IT Lecture 4

  1. What is the hierarchy of data in an organization?
    • Database: group of related files
    • File: group of records of the same type
    • Record: group fo related fields
    • Field: grouping of characters into a word, group of words, or a complete number
    • Byte: a string of bits (8) used to store one number or character
    • Bit: a binary digit representing the smallest unit of data
  2. Define entity, attribute, and primary key
    • Entity: Person, place, thing, or event on which we maintain information
    • Attribute: Each characteristic or quality describing the entity
    • Primary Key: unique field that no two entities can share
  3. DBMS
    • Database Management System
    • Integrates databases from different departments
    • Software that allows users to create and maintain a database and enable individual business applications to extract the data that they need
  4. Components of a DBMS
    • Data definition language: formal language programmers use to specify the structure of the database
    • Data manipulation language: used to extract data - SQL
    • Data dictionary: tool for storing, organizing definitions of data elements and data characteristics
  5. Database Approaches: Explain flat file, relational database, hierarchical database, network DBMS, object oriented
    • Flat file: data is in one table - ex. excel
    • Relational database: series of logically related tables or files - standard for organizations
    • Hierarchical database: records are divided in segments that are connected in a parent-child relationship
    • Network DBMS: similar to hierarchical, but parents can have multiple children and children can have multiple parents
    • Object oriented: stores both the data and the procedures acting on the data as objects
  6. Database vs. Data Warehouse
    • Databases: transaction-oriented, support TPS, keep track of the daily activities of the firm
    • Data Warehouses: a logical collection of information, gathered from databases, used to create business intelligence
  7. Data Mining
    Techniques to find hidden patterns and relationships in large pools of data to infer rules for predicting future trends
  8. Define business intelligence and principle BI enablers
    • Information that people use to support their decision-making efforts
    • Technology, people, culture
  9. Four stages managers go through to make a decision
    • 1. Intelligence - collect information
    • 2. Design - determine possible solutions to a problem
    • 3. Choice - select among the various solutions
    • 4. Implementation - put the decision into effect & reports on progress of solution
  10. Why does the decision making process matter to IT?
    Technology projects are business projects and business projects in the digital firm are technology projects
  11. Four steps of a knowledge management system
    • Acquire: data mining, intelligent agent
    • Store: databases
    • Disseminate: intranet, e-mail reports, groupware
    • Apply: DSS, enterprise application
  12. Define an expert system and list three components
    • Human knowledge is collected and built into a system to make a decision
    • Applies reasoning capabilities to reach a conclusion
    • Components: knowledge base (stores rules of the ES), inference engine (takes the problem facts and searches knowledge base for rules that fit), explanation model (explains why the system made the decision)
  13. Intelligent agents
    • Software that assists user or acts on user's behalf
    • Perform repetitive computer related tasks
  14. The duality of information systems: how they constrain and enable
    • Constraints: relying upon the technology restricts the choices of individuals, ex. a DSS
    • Enables: relying on the technology enables individuals to worry about non-routine decisions
  15. How to deal with the duality of IS
    • IS must fit (sociotechnical view) the organization
    • IT department is charged with ensuring the fit
Card Set
IT Lecture 4
IT Lecture 4