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Managing Data Resources - KU · PDF file• Problem: data used by sales ... and accounting...
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Essentials of Management Information Systems Chapter 7 Managing Data Resources
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Managing Data Resources
Chapter 7
Essentials of Management Information Systems Chapter 7 Managing Data Resources
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• United Asset Coverage (UAC) is a provider of maintenance services for office equipment
• Problem: data used by sales, marketing, customer service, and accounting department were scattered in several isolated information systems
• Solution: E-business suite to organize data based on an enterprise-wide relational database
Case Study
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Objectives
1. Why do businesses have trouble finding the information they need in their information systems?
2. How does a database management system help businesses improve the organization of their information?
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Objectives
3. How do the principal types of database models affect the way businesses can access and use information?
4. What are the managerial and organizational requirements of a database environment?
5. What new tools and technologies can make databases more accessible and useful?
Essentials of Management Information Systems Chapter 7 Managing Data Resources
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Management Challenges
1. Organizational obstacles to a database environment
2. Cost/benefit considerations
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• 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
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• 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
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Organizing Data in a Traditional File Environment
The data hierarchy
Figure 7-1
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Organizing Data in a Traditional File Environment
Entities and attributes
Figure 7-2
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• 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
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Organizing Data in a Traditional File Environment
Traditional file processing
Figure 7-3
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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
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The Database Approach to Data Management
The contemporary database environment
Figure 7-4
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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
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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
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The Database Approach to Data Management
Sample data dictionary report
Figure 7-5
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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
The Database Approach to Data Management
Database Management Systems
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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
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The Database Approach to Data Management
The relational data model
Figure 7-6
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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
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The Database Approach to Data Management
The three basic operations of a relational DBMS
Figure 7-7
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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
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The Database Approach to Data Management
A hierarchical database for a human resources system
Figure 7-8
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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
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The Database Approach to Data Management
The network data model
Figure 7-9
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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
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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
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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
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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
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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
relations (tables) from complex groups of data when designing a relational database
Creating a Database Environment
Designing Databases
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Creating a Database Environment
An entity-relationship diagram
Figure 7-10
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Creating a Database Environment
An unnormalized relation for ORDER
Figure 7-11
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Creating a Database Environment
A normalized relation for ORDER
Figure 7-12
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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
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Creating a Database Environment
Distributed databases
Figure 7-13
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Creating a Database Environment
Key organizational elements in the database environment
Figure 7-14
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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
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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
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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
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Database Trends
Multidimensional data model
Figure 7-15
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• 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
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Database Trends
Components of a data warehouse
Figure 7-16
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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
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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
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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
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Database Trends
A hypermedia database
Figure 7-17
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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 in PHP or CGI scripts
Database Trends
Databases and the Web
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Database Trends
Linking internal databases to the Web
Figure 7-18
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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
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Contemporary Hardware Trends • Cloud Computing:
• A model of computing in which firms and individuals obtain computing resources over the Internet • Cloud infrastructure as a service • Cloud platform as a service • Cloud software as a service
• Public vs. private clouds • Utility computing, on-demand computing • Data storage security is in hands of provider
Databases in the Cloud
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Cloud Computing Platform
In cloud computing, hardware and software capabilities are provided as services over the Internet. Businesses and employees have access to applications and IT infrastructure anywhere at any time using an Internet-connected device.
Databases in the Cloud
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• Cloud computing providers offer database management services, but typically with less functionality
• By moving to a cloud solution, companies are able to scale their computing resources in response to real-time demand while keeping costs low
Databases in the Cloud