Traffic ticket database

Homework Essay Help: Traffic ticket database : Using Microsoft Access, create the following traffic ticket database with its associated tables, fields (including appropriate data type), primary keys and foreign keys.  A traffic ticket is a notice issued by a law enforcement official to a motorist accusing violation of traffic laws.

Note: Make sure to create the relationships between your tables before adding the records in your tables. (MS ACCESS)

  • The motorist information includes driver license number, name, zipcode, state. The motorist is uniquely identified by his/her license number. Create at least 5 unique motorist records.  
  • The traffic offense type is associated with the offense description (i.e. red light) and its designed fine amount (i.e. $158). Each traffic offense type is uniquely identified by its offense description. Create at least 3 unique traffic offense type records. 
  • The law enforcement official information includes badge number, name, and year in service (i.e. 2). The law enforcement is uniquely identified by his/her badge number. Create at least 3 unique law enforcement official records. 
  • The traffic ticket includes the ticket number, date issued, the motorist’s driver license number, the traffic offense type’s description, and the law enforcement official’s badge number. The traffic ticket is uniquely identified by its ticket number. Create at least 8 unique traffic ticket records. 

A traffic ticket is issued by a specific law enforcement official to one and only motorist. A law enforcement official can issue many traffic tickets and a motorist can received many traffic tickets.

  • Create one query named “Invoices” using “Query Design” that outputs the total (aka SUM function) amount of the traffic tickets due andtotal number (aka COUNT function) of traffic tickets received by each individual motorist’s license number. The outputs should also display the name of the motorists.   

Your Submission


  • Correctness of the four tables and their associated fields’ name (25%)
  • Pertinence of the fields’ data type, field size and participation (required or not) (25%)  
  • Correctness of the relationships between the tables (25%)
  • Pertinence of the data entries (15%)
  • Correctness of the query (10%)
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