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Information Systems and
      Management
       Valuing Organizational
            Information
• Transactional Information
  – Contained within a business process
  – Supports performing daily operations

• Analytical Information
  – Includes transactional information plus market and
    industry information

• The Value of Timely Information
  – Real Time: Immediate, up-to-date
  – Within the Decision Makers Time frame
Characteristics of High-
  Quality Information

    •   Accuracy
    •   Completeness
    •   Consistency
    •   Uniqueness
    •   Timeliness
         The Cost of Low-Quality
              Information

• Using the wrong information can
  lead to making the wrong
  decision

• The wrong decision can cost
  time, money, and even
  reputations
The Benefits Of High-Quality
       Information

• Improve chances of making a
  good decision which, in turn,
  may directly affect the
  organizations bottom line
   Data Resource Management
Data Planning
• Develop an overall data and architecture
  for the firm’s data resources that ties in
  with the firm’s strategic mission and plans,
  and the objectives and processes of it’s
  business units.

Data Administration
• Involves the establishment and
  enforcement of policies and procedures
  for managing data as a strategic corporate
  resource.
 Cross-Functional Information Systems
• Support business processes
   • Production
   • Distribution
   • Order management

• Cross boundaries of Traditional business
  functions.

• IT helps by supporting the re-engineering and
  improvement of business processes.

• A strategic way to use IT to share information
  resources and improve both efficiency and
  effectiveness of business processes to help a
  business attain it’s strategic objectives.
Enterprise Resource Planning

• Replace functional mainframe legacy
  systems with cross-functional client/server
  network applications.

• SAP and others
     Database Structures
• Hierarchical
  • One-to-many (Tree like)

• Network
  – Many-to-many

• Relational
  – Elements reside in two dimensional interlinked tables

• Multidimensional
  – Cubes of data

• Object Oriented
  – Encapsulation: data and operations are stored together
    Entity Relationship Diagram
               (ERD)
•   Tool Used In Data Modeling
•   Depicts relationships between entities
•   Entity: a category of stored data
•   Relationship: how entities are associated
•   Attributes: descriptive components of an
    entity

• An ERD model can be easily translated
  into virtually any type of physical data
  base implementation
Entity Relationship Diagram
          Customer



           Order




            Item
           Rules Of Thumb

• 1:1 : One Table

• 1:M :primary key from one side used as a
  foreign key in the many side

• M:M : New table with a primary key which
  is a combination of both the other primary
  keys.
                       Rules Of Thumb

Bit
Byte ≡ Character
       Field     ≡     Data Element ≡   Attributes
       Record    ≡     Data Structure
                                        Entity   ≡ Table
        File       ≡   Database           ≡        Relational
                                                    Database
•   Primary Key
•   Secondary Key (or Foreign Key)
•   Referential Integrity
•   Normalization
            Normalization

• A method of simplifying complex data
  structures
• A process of assigning attributes to
  entities
• Determine how to traverse a relational
  database by identifying primary keys and
  foreign keys
   Referential Integrity



The Primary key data must exist
before data can be entered in
the table where the primary key
is used as a Foreign key.
               Normalization
First Normal Form (1NF)
  • An entity is in 1NF if there are no elements, or
    group of elements, which repeat for a single
    occurrence of the entity.
Second Normal Form (2NF)
  • An entity is in 2NF if it is in 1NF and if the full
    key and not part of it derive all non-key
    elements
Third Normal Form (3NF)
  • An entity is in 3NF if it is in 2NF and if the
    values for the non-key elements are not
    dependent on any other non-key elements.
          ERD Example


Faculty           Department



Course




Student
                      U of L Database
                                                             Calendar
       HR
                                      Course
              Faculty                 •Course # (K)
              •Fac. # (K)
                                      •Course Name
              •Name
                                      •Course Description
              •Address
                                      •Faculty # (k)
              •Dept # (k)

                            Phone                           Registration
                            Book         Course #
                                         Student #
      Department                                             To Grading
                                         Mark                  System
      •Dept. # (K)
      •Dept. Name
      •Dept. Description            Student
                                    •Student # (K)            Admissions
                                    •Student Name
Organizational                      •Student Address
    Chart
              Organizing Data
• Data is processed into information which
  in turn supports decision making

