o MS Access is preferable to Open Office which is a viable option for those without Access

o MS Access is preferable to Open Office which is a viable option for those without Access

· Projects

 

MS Access is preferable to Open Office which is a viable option for those without Access

 

o Use your own data. Don’t look to download anything from the site.

 

o Make the data realistic. It does not have to be real, but don’t do things like using A, B, C, etc. for names or just whole numbers for GPA. Use 2 decimal position GPAs.

 

o Use enough data to test all conditions. Make sure the data proves the queries worked

 

o Pay attention to format, spelling, etc. on the report

Part 1:

Course Project Part 1

You are required to use OpenOffice software to build tables, write, and execute queries.

 

1. Build a Database named DBMS Course Project. The database should include following tables.

 

o First Table – Students

 

§ ID

 

§ First Name

 

§ Last Name

 

§ Address

 

§ City

 

§ State

 

§ Zip Code

 

§ Phone Number with area code

 

o Second Table – GPA

 

§ ID

 

§ Current GPA

 

§ Class

 

§ 1 (Freshman)

 

§ 2 (Sophomore)

 

§ 3 (Junior)

 

§ 4 (Senior)

 

§ 5 (Graduate Student)

 

o Third Table – Scholarships

 

§ ID

 

§ Major course of study

 

§ Academic Scholarship (Yes or No)

 

§ Athletic Scholarship (Yes or No)

 

2. Extract the First and Last Name, Address, City, State, Zip Code and Phone Number of each senior on the database. Sort by Last Name, then First Name (1 sort).

 

3. Extract the First and Last Name, and GPA of each student who qualifies for the Dean’s List. Sort by GPA, then Last Name, then First Name (1 sort). A GPA of 3.25 is required to make the Dean’s List.

Part 2:

Course Project Part 2

You are required to use OpenOffice software to write and execute queries with tables you created in project part 1.

 

1. Extract the First and Last Name, Student ID, Course Major and GPA of any students on athletic scholarship. Sort by Student ID.

 

2. Produce a report with the data from Step #1 and Use good headings.

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