maintain the quality of the data in an organization’s databases Use the databases of an organization to provide the information needed by end users
  • 39.
    Chapter 5 DataResource ManagementChapter 5 39 Common DBMS Software Components  Database definition Language and graphical tools to define entities, relationships, integrity constraints, and authorization rights  Nonprocedural access Language and graphical tools to access data without complicated coding  Application development Graphical tools to develop menus, data entry forms, and reports
  • 40.
    Chapter 5 DataResource ManagementChapter 5 40 Common DBMS Software Components  Procedural language interface Language that combines nonprocedural access with full capabilities of a programming language  Transaction processing Control mechanism prevents interference from simultaneous users and recovers lost data after a failure  Database tuning Tools to monitor, improve database performance
  • 41.
    Chapter 5 DataResource ManagementChapter 5 41 Database Management System  Database Development Defining and organizing the content, relationships, and structure of the data needed to build a database  Database Application Development Using DBMS to create prototypes of queries, forms, reports, Web pages  Database Maintenance Using transaction processing systems and other tools to add, delete, update, and correct data
  • 42.
    Chapter 5 DataResource ManagementChapter 5 42 DBMS Major Functions
  • 43.
    Chapter 5 DataResource ManagementChapter 5 43 Database Interrogation  End users use a DBMS query feature or report generator Response is video display or printed report No programming is required  Query language Immediate response to ad hoc data requests  Report generator Quickly specify a format for information you want to present as a report
  • 44.
    Chapter 5 DataResource ManagementChapter 5 44 Database Interrogation  SQL Queries Structured, international standard query language found in many DBMS packages Query form is SELECT…FROM…WHERE…
  • 45.
    Chapter 5 DataResource ManagementChapter 5 45 Database Interrogation  Boolean Logic Developed by George Boole in the mid-1800s Used to refine searches to specific information Has three logical operators: AND, OR, NOT  Example Cats OR felines AND NOT dogs OR Broadway
  • 46.
    Chapter 5 DataResource ManagementChapter 5 46 Database Interrogation  Graphical and Natural Queries It is difficult to correctly phrase SQL and other database language search queries Most DBMS packages offer easier-to-use, point-and-click methods Translates queries into SQL commands Natural language query statements are similar to conversational English
  • 47.
    Chapter 5 DataResource ManagementChapter 5 47 Graphical Query Wizard
  • 48.
    Chapter 5 DataResource ManagementChapter 5 48 Database Maintenance  Accomplished by transaction processing systems and other applications, with the support of the DBMS Done to reflect new business transactions and other events Updating and correcting data, such as customer addresses
  • 49.
    Chapter 5 DataResource ManagementChapter 5 49 Application Development  Use DBMS software development tools to develop custom application programs Not necessary to develop detailed data- handling procedures using conventional programming languages Can include data manipulation language (DML) statements that call on the DBMS to perform necessary data handling