• Database Management System (DBMS)
  – User/database interface
• Database Administrator (DBA)
  – IT professional responsible for all aspects of the
    database
              Data Management
• For data to be turned into information it must first be
  organized in a meaningful way


• Traditional approach
    – Data redundancy: duplication of data in separate files
    – Data integrity: the degree to which data is correct


• Database approach
    – A pool of related data is shared by mulitple application
      programs
               Data Modeling
• Key Considerations:
  • What data will be collected
  • Who will have access to it
  • How the data will be used


• Data Model
  • A diagram of data entities and their
    relationships
             Data Modeling
• Enterprise Data Modeling
  • Data modeling done at the enterprise level

• Entity Relationship Diagram (ERD)
  • Use basic graphic symbols
  • Show the organization and relationships
    between data

• Planned Data Redundancy
  • Summary totals carried in data
  • To improve system performance
  • Data Marts in ERP systems
 The Relational Database Model


• Relational Model:
  • A database model that describes data
    in which all data elements are placed in
    two dimensional tables
  • The tables are the logical equivalent to
    files
  • Domain: Allowable values for data
    attributes
       Data Clean-up
• The process of looking for and
  fixing inconsistencies to ensure
  that data are accurate and
  complete
Overview of Database Types
 • Flat file
   – Sequential or direct
   – Does not use database concepts

 • Single User
   – One person can use the database at a time
     (Access)

 • Multiple Users
   – Large DBMS (Oracle)
       Providing a User View

• Schema:
  • a description of the entire database

• Sub schema:
  • a description of a subset of the
    database
  • Users can view and modify data terms
    in the subset
   Creating and Modifying the
            Database


• Data Definition Language (DDL)
  • Commands used to describe data and their
    relationships


• Data Dictionary
  • Detailed descriptions of all data in the
    database
   Storing and Retrieving Data

• The system must calculate the physical
  location based upon logical application of
  data

• Concurrency Control
  • A method of dealing with two people
    accessing the same record, in the same
    database, at the same time
       Manipulating Data and
        Generating Reports

• Query-by-example (QBE)
  – Point and click, drag and drop


• Data Manipulation Language (DML)
  – Commands used to manipulate data in a database
  – Structured Query Language (SQL)
         Selecting a Database
         Management System
• Determine information needs of the
  organization
• Considerations
  •   Size (current and future)
  •   Number of Concurrent Users
  •   Performance (response time)
  •   Integration (relation to other applications)
  •   Features (security, privacy, templates)
  •   The Vendor (service, reputation, viability)
  •   Cost
• Data Warehouse:
  • A database that collects business
    information from many sources in the
    enterprise, covering all aspects of the
    company’s processes, products, and
    customers

• Data Mart:
  • Subset of a data warehouse
                    Data Mining

• An information analysis tool that
  involves the automated discovery of
  patterns and relationships in a data
  warehouse

• Predictive Analysis
  • Combines historical data with
    assumptions about future conditions
  • Used to predict outcome of events
       Business Intelligence
• The process of gathering enough of the
  right information in a timely manner and
  usable form and analyzing it to have a
  positive impact on business strategy,
  tactics, or operations
• Competitive Intelligence
• Counter Intelligence
• Knowledge Management
   More Business Intelligence
• Competitive Intelligence
  – One aspect of business intelligence limited to
    information about competitors
• Counter Intelligence
  – The steps an organization takes to protect information
    sought by “hostile” intelligence gathers


• Knowledge Management
  – The process of capturing a company’s collective
    expertise wherever it resides – in computers, on paper,
    in people’s heads – and distributing it wherever it can
    help produce bigger payoffs
       Distributed Databases

• A database in which the data may spread
  across several smaller databases
  connected via telecommunication devices

• Replicated Database
  – A database that holds a duplicate set of
    data
 Online Analytical Processing
           (OLAP)


• Software that allows users
  to explore data from a
  number or different
  perspectives
            Object-Oriented
• Object-Oriented Database
  • Database that stores both data and its
    processing instructions together
  • Encapsulation

				
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