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Systems Analysis | Case Study Report

1. Introduction

The assignment would focus on providing a layout for developing a College Student Registration System. Entity relationship diagram, data dictionary and normalisation are the main objectives of the first part of the assignment. The second part of this assignment deals mainly with data model and data flow diagram followed by CRUD matrix to establish relationship among CSRS entities.

2. Part A: Entity, relationship analysis and normalisation

2.1 Task 1: Identifying entities: noun phrase analysis

Identification of noun phrase analysis is important so that students can online register themselves for sections in each semester and would also improve efficiency of the database system. The system would verify a student’s prerequisite verification based on grades received and classes completed. However, in this task, it is necessary to identify all nouns used in the registration system to narrow the use of entities. The following objectives need to be fulfilled required for noun phrase analysis:

1. Findings all nouns: As per the given case scenario and analysis, the following nouns have been identified:

  • College
  • Student
  • Online
  • Students
  • Sections
  • Semester
  • Student
  • Register online
  • Prerequisites
  • Requested section
  • Student
  • Online transcript
  • Classes
  • Grades
  • Sections
  • Room
  • Student
  • Registration
  • Period
  • Semester
  • Sections
  • System
  • Student
  • Requested sections
  • Section
  • Prerequisite
  • Room
  • System
  • Student
  • CSRS system

2. Eliminating duplicates: After grouping ........

and data flow diagram followed by CRUD matrix to establish relationship among CSRS entities.

2. Part A: Entity, relationship analysis and normalisation

2.1 Task 1: Identifying entities: noun phrase analysis

Identification of noun phrase analysis is important so that students can online register themselves for sections in each semester and would also improve efficiency of the database system. The system would verify a student’s prerequisite verification based on grades received and classes completed. However, in this task, it is necessary to identify all nouns used in the registration system to narrow the use of entities. The following objectives need to be fulfilled required for noun phrase analysis:

1. Findings all nouns: As per the given case scenario and analysis, the following nouns have been identified:

  • College
  • Student
  • Online
  • Students
  • Sections
  • Semester
  • Student
  • Register online
  • Prerequisites
  • Requested section
  • Student
  • Online transcript
  • Classes
  • Grades
  • Sections
  • Room
  • Student
  • Registration
  • Period
  • Semester
  • Sections
  • System
  • Student
  • Requested sections
  • Section
  • Prerequisite
  • Room
  • System
  • Student
  • CSRS system

2. Eliminating duplicates: After grouping all nouns in CSRS system, duplicate entries have been eliminated. The following are the results of duplicates elimination:

  • College
  • Student
  • Online
  • Sections
  • Semester
  • Register online
  • Prerequisites
  • Online transcript
  • Classes
  • Grades
  • Room
  • Registration
  • Period
  • System
  • Requested sections
  • CSRS system

3. Eliminating references to the system itself: By eliminating references to the system, following are the remaining entities:

  • College
  • Student
  • Online
  • Sections
  • Semester
  • Register online
  • Prerequisites
  • Online transcript
  • Classes
  • Grades
  • Room
  • Registration
  • Period
  • Requested sections

4. Elimination of references to the organisation: Following are the remaining entities by eliminating references to the organisation which is college in this case:

  • Student
  • Online
  • Sections
  • Semester
  • Prerequisites
  • Online transcript
  • Classes
  • Grades
  • Register online
  • Room
  • Registration
  • Period
  • Requested sections

5. Eliminating other terms which doesn’t fit to be entities: After eliminating references to the organisation, the following entities remain:

  • Student
  • Sections
  • Semester
  • Prerequisites
  • Online transcript
  • Classes
  • Grades
  • Room
  • Registration
  • Requested sections

6. Grouping synonyms: Entities that have synonyms are group as follows:

  • Student
  • Sections
  • Semester
  • Prerequisites
  • Online transcript
  • Classes completed
  • Grades received
  • Room
  • Registration
  • Requested sections

7. Separating roles of an entity: In this step, the roles of entities are combined to form a single entity:

  • Student
  • Sections
  • Semester
  • Prerequisites
  • Online transcript
  • Classes completed
  • Grades received
  • Room
  • Registration
  • Requested sections

2.2 Task 2: Identifying relationships: verb analysis

The main verbs which are included in relationship matrix are as follows:

1. Student registers in the system

2. College Student Registration System approves access to the system

3. CSRS verifies a student, based on grades received and classes completed

Entity relation matrix

Student

Sections

Semester

Prerequisites

Online transcript

Classes completed

Grades received

Room

Registration

Requested sections

Student

?

?

?

?

?

?

?

?

?

?

Sections

?

?

?

?

?

?

?

?

?

?

Semester

?

?

?

?

?

?

?

?

?

?

