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Chapter 7 – Accessing Organizational Data

  1. Managing Organizational Data
    • Problems with Separate Files and File Ownership
      • Separated and Isolated Data
      • Data Duplication - data integrity
      • Application Program Dependency on Data (e.g. Year 2000 crisis)
      • Incompatible Files
      • The Difficulty of Representing Data in Users' Perspective (not natural)
    • The Database Solution

      Definition of a Database

      bits -> bytes(characters) -> fields -> records -> files -> database
      A database is a self-describing collection of integrated records
      • A Database is Self-Describing - description is in a data dictionary
      • A Database is a Collection of Integerated Records - uses indexes
      • A Database is a Model of a Model (model of the users' model = views)

      • Integrated Data - database
      • Reduced Data Duplication
      • Program/Data Independence
      • Easier Representation of the Users' Perspective

      • requires a database administrator
      • database management system (DBMS) - software that manages & creates the databases
      • data manipuation language (DML) - uses to program the DBMS
      • database query language - used to formulate queries and reports
      • data definition language (DDL) - used to define the structure and schema of the database

    • Enterprise Databases - requires a centralized enterprise-wide database

    • Client/Server Databases - allocates data to a database server and assigns local responsibility for its maintenance and integrity [database appears local to the user]
    • Data Warehousing - database created specifically for retrieval by knowledge workers

  2. Review of Data Concepts
    • Entities, Attributes, and Relationships
      • entity (entity class) - type or category of objects about which data is collected
      • entity instance - individual instance within the category
      • attribute - characteristic of interest about an entity (field)
      • identifier (key) - attribute that distinguishes one entity instance from another
      • relationship - correspondence or association between entities
      • degree of a relationship is determined by the largest # of instances on each end of the relationship

    • Relating Entity Terminology to Files, Records, and Data Items

    • Data Names - ex. CUSTOMERID

    • Data Types - integer, real, string, date [each data item has a domain]

    • Data Structures
      • E-R Diagram
      • Data Structure Diagram
      • Semantic Object Diagram
      • Algebraic Data Description

    • Data Order (collating sequences: ASCII, EBCDIC)

  3. Relational Databases Maintained by the Organization
    need to develop tables for querying and reports
    • Identifying the Tables of Interest - select tables; include
      • names and types of attributes (include meanings)
      • identify which attributes are keys and foreign keys
      • determine the domains of each attribute
      • describe constraints on the data

    • Formatting the Output or Report
      1. data for use in spreadsheet analysis
      2. data for use as part of a document
      3. report output
    • Determining Selection and Ordering Criteria
    • Forming and Executing a Database Query (SQL - Structured Query Language vs. QBE - Query By Example)
      ex. SELECT CUSTOMER-NAME, ORDER-NO, AMOUNT
        FROM ORDERS
        ORDER BY AMOUNT DESCENDING
        WHERE AMOUNT > 1000 AND MONTH = CURRENT-MONTH

    • Validating Query Results
      1. estimate the number of records to be retrieved prior to the query operation
      2. inspect or print a sample from each of the tables being used in order to review your understanding of the tables and their values
      3. make rough estimates for any calculations such as totals that will result from your queries
      4. compare your results with previous queries or with estimates by others in your workgroup
      5. do a complex query by starting with the simplest part and adding query elements one by one
      6. sort results so as to highlight possible errors or omissions
      7. perform a second query using independently formulated conditions to verify that the WHERE clause and other parts of the expression have been processed as expected
      8. consider a complementary selection (or at least a count)

  4. Online Analytical Processing (OLAP) - multidimensional analysis combining analytic and retrieval software

  5. Constraints on Accessing Organizational Databases (who has priviliges; views into the database; snapshots of data)

  6. Knowledge Work Productivity in Accessing Organizational Data
    • Efficient Use of Data Access Software - should include a GUI, easy to learn, and help facilities
    • Obtaining Data for Direct Use - should have a GUI for designing queries and reports
    • Obtaining Data for Spreadsheet Analysis
    • Obtaining Data for Word Processing Documents (RFT)

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