FEBRUARY 2023

Overview

In this assessment, you will apply normalization techniques to evaluate the entities designed in Assessment 1 and ensure that all relations are normalized to at least the third normal form (3NF).

Note: This is an individual assignment carrying 10% of the total mark in this unit. The submission deadline is end of the week of session 9.

Objectives(s)

This assessment item relates to the unit learning outcomes as in the unit descriptor. This assessment is designed to improve students’ skills to analyze organization database requirements, normalize a database and use data manipulation language to manage a database. This assessment covers the following LOs.

• Derive a physical design from the logical design taking into account application, hardware, operating system, and data communications networks requirements; further use of data manipulation language to query, update, and manage a database
• Identify functional dependencies, referential integrity, data integrity and security requirements; Further integrate and merge physical design by applying normalization techniques.
• Design and build a database system using the knowledge acquired in the unit as well as through further research on recent trends to demonstrate competence in various advanced tasks with regard to modelling, designing, and implementing a DBMS including Data warehousing, Data Management, DB Security.

Assessment Criteria

This assessment is designed to assess student’s knowledge, skill and application of

knowledge and skill in relation to

1. Design guidelines for relational schemas.
2. Database design process.
3. Application of normalization techniques.
4. Building a database.
5. Data manipulation language.

Task 1                                                                                                                   (Weighting 20%)

Ensure all tables designed in Assignment 1 satisfies the design guidelines for relational schemas.

• Identify any non-semantic columns in each table and transform tables where the tables should have semantic columns.

• Identify tables which could possibly have any anomalies and remove all anomalies from the tables.

• Identify any columns which may have frequently null values and remove or revised those columns. If nulls are unavoidable, then make sure that they apply in exceptional cases only.

• Identify any possibility of spurious tuples and avoid such relations that contain matching columns that are not primary key and foreign key combination.

Task 2                                                                                                                   (Weighting 30%)

Apply normalization technique on all tables designed in Assignment 1.

• Identify any repeating group of columns in each table and transform unnormalized tables into tables that are in 1st Normal Form.

• Identify any partial dependencies in each table and transform 1NF table into tables that are in 2nd Normal Form.

• Identify any transitive dependencies in each table and transform 2NF table into tables that are in 3rd Normal Form.

Please note: Your tables must be in 3NF.

Task 3                                                                                                                   (Weighting 50%)

This task must execute on MS SQL Server and be able to be demonstrated. SQL code required (Use MS SQL Server):

• Write a Create database statement to create a database and also, write a Create Table statement for all tables including integrity constraints.

• INSERT INTO statements for populating the database.

• You must at least enter 5 records for each table.
  • Data may need to be inserted in a particular order to comply with the integrity constraints.
• SELECT statement that will list all houses / apartments that have not been rented.

• The details may be included like house id, classification, number of bedrooms, number of washrooms, garden, parking for number of cars, rent per day, etc.
• SELECT statement that will produce the total amount paid per customer.

• The details may be included customer id, registration date, customer name, customer address, customer phone number and total amount paid, etc.

General Instructions

• Your submission should be clear and concise and in your own words.

• One submission per student.

• Use headings to guide the marker and include tables or diagrams where required.

• The referencing style must follow the IEEE referencing style.

Submission Guidelines

• Follow the link in Moodle to upload your submission on or before the deadline. All submissions must be done in LMS using the respective link provided.

• Submission must be made by the due date and time as determined by the unit facilitator.

Submissions made after the due date/time will be penalized at the rate of 20% per day (including Saturday, Sunday and public holidays).

• Incidence of plagiarism will be penalized based on VIT Academic Integrity Policy and Procedure.

• Submit your work in a word document file named ‘Student_Id_MITS4003_A2’.

Marking Guide:

Marking Guide: Case Study 1	Unacceptable	Acceptable	Good	Excellent
1.      Task 1   (Weighting 20%)
1.1 Semantic columns (Weighting 5%)	Does not adequately identify non-semantic columns.	Identify a few of the non-semantic columns and precisely transform tables that are having semantic columns.	Correctly identify most of the non- semantic columns and precisely transform tables that are having semantic columns.	Correctly identify all of the non-semantic columns and precisely transform tables that are having semantic columns.
1.2 Anomalies (Weighting 5%)	Does not adequately identify anomalies.	Identify a few of the anomalies and remove those anomalies from the tables.	Correctly identify most of the possible anomalies and remove those anomalies from the tables.	Correctly identify all of the possible anomalies and remove those anomalies from the tables.
1.3 Null values (Weighting 5%)	Does not adequately identify columns which may have frequently null values.	Identify a few of the columns which may have frequently null values and remove or revise those columns.	Identify most of the columns which may have frequently null values and remove or revise those columns.	Identify all of the columns which may have frequently null values and remove or revise those columns.
1.4 Spurious tuples (Weighting 5%)	Does not adequately identify possible spurious tuples.	Identify a few of the possible spurious tuples and avoid those relationships.	Identify most of the possible spurious tuples and avoid those relationships.	Identify all of the possible spurious tuples and avoid those relationships.
2.      Task 2   (Weighting 30%)
2.1 1NF (Weighting 15%)	Does not adequately identify repeating group of columns and not transform unnormalised tables into 1NF tables.	Identify a few of the repeating group of columns and correctly transform a few of the unnormalised tables into 1NF tables.	Identify most of the repeating group of columns and correctly transform most of the unnormalised tables into 1NF tables.	Identify all of the repeating group of columns in each table and correctly transform all of the unnormalised tables into 1NF tables.
2.2 2NF (Weighting 10%)	Does not adequately identify partial dependencies and not transform 1NF tables into 2NF tables.	Identify a few of the partial dependencies and correctly transform a few of the 1NF tables into 2NF tables.	Identify most of the partial dependencies and correctly transform most of the 1NF tables into 2NF tables.	Identify all of the partial dependencies in each table and correctly transform all of the 1NF tables into 2NF tables.
2.3 3NF (Weighting 5%)	Does not adequately identify transitive dependencies and not transform 2NF tables into 3NF tables.	Identify a few of the transitive dependencies and correctly transform a few of the 2NF tables into 3NF tables.	Identify most of the transitive dependencies and correctly transform most of the 2NF tables into 3NF tables.	Identify all of the transitive dependencies and correctly transform all of the 2NF tables into 3NF tables.
3.      Task 3   (Weighting 50%)
3.1 Create table (Weighting 10%)	Incorrect syntax.	Partially correct syntax.	Syntactically correct code and correctly created most tables.	Correctly created all tables.

3.2 Insert statements (Weighting 10%)	Incorrect syntax.	Partially correct syntax and very few records are inserted as per the requirements.	Syntactically correct and most of the records are inserted as per the requirements.	Code is correct and all records are inserted as per the requirements.
3.3 SELECT statement that will list all houses / apartments that have not been rented (Weighting 15%)	Incorrect syntax.	Partially correct syntax and gives output somewhat near to requirements.	Syntactically correct and gives output very near to requirements.	Code is correct and used JOIN, etc. and gives the required output
3.4 SELECT statement that will produce the total amount paid per customer. (Weighting 15%)	Incorrect syntax.	Partially correct syntax and gives output somewhat near to requirements.	Syntactically correct and gives output very near to requirements.	Code is correct and used JOIN, etc. and gives the required output

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