Managing Data Resources

1
Managing Data Resources
Chapter 7
2
Objectives

• Why do businesses have trouble finding the
  information they need in their information
  systems?
• How does a database management system help
  businesses improve the organization of their
  information?

3
Objectives

• How do the principal types of database models
  affect the way businesses can access and use
  information?
• What are the managerial and organizational
  requirements of a database environment?
• What new tools and technologies can make
  databases more accessible and useful?

4
Management Challenges

• Organizational obstacles to a database
  environment
• Cost/benefit considerations

5
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

6
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

7
Organizing Data in a Traditional File Environment
The data hierarchy
Figure 7-1
8
Organizing Data in a Traditional File Environment
Entities and attributes
Figure 7-2
9
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

10
Organizing Data in a Traditional File Environment
Traditional file processing
Figure 7-3
11
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

12
The Database Approach to Data Management
The contemporary database environment
Figure 7-4
13
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

14
The Database Approach to Data Management
Database Management Systems

• Three Components to a DBMS
• Data definition language Formal language
  programmers use to specify structure of database
• Data manipulation language For extracting data
  from database, e.g. SQL
• Data dictionary Tool for storing, organizing
  definitions of data elements and data
  characteristics

15
The Database Approach to Data Management
Sample data dictionary report
Figure 7-5
16
The Database Approach to Data Management
Database Management Systems

• How a DBMS Solves Problems of a
• Traditional 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

17
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

18
The Database Approach to Data Management
The relational data model
Figure 7-6
19
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

20
The Database Approach to Data Management
The three basic operations of a relational DBMS
Figure 7-7
21
The Database Approach to Data Management
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
  high-volume transactions Banks insurance
  companies
• Examples IBMs IMS

22
The Database Approach to Data Management
A hierarchical database for a human resources
system
Figure 7-8
23
The Database Approach to Data Management
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

24
The Database Approach to Data Management
The network data model
Figure 7-9
25
The Database Approach to Data Management
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

26
The Database Approach to Data Management
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

27
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

28
Creating a Database Environment
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

29
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

30
Creating a Database Environment
An entity-relationship diagram
Figure 7-10
31
Creating a Database Environment
An unnormalized relation for ORDER
Figure 7-11
32
Creating a Database Environment
A normalized relation for ORDER
Figure 7-12
33
Creating a Database Environment
Distributing Databases

• 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

34
Creating a Database Environment
Distributed databases
Figure 7-13
35
Creating a Database Environment
Key organizational elements in the database
environment
Figure 7-14
36
Creating a Database Environment
Management Requirements for Database Systems

• Data Administration
• Develop information policy
• Define information requirements
• Plan for data
• Oversee logical database design and database
  dictionary development
• Monitor use of information

37
Creating a Database Environment
Management Requirements for Database Systems

• Data Planning and Modeling Methodology
• Enterprise-wide planning for data
• Identify key entities, attributes, and
  relationships that constitute the organizations
  data

38
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

39
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

40
Database Trends
Multidimensional data model
Figure 7-15
41
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

42
Database Trends
Components of a data warehouse
Figure 7-16
43
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

44
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?

45
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

46
Database Trends
A hypermedia database
Figure 7-17
47
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

48
Database Trends
Linking internal databases to the Web
Figure 7-18
49
Database Trends
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

50
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?

51
Chapter 7 Case Study
Database Woes Plague Homeland Security and Law
Enforcement

• Briefly summarize why it is important to connect
  much of the data in many of the federal, state,
  and local information systems.
• Describe the major data management problems in
  bringing these data together.
• Describe the management, organization, and
  technology issues that need to be addressed to
  make these data easily available to those who
  need it.

52
Chapter 7 Case Study
Database Woes Plague Homeland Security and Law
Enforcement

• 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.