Chapter 3
Data Resource Management
Learning Objectives
 Explain the importance of implementing data resource management
processes and technologies in an organization.
 Understand the advantages of a database management approach to
managing the data resources of a business.
 Explain how database management software helps business
professionals and supports the operations and management of a
business.
 Illustrate each of the following concepts:
 Major types of databases
 Data warehouses and data mining
 Logical data elements
 Fundamental database structures
 Database access methods
 Database development
Section I
Managing Data Resources
Data Resource Management
 A managerial activity
 Applies information systems technology to managing data resources
to meet needs of business stakeholders.
Foundation Data Concepts
 Levels of data
 Character
 Single alphabetical, numeric, or other symbol
 Field
 Groupings of characters
 Represents an attribute of some entity
 Records
 Related fields of data
 Collection of attributes that describe an entity
 Fixed-length or variable-length
 Files (table)
 A group of related records
 Classified by
 Primary use
 Type of data
 permanence
 Database
 Integrated collection of logically related data elements
 Consolidates records into a common pool of data
elements
 Data is independent of the application program using
them and type of storage device
Logical Data Elements
Types of Databases
 Operational
 Supports business processes and operations
 Also called subject-area databases, transaction databases,
and production databases
 Distributed
 Replicated and distributed copies or parts of databases on
network servers at a variety of sites.
 Done to improve database performance and security
 External
 Available for a fee from commercial sources or with or without
charge on the Internet or World Wide Web
 Hypermedia
 Hyperlinked pages of multimedia
Data Warehouses and Data Mining
 Data warehouse
 Stores data extracted from operational, external, or other
databases of an organization
 Central source of “structured” data
 May be subdivided into data marts
 Data mining
 A major use of data warehouse databases
 Data is analyzed to reveal hidden correlations, patterns, and
trends
Database Management Approach
 Consolidates data records and objects into databases that can be
accessed by many different application programs
 Database Management System
 Software interface between users and databases
 Controls creation, maintenance, and use of the database
 Database Interrogation
 Query
 Supports ad hoc requests
 Tells the software how you want to organize the data
 SQL queries
 Graphical (GUI) & natural queries
 Report Generator
 Turns results of query into a useable report
 Database Maintenance
 Updating and correcting data
 Application Development
 Data manipulation language
 Data entry screens, forms, reports, or web pages
Implementing Data Resource Management
 Database Administration
 Develop and maintain the data dictionary
 Design and monitor performance of databases
 Enforce database use and security standards
 Data Planning
 Corporate planning and analysis function
 Developing the overall data architecture
 Data Administration
 Standardize collection, storage, and dissemination of data to
end users
 Focused on supporting business processes and strategic
business objectives
 May include developing policy and setting standards
 Challenges
 Technologically complex
 Vast amounts of data
 Vulnerability to fraud, errors, and failures
Section II
Technical Foundations of Database Management
Database Structures
 Hierarchical
 Treelike
 One-to-many relationship
 Used for structured, routine types of transaction processing
 Network
 More complex
 Many-to-many relationship
 More flexible but doesn’t support ad hoc requests well
 Relational
 Data elements stored in simple tables
 Can link data elements from various tables
 Very supportive of ad hoc requests but slower at processing
large amounts of data than hierarchical or network models
 Multi-Dimensional
 A variation of the relational model
 Cubes of data and cubes within cubes
 Popular for online analytical processing (OLAP) applications
 Object-oriented
 Key technology of multimedia web-based applications
 Good for complex, high-volume applications
Accessing Databases
 Key fields (primary key)
 A field unique to each record so it can be distinguished from
all other records in a table
 Sequential access
 Data is stored and accessed in a sequence according to a key
field
 Good for periodic processing of a large volume of data, but
updating with new transactions can be troublesome
 Direct access
 Methods
 Key transformation
 Index
 Indexed sequential access
Database Development
 Data dictionary
 Directory containing metadata (data about data)
 Structure
 Data elements
 Interrelationships
 Information regarding access and use
 Maintenance & security issues
 Data Planning & Database Design
 Planning & Design Process
 Enterprise model
 Entity relationship diagrams (ERDs)
 Data modeling
 Develop logical framework for the physical design