AIS Definitions

  1. Database
    • A set of interrelated, centrally coordinated
    • files.
  2. Database management system DBMS
    • Is the interface between a database and the
    • various application programs.
  3. Database administrator DBA
    Is responsible for the database
  4. Data warehouse·
    Contains both detailed and summarized data for anumber of years and is used for analysis rather than transaction processing.
  5. Business intelligence·
    Using a data warehouse for strategicdecision-making.
  6. Online analytical processing OLAP·
    Is using queries to guide the investigation of hypothesized relationships in data.
  7. Data mining
    Is using sophisticated statistical analysis, including artificial intelligence techniques such as neural networks, to “discover” hypothesized relationships in the data. Credit card companies looking at trends to detect fraud.
  8. Record layout
    In file-oriented systems, programmers must know the physical location and layout of records.
  9. Logical view
    Is how people conceptually organize and understand the data.
  10. Physical view
    Refers to how and where data are physical arranged and stored in the computer system.
  11. Schema
    Describes the logical structure of the database.
  12. Conceptual-level schema
    The organization wide view of the entiredatabase, list of all data elements and the relationships among them.
  13. External-level schema·
    Consist of individual user views of portions of the database.
  14. Subschema·
    portions of the database.
  15. Internal-level schema·
    A low-level view of the database, describes how the data are stored and accessed, including record layouts, definitions,addresses, and indexes.
  16. Data dictionary·
    Contains information about the structure of the database.
  17. Data definition language DDL·
    Builds the data dictionary, crease the database,describes logical views for each user, and specific records or field securityconstraints.
  18. Data manipulation language DML·
    Changes the database content, including dataelement updates, and deletions.
  19. Data query language DQL·
    Contains powerful, easy-to-use commands that enable users to retrieve, sort, order, and display data.
  20. Report writer·
    Simplifies report creation. Prints out the userspecified data.
  21. Data model·
    The abstract representation of database of database contents, upon which the database is based.
  22. Relational data model·
    Represents conceptual-and-external-level schemasas if data are stored in tables. Data are actually stored not in tables, but in the manner described in the internal-level schema.
  23. Tuple·
    The rows in a table
  24. Primary key·
    Is the database attribute, or combination of attributes, that uniquely identifies a specific row in a table.
  25. Foreign key·
    • Is an attribute that is a primary key in anothertable that is
    • used to link tables.
  26. Update anomaly·
    A problem that occurs when data is stored in onetable. This is when data value updates are not correctly recorded. updating one record does not automatically update the rest.
  27. Insert anomaly·
    When there is no way to enter a customer before they actually buy something.
  28. Entity integrity rule·
    A primary key cannot uniquely identify a row in a table if it is null. A non-null primary key ensures that every row in a tablerepresents something that can be identified.
  29. Referential integrity rule·
    Ensures database consistency, by linking tablestogether.
  30. Semantic data modeling·
    An alternative to normalization, the designer uses knowledge of business processes and information needs to create a diagram thatshows what to include in a database. The diagram shows the user how to put the tables in 3NF.
  31. advantages of database systems
    data integration, data sharing, minimal redundancy, data independence, cross-functional analysis
Card Set
AIS Definitions
Chapter 4