Prerequisites

?

?

?

?

?

?

?

?

?

?

Online transcript

?

?

?

?

?

?

?

?

?

?

Classes completed

?

?

?

?

?

?

?

?

?

?

Grades received

?

?

?

?

?

?

?

?

?

?

Room

?

?

?

?

?

?

?

?

?

?

Registration

?

?

?

?

?

?

?

?

?

?

Requested sections

?

?

?

?

?

?

?

?

?

?

Table 2.1: Entity relationship matrix

(Source: created by author)

2.3 Task 3: Preparing data dictionary for entities

Sl. No.

Field name

Data type

Structured data types

IsNullable

Reference types

User defined functions

1.

student_id

int

Struct_student_information (

int student_id (100);

char student_name (300);

char contact_number(20);

char email_address (100);

);

NO

 

Identification number of students. This is the PRIMARY KEY and UNIQUE KEY

2.

student_name

varchar (300)

 

NO

REF(student_name)SCOPE (Students)

Name of students

3.

contact_number

varchar (20)

 

NO

 

Mobile or telephone numbers of students

4.

email_address

Varchar (100)

 

YES

 

Email address of students

5.

student_roll_no

Varchar (20)

 

NO

 

Roll number of students. FOREIGN KEY

Table 3.1: Data dictionary table for Students

(Source: created by author)

 

Sl. No.

Field name

Data type

Structured data types

IsNullable

Reference types

User defined functions

1.

section_id

int

Struct_structure_information (

int section_id (100);

char section_enrollment_no (20);

char section_room_no (20);

char section_student_no (20);

);

NO

 

Section identification numbers.

PRIMARY KEY

2.

section_enrollment_no

varchar (20)

 

NO

REF(student_roll_no) SCOPE (Students)

Section enrollment numbers given to students after validation. FOREIGN KEY

3.

section_room_no

varchar (20)

 

NO

 

Room number given to students after verification by the system

4.

section_student_no

Varchar (20)

 

NO

 

Student identification number generated after verification

Table 3.2: Data dictionary table for Sections

(Source: created by author)

 

Sl. No.

Field name

Data type

Structured data types

IsNullable

Reference types

User defined functions

1.

semester _no

int

Struct_semester_information (

int semester_no (10);

int semester_year (10);

char semester_course (3000);

);

NO

 

Semester number for the curriculum year. PRIMARY KEY

2.

semester_year

int

 

NO

 

Year in which semester is running

3.

semester_course

varchar (3000)

 

YES

 

Course name and course details of the semester

Table 3.3: Data dictionary table for Semester

(Source: created by author)

 

Sl. No.

Field name

Data type

Structured data types

IsNullable

Reference types

User defined functions

1.

class _no

int

Struct_class_information (

int class _no (10);

int class_year (10);

char class_student_name (3000);

);

NO

 

Class number for the curriculum year. PRIMARY KEY

2.

class_year

int

 

NO

 

Year in which class is included

3.

class_student_name

varchar (100)

 

YES

REF(student_name) SCOPE (Students)

Class name assigned with student’s name. FOREIGN KEY

Table 3.4: Data dictionary table for Classes completed

(Source: created by author)

 

Sl. No.

Field name

Data type

Structured data types

IsNullable

Reference types

User defined functions

1.

grade_id

varchar

     

PRIMARY KEY

2.

grade1_student_name

varchar

Struct_grades_information (

Char grade1_student_name (10);

Char grade_id (10);

Char grade2_student_name (10);

char grade3_student_name (10);

);

NO

 

Grades obtained for first subject

3.

grade2_student_name

varchar

 

NO

 

Grades obtained for first subject

4.

grade3_student_name

varchar

 

NO

REF(student_name, class_no) SCOPE (Students, Section)

Grades obtained for first subject

Table 3.5: Data dictionary table for Grades received

(Source: created by author)

 

Sl. No.

Field name

Data type

Structured data types

IsNullable

Reference types

User defined functions

1.

room_id

varchar

Struct_room_information (

Char room_id (10);

Char room_no (10);

char room_section (10);

);

NO

 

Room id serves as PRIMARY KEY

2.

room_no

varchar

 

NO

 

Room number is allocated to students based on validation

3.

room_section

varchar

 

NO

REF(student_name, section_enrollment_no) SCOPE (Students, Section)

Room sections added for room classification. COMPOSITE KEY

Table 3.6: Data dictionary table for Room

(Source: created by author)

 

Sl. No.

Field name

Data type

IsNullable

Reference types

User defined functions

1.

reg_id

Varchar (20)

NO

 

Registration id helps to identify students who have been verified and are eligible to for registration. PRIMARY KEY

Table 3.7: Data dictionary table for Registration

(Source: created by author)

 

Sl. No.

