Information and Knowledge Concepts Quiz

Introduction

• This presentation covers the management of data, information, and knowledge.
• The presenter is Emmanuel.
• Contact email: [email protected]

Topic Outline

• Data, information, and knowledge.
• Data, information, knowledge MIS focus.
• Technology for managing data/information.
• Newer database developments.
• Managing information-life cycle metaphor.
• Technology for information management.

Data, Information, and Knowledge Relationship

• Data: raw, unorganized facts (low level)
  • Size, complexity, management cost define raw data characteristics.
• Information: data with meaning (mid level)
  • Information transforms data from unorganized facts into meaningful data
  • Context is crucial for data interpretation.
• Knowledge: interpreted and organized information (high level)
  • Knowledge builds on information to develop perspectives and understanding.

Data

• Representation of facts.
• Collection of symbols (text, visual, audio), may or may not have meaning.
• Essentially, raw material used to create information.
• Meaning arises from context.
• Examples include sales records with last name, sales, product type, and company, client requests to the server.

Information

• Data given context.
• Data in context to build meaning.
• It is meaningful information in the context of data in other contexts
• Examples: "Juan is my friend", "a client device sent requests to the server, database record."

Knowledge

• Interconnected information with meaning and purpose.
• Understands the significance of information.
• Guides effective action and decision making.
• Recognition of patterns and trends based on information and experience.
• Involves multiple data points, information, and experience.
• Example: The surgeon's knowledge of anatomy and methodology guide surgery.

Information Resources

• More vs. Less Structured Information (Records vs. Documents):

  • Documents are planned and can be revised.
  • Records document events and don't change.

• Hypertext-Based Structures:

  • Hypertext systems are non-linear.
  • Linking content pieces is a major component
  • Information can be retrieved via indexes, similar to dictionaries.

• Data about data (Metadata):

  • Meta-data describes another data.
  • Metadata summarizes essential information that makes finding particular data entries simpler and faster.

Managing Information-Life Cycle Metaphor

• Information life cycle traces value changes over time.
• Value is highest when data is created and used frequently.
• Value decreases as data ages and is used less often.
• Appropriate storage infrastructure should adjust to the changing value of information.

Technology for Managing Data/Information

• DBMS Models:
  • Hierarchical, network, relational, and object models.
  • Database Models (logical structure) are models that structure data in a database.
  • These models dictate how structured data will be stored, accessed, and updated.
• Hierarchical Models:
  • Organizes data in a tree-like structure, with one root node to connect all other related information.
• Network Models:
  • Follows the hierarchical format of a tree in the form of a graph.
• Entity Relationship Model:
  • Groups related data elements in groups called entities.
  • These entities use attributes, such as name, address, to connect related data.
• Relational Model:
  • Data organized in tables (rows and columns)
  • Tables' relationships depend on common, related-field attributes.
• Example: A database that handles data about students in a college setting. Several student entities form the database, categorized by attribute such as name, id, age, or address.

Newer Database Developments

• Data Warehousing:
  • Combines data from various sources to support analytical reporting in data processing.
• Data Mining:
  • Uses software to discover patterns in large quantities of data for business decision making.
• Online Analytical Processing (OLAP):
  • Enables complex data analysis, reports, and predictive scenarios.

Assignment #1

• Define data and information management.