NAME: AKASH A P REG NO: 22ETIS411004
Laboratory 2
Title of the Laboratory Exercise: Requirement analysis and data modelling
• Introduction and Purpose of Experiment
The requirements analysis phase produce both data requirements and functional
requirements. The data requirements are used as a source of database design and should be
specified as detailed and complete form as possible. In data modelling, the designers first
create a conceptual model of how data items relate to each other. By doing this lab, students
will be able to perform data modelling of the application.
• Aim and Objectives
Aim
• To analyse the given application and create a data model
Objectives
At the end of this lab, the student will be able to
• Identify functional and data requirements from problem statement
• Create a data model from the data requirements
• Experimental Procedure
• Read the problem statement and identify requirements
• Perform data modeling
• Document the requirements and ER diagram
• Question
Students have to choose one of the following problem statements and develop the software
solution. The Course leader is the customer. Contact the Course leader for any clarifications.
• Student enrolment system
• Automobile sales system
• Railway reservation system
Perform the following based on the problem statement you have chosen
• Analyse the given application and list the functional and data requirements
• Perform data modelling based on the identified data requirements
NAME: AKASH A P REG NO: 22ETIS411004
• Calculations/Computations/Algorithms
ER Diagram: A conceptual model of entities, their attributes, and relationships.
Schema Diagram: A relational schema including tables, columns, primary keys, and foreign
keys.
• Presentation of Results
• Student enrolment system
• Analysis and Discussions
The effectiveness of the ER diagram in representing relationships between data entities.
• Conclusions
I learned how important it is to understand the system’s needs before designing the database.
Creating a clear and simple data model helped make sure the data stays accurate.
• Comments
Challenges faced, such as deciding on entity relationships or attributes.