University Database Management Project Focuses on managing the data associated with the Academic and Research department of the University. This presentation consists of the problem statement, E-R Diagram, the way of normalizing tables, an overview of the procedures, views, triggers etc and some of the complex queries. One is requested to go through the doc file to get an in-depth information about the project and its functionality. Doc file link - https://www.scribd.com/doc/269150294/University-Database-Management-System

1. University Database Management
System
Database Management System Project – SEM IV
Institute of Engineering and Technology – Ahmedabad University
7th March, 2015
Group Members:
Kavi Pandya - 131020
Mayank Jobanputra - 131026
Urvika Sonar - 131060
Preksha Chavda - 121036
DBMS, SEM-IV

2. Project Statement
University Database Management System creates, manages and
performs all the activities related to the database of a given
university. The database consists of information about the university,
colleges, students, faculties, academic and research programs. The
main aim of this project is to manage the database in such a way
that information about academic and research activities can be
retrieved easily, efficiently and accurately.

3. E R Diagram

4. Normalization of Forms
Normalization is applied to remove problems caused due to redundancy of data and
different kinds of anomalies.
1. Removing Redundancy:
Information about funding organizations funding different research projects of a university
and the data about the research projects being funded by this organizations are stored in
different tables because it may be possible that a funding organization maybe funding more
than one research project and keeping them in same table results in redundant data.
2. Avoiding Null Values:
Information about the faculties currently associated with the university is stored in a faculty
table. The data regarding the research projects on which the faculties are currently working
on or worked in the past are stored in a different table. It is possible that there may be
faculties that are not associated with any research project at present or in the past, so
keeping both the information in the same table would result in null values for the faculties
that are not related with any research project. Thus to avoid this problem, normalization is
applied, tables are separated and data is stored accordingly.

5. 3. Update Anomaly:
Update anomaly occurs when while updating certain data, past record about that data
is lost. Information about the courses being offered are kept in courses table.
Information about the courses being offered in a particular semester is stored in
different table. It may happen that a particular course was offered in some other
semester earlier and is currently being offered in some other semester. If the data is
kept combined in one table, it would result in loss of data as the record about the
semester in which the particular course was offered earlier would be lost while
updating the data for current semester, resulting in update anomaly.
4. Delete Anomaly:
This anomaly occurs when data is lost while deleting previous records from the table.
Information regarding the topics that are being taught in a given course are stored in one
table. The data about the course structure for that particular course is stored in another
table. It is done because the course structure for courses might change. For example, few
topics that were included in course structure for a particular course earlier are now
removed from it. If the data was kept in same table then removing those topics from
course structure would permanently remove its record from the database. To avoid this,
Normalization is applied and tables are separated for storing data according to that.

6. Database Schema
Contents:
➢ Tables: 65
➢ Queries: 57
➢ Triggers: 6
➢ Stored Procedures: 4
➢ Views: 2
➢ Tables with Java Connectivity: 1

7. Complex Queries
1. Finding students having following constraints and studying in section-1, having
Attendance>7, quiz>7, assignment>15, project>43, mid-exam>30 and final-exam>35
2. Percentage obtained by student '1301001A01' in SEM-1 in the subject of CS101 in
Batch-A (including marks obtained in Quiz, Assignment, Attendance, Project, Mid-Term
Exam and Final-Term-Exam)