7.1

Managing Data Resources

Chapter 7Essentials of Management Information Systems, 6eEssentials of Management Information Systems, 6e

Chapter 7 Managing Data ResourcesChapter 7 Managing Data Resources

© 2005 by Prentice Hall

7.2

Management Challenges

1. Organizational obstacles to a database environment

2. Cost/benefit considerations

7.3

• 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

Organizing Data in a Traditional File Environment

File Organization Terms and Concepts

7.4

• 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

Organizing Data in a Traditional File Environment

File Organization Terms and Concepts

7.5

Organizing Data in a Traditional File Environment

The data hierarchy

Figure 7-1

7.6

Organizing Data in a Traditional File Environment

Entities and attributes

Figure 7-2

7.7

• Data redundancy

• Program-data dependence

• Lack of flexibility

• Poor security

• Lack of data-sharing and availability

Organizing Data in a Traditional File Environment

Problems with the Traditional File Environment

7.8

Organizing Data in a Traditional File Environment

Traditional file processing

Figure 7-3

7.9

Database

• Collection of centralized data

• Controls redundant data

• Data stored so as to appear to users in one location

• Services multiple application

The Database Approach to Data Management

Database Management Systems

7.10

The Database Approach to Data Management

The contemporary database environment

Figure 7-4

7.11

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

The Database Approach to Data Management

Database Management Systems

7.12

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

The Database Approach to Data Management

Database Management Systems

7.13

The Database Approach to Data Management

Sample data dictionary report

Figure 7-5

7.14

How a DBMS Solves Problems of aTraditional File Environment

• 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

The Database Approach to Data Management

Database Management Systems

7.15

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

The Database Approach to Data Management

Types of Databases

7.16

The Database Approach to Data Management

The relational data model

Figure 7-6

7.17

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

The Database Approach to Data Management

Types of Databases

7.18

The Database Approach to Data Management

The three basic operations of a relational DBMS

Figure 7-7

7.19

Hierarchical DBMS

• Older system presenting data in tree-like structure

• Models one-to-many parent-child relationships

• Found in large legacy systems requiring intensive high-volume transactions: Banks; insurance companies

• Examples: IBMs IMS

The Database Approach to Data Management

Types of Databases

7.20

The Database Approach to Data Management

A hierarchical database for a human resources system

Figure 7-8

7.21

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

The Database Approach to Data Management

Types of Databases

7.22

The Database Approach to Data Management

The network data model

Figure 7-9

7.23

Disadvantages of Hierarchical and

Network DBMS

• Outdated

• Less flexible compared to RDBMS

• Lack support for ad-hoc and English language-like queries

The Database Approach to Data Management

Types of Databases

7.24

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

The Database Approach to Data Management

Types of Databases

7.25

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

Creating a Database Environment

Designing Databases

7.26

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

Creating a Database Environment

Designing Databases

7.27

Entity-Relationship DiagramA methodology for documenting databases that illustrates the relationship between various elements in the database

NormalizationThe process of creating small, stable, and adaptive data structures from complex groups of data when designing a relational database

Creating a Database Environment

Designing Databases

7.28

Creating a Database Environment

An entity-relationship diagram

Figure 7-10

7.29

Creating a Database Environment

An unnormalized relation for ORDER

Figure 7-11

7.30

Creating a Database Environment

A normalized relation for ORDER

Figure 7-12

7.31

Distributed Database

• 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

Creating a Database Environment

Distributing Databases

7.32

Creating a Database Environment

Distributed databases

Figure 7-13

7.33

Creating a Database Environment

Key organizational elements in the database environment

Figure 7-14

7.34

Data Administration

• Develop information policy• Define information requirements• Plan for data• Oversee logical database design and database

dictionary development• Monitor use of information

Creating a Database Environment

Management Requirements for Database Systems

7.35

Data Planning and Modeling Methodology

• Enterprise-wide planning for data• Identify key entities, attributes, and relationships

that constitute the organization’s data

Creating a Database Environment

Management Requirements for Database Systems

7.36

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

Creating a Database Environment

Management Requirements for Database Systems

7.37

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

Database Trends

Multidimensional Data Analysis

7.38

Database Trends

Multidimensional data model

Figure 7-15

7.39

• 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

Database Trends

Data Warehouses and Datamining

7.40

Database Trends

Components of a data warehouse

Figure 7-16

7.41

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

Database Trends

Data Warehouses and Datamining

7.42

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?

Database Trends

Window on Management

7.43

Hypermedia database

• Organizes data as network of nodes

• Links nodes in pattern specified by user

• Supports text, graphic, sound, video and executable programs

Database Trends

Data Warehouses and Datamining

7.44

Database Trends

A hypermedia database

Figure 7-17

7.45

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

Database Trends

Databases and the Web

7.46

Database Trends

Linking internal databases to the Web

Figure 7-18

7.47

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

Database Trends

Databases and the Web

7.48

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?

Database Trends

Window on Technology