ITGS HL

ITGS Textbook: Chapter 7 (Databases) Summary/Review/Study Guide

Databases

  • a collection of information that has been organized in a certain way or a storage container for data
  • Organized collection of collected data (ex: Privacy Issue)

Databases: Business database, transport databases, search engines, online databases, government databases

Database Management System

  • DBMS:
    • Software used to create, enter, edit and retrieve data in a database
    • RDBMS: Relational DBMS- allows tables to relate to each other
    • Does NOT include spreadsheet

Database Structure

  1. Fields: smallest pieces of information; property of an item
  2. Records: Collection of related fields
  3. Tables: Collection of related records

Primary and Composite Key

  1. Primary:
  • Each table likely has a primary key (key field)
  • Enables unique identification
  1. Composite:
  • Utilized when a primary key is insufficient
  • Two or more fields
  • Combination is essential

Secondary Keys

  • AKA alternative keys
  • A field frequently used to search a table

Data Type

  • Each field needs a data type
    • Example: Number, Autonumber, Text, Memo, Attachment

 

Terms:

  • Redundancy: data in a database which is needlessly duplicated
  • Data Integrity: ensuring data is correct, consistent, up to date
  • Validation: Ensure whether data is in the right format
  • Verification: Checking whether the data is correct
  • Normalization: Process of converting a database from a flat file database to a relational database
  • Foreign key: database field whose purpose is to form a relationship with another table
  • Data Matching: Combining several databases for more info
  • Relational database: database containing multiple related tables and no redundant (no longer needed) data.
  • Flat File database: consist of only one table
    • Data integrity:
      • the more often data is repeated, the higher the chance that a mistake will be made (same field can have different, inconsistent values in different records)
      • This causes problems because some copies of the field might be updated while others are missed, creating inconsistent data

Relationships:

  1. One to many relationship

 

  • Queries: a way of selecting only the records in a database that match certain criteria
    • essential for accessing only the required information from a database
    • Boolean operators: AND, OR, and NOT are used to combine criteria (SQL)
    • Parameter Queries:
      • prompts the user for a value when the query is run.
      • data entered by the user is used as the criteria for that field

Forms: Forms are used to present a user friendly graphical interface for entering and altering data in a database (aka. data entry screens)

  • Can shield some data from users = help to control how it is accessed
  • Multiple layouts and designs

CSV (Comma Separated Values) & TSV (Tab Separated Values)= common ways of transferring data between different database and spreadsheet applications.

(adv: useful in cases where programs use different file formats to store their data)

 

Reports: a way of presenting data from a table in a database in a more professional manner than the default data sheet view.

 

SQL

  • Structured Query Language
    • Standard language
    • Available for many database management system

Issues: Integrity (ensuring that data is collect, relevant and up to date)

  1. A woman lost her job as an accountant and stated that she’s not ‘suitable’ for the job and did not tell her why (FBI). Later they discovered an error in the FBI National Criminal Information Center’s database, but the woman was still not hired. The problem was not only the incorrect data, but the lack of transparency about how the decision that the woman was ‘ unsuitable’ was reached.
  2. UK’s new electronic medical records systems could lead to patients being given inappropriate medication or suffering severe reactions, while in the the worse cases can be fatal.

Data may be incorrect for several reasons like: CTCIMID

  • Out of date
  • Entered Incorrectly
  • Transferred from another database (badly)
  • Changed accidentally
  • Changed deliberately
  • Incomplete
  • Totally missing

 

Validation: Ensure whether data is in the right format (PRVLCCC)

  1. Range check
  2. Length check
  3. Character check
  4. Presence check
  5. Consistency check
  6. Check digit
  7. Value list

Verification: Checking whether the data is correct

  1. Entering data twice: helps avoid typing mistakes that have occurred when data was entered.
  2. Comparing the original documents
  3. Verifying with the data subject

 

Issues; Privacy

Data Matching: combining databases to build up more information about a person

  1. Financial Records matched with tax data to look for people who may be avoiding tax payments by understating their income

Data Mining: Searching collections of data for hidden patterns and trends

  1. In Businesses: Used to target their advertising rather than printing their brochures and giving it to all customers, data mining can be used to identify those who are most likely to respond to the advertisement. (+) saves money
  2. Health: When someone is trying to apply for medical insurance, medical histories and family histories are checked to determine an individual’s risk

 

Privacy Concerns and Principles: PPDACLS

Def: how our data is used by the people who collect it

  1. Personally identifiable data or sensitive data
  2. Consent; terms of service or privacy policy documents
  3. Purpose
  4. Distribution
  5. Accessing data and correcting errors
  6. Length or storage
  7. Security

Issues: Security

Def: how safe data is from unauthorised access

  1. Police officers have taken bribed to provide criminal record data from the system to private investigators, journalists and even criminal gangs

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