Data Information Knowledge

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Data - Information - Knowledge

• Data - Raw Facts
• Information - Facts organized in a meaningful and
  useful fashion so as to have additional value
  beyond the value of the facts themselves.
• Knowledge - An awareness and understanding of
  information and how that information can be put
  to best use.

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Characteristics of Valuable Information

• Accurate - Error free
• Complete - All important facts included
• Economical - Cost effective to produce
• Flexible - Usable for a variety of purposes
• Reliable - Can be depended on
• Relevant - Applicable to users purpose
• Simple - Only the facts that are needed

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Characteristics of Valuable Information (Cont.)

• Timely - Delivered when it is most useful
• Verifiable - Can be checked for correctness
• Reusable - Using information does not preclude
  using it again

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Information Value Chain
Data
Transformation Process
Information
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Data
Transformation Process
Information
Dissemination Process
Retention Process
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Information Resource Management

• Resources can be internal or external to the
  organization.
• Resources can be physical or conceptual.
• As the scale of the enterprise grows, it becomes
  more difficult to manage the resources.

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• The principles developed to manage physical
  resources can be applied to conceptual resources.
• Management of conceptual resources requires
  processes and policies for aquisition, security,
  quality control, disbursement and obsolescence.
• Organizational commitment is required for
  successful management of conceptual resources.

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• INFORMATION SYSTEM Hardware, software and
  procedures that maintain data and convert it into
  usable information.

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Components of a Computer Based Information System
Communications
Hardware
I S
Software
Procedures
Databases
People
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Functions of an Information System

• Collect
• Process
• Store
• Retrieve
• Analyze
• Disseminate

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Hierarchy of Data
Bit (Binary 1or 0) Byte (Character) Field
(Attribute or Column) Record (Tuple or
Row) File (Table or Relation) Database
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Database
A self describing collection of logically
related data, organized to meet the information
needs of multiple users.
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Database Management System (DBMS)
An integrated set of programs that facillitate
the creation,access and management of databases.
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Data Organization

• Files
• Data organized into file structures that are
  typically application specific and described by
  data descriptions in programs
• Databases
• Data organized into structures that are shared
  and store most of the meta-data with the data
  itself.

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Database vs File Systems
FILE SYSTEM
Program 1
Meta-Data
Data
Program 2
Meta-Data
Program 3
Meta-Data
DATABASE
Program 1
Meta- Data
Data
Program 2
Program 3
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FILE BASED SYSTEMS
Advantages Disadvantages

• Conceptual Simplicity
• Easy Backupand Recovery
• Fast Batch Processing

• Separated and Isolated Data
• Data Duplication
• Application Dependent
• Difficult To Represent User View

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DBMS BASED SYSTEMS
Advantages Disadvantages

• Integrated Data
• Reduced Data Redundancy
• Application Independence
• Easier Representation of User View

• Processing Overhead
• DBMS Cost
• Requires specialized IS Roles
• Data Contention
• Organizational Conflict

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How Databases And DBMS Add Value

• Accuracy - DBMS can enforce format rules on data
  entered.
• Flexible - Data can easily be pulled together in
  a variety of fashions from different tables or
  files.
• Economical - Information can be accessed without
  the cost of writing new programs.

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• Reliable - Modern DBMS designed for mission
  critical application usage.
• Relevant- Data within tables or databases that is
  or can be viewed is tailored to specific users or
  applications.
• Simple - Entire table or record does not need to
  be retrieved to access one field.
• Timely - Once data is entered to the system it is
  immediately available.

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• Verifiable - Reduced data redundancy increases
  the ease with which data can be verified.
• Reusable - Files are not constantly created and
  deleted in order to extract relevant data.

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Models

• Models are an abstract representation of the way
  we perceive a system or process.
• This abstraction allows us to make predictions
  concerning the results of changes to various
  components or conditions that are included in the
  model.

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Goals of Data Modeling

• We are seeking to describe the data structures
  and relationships that are required to support
  the users business model.The business model is
  the abstract description of the rules and
  processes by which the organization creates value.

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Data Models

• Conceptual Model
• A description of the data requirements of a
  system that is independent of the way it will be
  stored and accessed
• Physical Model
• A description of the data and relationships that
  takes into account the requirements of the
  database organization

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Enterprise Modeling
Analysis of current databases and file
processing. High level analysis of data needs
of the supported business functions. Project
planning
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Conceptual Data Modeling
Overall data analysis of the supported business
functions. Develop preliminary conceptual
data model.
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File based processing systems were traditionally
developed by specifying the program functions
then designing the files to conform to the
program.
Data models that are based on a description of
program functions tend to put attributes
together based on how they are used. This gives
a less flexible and more volatile model than
models based on the entities in the system.
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Logical Database Design
Detailed analysis of the business function data
requirements. Normalization Integrate views
into the conceptual model. Design screens,
reports, applications. Identify security
requirements.
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Physical Database Design
Define the database to the DBMS. Decide on
physical organization of data. Design programs.
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Database Implementation
Code and test programs. Complete
documentation. Install and perform any
conversions. Train users.
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Database Maintenance
Performance tuning. Error correction. Running
updates.