Field name

Data type

Structured data types

IsNullable

Reference types

User defined functions

1.

preq_id

int

Struct_preq_information (

int preq_id (100);

char preq_verify_1 (200);

char preq_verify_2 (200);

char preq_verify_3 (200);

);

NO

 

PRIMARY KEY

2.

preq_verify_1

varchar (200)

 

NO

REF(grade_no, class_no) SCOPE (Grades, Classes)

Verifies the marks obtained in first course

3.

preq_verify_2

varchar (200)

 

NO

 

Verifies the marks obtained in second course

4.

preq_verify_3

Varchar (200)

 

NO

 

Verifies the marks obtained in third course

Table 3.8: Data dictionary table for Prerequisites

(Source: created by author)

Coronel and Morris (2016) stated that multiple attributes are associated with each database record where every attribute consists of an associated data type. These are known as attribute data types. Some of their applications are as follows:

Data type

Name of the data type

Description

BLOB

Binary large object

Stores files in single records such as JPEG or PDF files inside databases

CRYPTO

Encrypted binary

Encrypts data in database and also on the screen. Generally used for passwords.

Table 3.9: Application of attribute data type

(Source: Laudon and Laudon, 2016)

 

2.4 Task 4: Normalisation and ER diagram

Based on Norman South lift company case study, the following ER diagram (2NF) can be obtained.

 

 
 

SALES STAFF 2NF

 

 

staff_id

sales_person

sales_office

office_number

1003

David Smith

Chicago

312-555-1212

1004

Jennifer Hugh

New York

212-555-1212

1005

Frank Chu

Chicago

312-555-1212

 

CUSTOMER TABLE 2NF

 

customer1

customer2

customerr3

Ford

GM

 

Dell

Apple

HP

Boeing

 

 

 

ORDER

ONLINE ORDER

PRODUCT

SALES STAFF

CUSTOMER

has

Text Box: has

1

Text Box: 1

0:M

Text Box: 0:M

1:M

Text Box: 1:M

contains

Text Box: contains

1

Text Box: 1

1:M

Text Box: 1:M

1

Text Box: 1

0:M

Text Box: 0:M

serves

Text Box: serves

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 3.1: ER Diagram

(Source: created by author)

 

 

 

3. Part B: Data model and data flow diagram

3.1 Task 1: Context data flow diagram

COLLEGE STUDENT REGISTRATION SYSTEM

 

1.0

Verify prerequisite

1.2

Add to waiting list

1.3

Notify enrolment

1.4

Enrol

1.1

Check availability

Student

Grades and Classes

Sections and Rooms

Sends data

Text Box: Sends data

Confirmation of registration

Text Box: Confirmation of registration

Registration

Text Box: Registration

Acceptance or rejection

Text Box: Acceptance or rejection

Sends data

Text Box: Sends data

Sends data

Text Box: Sends data

Verification

Text Box: Verification

Request

Text Box: Request

 

 

 

3.2 Task 2: Level 0 DFD

 

Registration

Text Box: Registration

1.0

Verify prerequisite

1.2

Add to waiting list

1.3

Notify enrolment

1.4

Enrol

1.1

Check availability

Student

Grades and Classes

Sections and Rooms

Acceptance or rejection

Text Box: Acceptance or rejection

Sends data

Text Box: Sends data

Sends data

Text Box: Sends data

Sends data

Text Box: Sends data

Verification

Text Box: Verification

Confirmation of registration

Text Box: Confirmation of registration

Request

Text Box: Request

 

 

 

 

1.1

Check room availability

1.2

First-serve first-come Waiting list

If prerequisite requirement is satisfied but room is not available

If a class or section becomes available, first-come student will automatically be added to the next section

1.2.1

Next section

3.3 Task 3: Level 1 DFD

 

 

Y

Text Box: Y                                                           

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

                                                                                                     

 

 

3.4 Task 4: Data model and process model CRUD matrix

Processes

Student

Section

Class

Room

Prerequisite

Semester

Registration

Grades

Transcript

Verify prerequisite

R

CRU

CR

CRU

C

R

C

R

R

Check room availability

R

R

R

CRUD

 

 

 

U

R

Add to waiting list

CRUD

R

 

UD

 

 

CU

 

CU

Notify enrolment

RU

 

R

 

U

R

U

 

R

Enrol

CRUD

R

CU

CU

 

U

RU

 

R

Table 4.1: CRUD Matrix

(Source: created by author)

4. Conclusion

Therefore, this assignment helped to create a schematic representation mainly for College Student Registration System. However, a case study of Norman South Lift Security Company where a ER diagram was required has also been explained. Altogether, this assignment focuses on evaluating pre-requirements for establishing an online database system used for systems analysis.