1. Data Resource Management
Chapter 5
Data Resource Management
McGraw-Hill/Irwin
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.

2. Learning Objectives
Explain the business value of implementing data resource management processes and technologies in an organization.
Outline the advantages of a database management approach to managing the data resources of a business, compared to a file processing approach.
Explain how database management software helps business professionals and supports the operations and management of a business.

3. Provide examples to illustrate the following concepts
Learning Objectives
Provide examples to illustrate the following concepts
Major types of databases
Data warehouses and data mining
Logical data elements
Fundamental database structures
Database development

4. Logical Data Elements File or table Database
A group of related records
Master file
Transaction file
History file
Archival file
Database
An integrated collection of logically related data elements
World’s largest database?
File or table - A group of related records
Master file - relatively permanent information, such as the names and addresses of customers or suppliers.
Transaction file - routine activity of a business, such as the sale of each product, or the courses that a student took.
History file - obsolete transactions or inactive customers, retained for backup purposes
Archival file - long-term historical storage
Database - An integrated collection of logically related data elements
World’s largest database? – World Wide Web / Internet

5. Common database structures…
Hierarchical
Network
Relational
Object-oriented
Multi-dimensional

6. Most widely used structure
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
Relational - join two or more tables so that he/she can see relevant data in a form that looks like it is in one big table
Example relationships on next slide

7. 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

8. Evaluation of Database Structures
Hierarchical
Works for structured, routine transactions
Can’t handle many-to-many relationships
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

9. Database Administrator (DBA)
Database Development
Database Administrator (DBA)
Enterprise database development
Improves integrity and security
Data Definition Language (DDL)
Data contents, relationships, and structure
Specifications
Data dictionary
Metadata repository
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

10. Contains information on…
Data Dictionary
A data dictionary
Contains data about data (metadata)
Specialized software manages data definitions
Contains information on…
Names, types and descriptions of data
Relationships
Requirements for access and use
Maintenance
Security
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
A data dictionary (metadata repository) is a database management catalog or directory containing
metadata (i.e., data about data). A data dictionary relies on a specialized database software
component to manage a database of data definitions, which is metadata about the
structure, data elements, and other characteristics of an organization’s databases. For
example, it contains the names and descriptions of all types of data records and their
interrelationships; information outlining requirements for end users’ access and use of
application programs; and database maintenance and security.
The database administrator can query data dictionaries to report the status of any
aspect of a firm’s metadata. The administrator can then make changes to the definitions
of selected data elements. Some active (versus passive ) data dictionaries automatically
enforce standard data element definitions whenever end users and application
programs access an organization’s databases. For example, an active data dictionary
would not allow a data entry program to use a nonstandard definition of a customer
record, nor would it allow an employee to enter a name of a customer that exceeded
the defined size of that data element.
Developing a large database of complex

11. Data Planning and Database Design
Database development is top-down process
Develop an enterprise model
Define the information needs of end users
Identify the key data elements
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)

12. Data Resource Management
Managerial activity
Uses data management, data warehousing, and other IS technologies
Manages data for business stakeholders
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

13. Database Interrogation
Boolean Logic
Developed by George Boole
Mid-1800s
Used to refine searches
Three logical operators: AND, OR, NOT
Example
Cats OR felines AND NOT dogs OR Broadway
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

14. Database Maintenance Accomplished by Transaction processing systems
Utilities and other applications, supported by DBMS
Records new business transactions
Updating and correcting data
Customer addresses
The database maintenance process is accomplished by transaction processing systems and other end-user applications, with the support of the DBMS.
End users and information specialists can also employ various utilities provided by a DBMS for database maintenance.
The databases of an organization need to be updated continually to reflect new business transactions (e.g., sales made, products produced, inventory shipped) and other events. Other miscellaneous changes also must be made to update and correct data (e.g., customer or employee name and address changes) to ensure the accuracy of the data in the databases.

15. Application Development
DBMS tools
4GL programming language
Built-in software development tools
Data manipulation language (DML) statements
Eliminate conventional programming
Applications
Data entry screens
Forms
Reports
Web pages