Management Information Systems, 3rd Edition

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Chapter 8Data and Knowledge Management
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Learning Objectives

• When you finish this chapter, you will
• Know the difference between traditional file
  organization methods and the database approach.
• Know how database management systems are used to
  construct databases, populate them with data, and
  manipulate the data to produce information.
• Be familiar with the different database models
  and the advantages and disadvantages of each
  model.

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Learning Objectives

• Know the most important features and operations
  of a relational database.
• Understand how databases are changing business
  operations across industries and what impact they
  might have on our personal lives.
• Understand the concepts of data warehousing and
  data-mining and their use in business.
• Recognize the need for knowledge storage and
  management and be able to give examples of the
  ways knowledge is managed in organizations.

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Managing Digital Data

• The Traditional File Approach
• Disadvantages
• Program/Data Dependency
• Data Redundancy
• Data Integrity

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Managing Digital Data
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Managing Digital Data
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Managing Digital Data

• Moving to Databases
• Maintain and manipulate data about entities
• Entity any object chosen to collect data about
• Field one piece of information about entity
• Fields can hold text, numbers, pictures, sounds
  and video clips
• Record several fields related to same entity
• File collection of related records

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Managing Digital Data
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Managing Digital Data

• Database Management System (DBMS)
• The program used to build databases, populate
  them with data, and manipulate the data
• Queries Request data from specified fields
• Security Giving users different views addresses
  security issue

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Managing Digital Data
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Managing Digital Data
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Managing Digital Data

• Traditional Files vs. Databases Pros and Cons

• Traditional File Advantages
• Simplicity
• Efficiency
• Customization
• Traditional File Disadvantage
• Creates data redundancy and application-data
  dependence
• Does not support as tight control over data
  currency, accuracy, and integrity as database
  approach
• Provides less flexibility in data maintenance

• Database Advantages
• Reduced data redundancy
• Application/data independence
• Better control
• Flexibility

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Database Models
Database model general logical structure which
stores records within a database.
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Database Models

• The Hierarchical Model
• Records are related hierarchically -- each
  category is a subcategory of the next level up
• Disadvantages of hierarchical databases
• To retrieve a record, a user must start at the
  root and navigate the hierarchy.
• If a link is broken, the entire branch is lost.
• Requires considerable data redundancy

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Database Models

• The Network Model
• Allows a record to be linked to more than one
  parent
• Supports many-to-many (NM) relationships
• Advantage of the network model
• Reduced data redundancy
• Disadvantages of the network model
• Complicated to build and difficult to maintain
• Difficult to navigate

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Database Models

• The Relational Model
• Consists of tables links among entities are
  maintained with foreign keys
• Advantages of relational databases
• Same advantages of a network database without the
  complications
• Easier to conceptualize and maintain
• Virtually all DBMSs offered for microcomputers
  accommodate the relational model

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Database Models

• Keys
• A field whose values identify records
• Either for display or for processing
• Primary Key
• Unique key
• Linking
• To link records from one table with records of
  another table, the table must have one field in
  common
• Repeated field a primary key in one table and a
  foreign key field in another table

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Database Models

• The Object-Oriented Structure
• Affords maintenance of data along with the
  applications that process them
• Entity-Relationship Diagrams
• Conceptual (logical) blueprint of a database
• Graphical representation of all entity
  relationships

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Database Models
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Components of Database Management Systems

• The Schema
• Describes the structure of the database
• Types of Data fields can hold
• Building a Database
• The Data Dictionary (Metadata)
• Maintains all information supplied by the
  developer when constructing the schema

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Components of Database Management Systems
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Components of Database Management Systems

• Data Definition Language (DDL)
• Used to construct the schema

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Components of Database Management Systems

• Data Manipulation Language (DML)
• Used to query the database

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Relational Operations

• Data Manipulation
• Select, Project, Join

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Relational Operations
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Relational Operations

• Structured Query Language (SQL)
• International standard DDL and DML for relational
  DBMS
• Advantages of using SQL
• Users do not need to learn different DDLs and
  DMLs.
• SQL can be embedded in widely used 3rd generation
  languages, increasing efficiency and
  effectiveness.
• Programmer not forced to rewrite statements since
  SQL statements are portable.

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Popular Database Management Systems
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Database Architecture

• Database Architecture refers to both the physical
  and logical layouts
• Distributed Databases (geographically remote
  sites)
• Replication
• Full copy of the entire database is stored at all
  sites
• Fragmentation
• Parts of database are stored where they are most
  often accessed

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Database Architecture
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Database Architecture
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Database Architecture

• Shared Resource and Client/Server Systems
• Four basic client/server models
• Applications run at a server
• Applications run on local PCs
• Applications run on both the local PCs and the
  server
• Applications and key elements of the database are
  split between the PCs and the server

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Database Architecture
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Web Databases

• Databases on the Web
• Catalogs
• Libraries
• Directories
• Client lists and profiles
• Points to consider (when linking a database to
  the Internet)
• Which application to use
• How to ensure Web surfers do not interfere with
  database updates
• How to maintain security

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Data Warehousing

• Data warehouse
• Collection of data that supports management
  decision making
• From Database to Data Warehouse
• Hardware
• Data and Software
• Phases in Building a Data Warehouse
• Extraction Phase
• Cleansing Phase
• Loading Phase

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Data Warehousing
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Data Mining

• Selecting, exploring, and modeling data to
  discover unknown relationships

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Data-Mining
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Knowledge Management

• Where to find information
• Gathering, organizing, sharing, analyzing and
  disseminating knowledge to improve an
  organizations performance
• Transfer knowledge into databases
• Filter and separate the most relevant knowledge
• Organize knowledge in databases that either
• Allow other employees to easily access the
  knowledge
• Push specific knowledge to employees based on
  their prespecified needs

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Ethical and Societal IssuesA Too-Risky Info
Highway

• Out of Hand -- Out of Control
• DBMSs allow organizations to collect, maintain,
  and sell vast amounts of private personal data
  easily.
• The Web A Source of Data Collection
• Many consumers provide information daily without
  being aware of it.

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Ethical and Societal IssuesA Too-Risky Info
Highway

• Our Finances Exposed
• Companies sharing private financial information
  with other organizations.
• The Upside
• Database technology enables better and faster
  services.
• Makes markets more competitive.