Database Concepts – Hire Academic Expert

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School of Science

ISYS1055 Database Concepts
Assessment 4: Database Design Project

Assessment type: Take-home assessment Word limit: N/A
Due Date: 12 June at 23:59 (Melbourne Time)
Weighting: 35%, 35 Marks

This is a practical and real-world project that puts the knowledge you gained into practice. You are required to
investigate and understand a publicly available dataset, design a conceptual model for storing the dataset in a
relational database, apply normalisation techniques to improve the model, build the database according to your
design and import the data into your database, and develop SQL queries in response to a set of requirements.
The objective of this assignment is to reinforce what you have learned in the whole course. Specifically, it involves
how to build a simple application that connects to a database backend, running a simple relational schema.
Part A: Understanding the Data (0 Marks, Preliminary Work)
Part B: Designing the Database (10%)
Part C: Creating the Database and Importing Data (10%)
Part D: Data Retrieval and Visualisation(15%)
Assessment criteria
This assessment will measure your ability to:
Analyse the requirements outlined in the problem description
Develop a conceptual model for the design of a database backend required for the system
Use an industry-standard ER modelling tool to draw the ER model
Use 7-step mapping process to create relational database schema
Use normalisation process to evaluate the schema and make sure that all the relations are at
least 3NF

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Create tables on SQLite Studio and populate them with data available from the specified sources.
Write SQL statements required for CRUD (create, read, update and delete) operations on the
database you built
Develop your knowledge further to represent data in a meaningful way using data visualisation.
Course learning outcomes
This assessment is relevant to the following course learning outcomes:

CLO1 Describe the underlying theoretical basis of the relational database model and apply
the theories into practice;
CLO2 Explain the main concepts for data modelling and characteristics of database systems.
CLO3 Develop a sound database design using conceptual modeling mechanisms such as
entity-relationship diagrams.
CLO4 Develop a database based on a sound database design;
CLO5 Apply SQL as a programming language to define database schemas, update database
contents, and to extract data from databases for specific users’ information needs.

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Assessment details
Part A: Understanding the Data
In this assignment, we are working with the publicly available dataset: A Global Database of
COVID-19 Vaccinations
. Further details about this dataset are available in the article available
through the following URL: The abstract of
the article is as follows.
An effective rollout of vaccinations against COVID-19 offers the most promising
prospect of bringing the pandemic to an end. We present the Our World in Data COVID-
19 vaccination dataset, a global public dataset that tracks the scale and rate of the
vaccine rollout across the world. This dataset is updated regularly and includes data on
the total number of vaccinations administered, first and second doses administered,
daily vaccination rates and population-adjusted coverage for all countries for which
data are available (169 countries as of 7 April 2021). It will be maintained as the global
vaccination campaign continues to progress. This resource aids policymakers and
researchers in understanding the rate of current and potential vaccine rollout; the
interactions with non-vaccination policy responses; the potential impact of vaccinations
on pandemic outcomes such as transmission, morbidity and mortality; and global
inequalities in vaccine access.
A live version of the vaccination dataset and documentation are available in a public GitHub
repository at These
data can be downloaded in CSV and JSON formats.
For the purposes of completing this assignment, we are only using the following files. You are
required to review and analyse the dataset available in these files. You will find that reviewing the
rest of the files, even if not listed below, will help you to form a better understanding about the big

1 locations.csv Country names and the type of vaccines administered.
Each line represents the last observation in a specific
country. Refer to for the details.
2 us_state_vaccinations.csv History of observations for various locations in the US.
3 vaccinations-by-age-group.csv History of observations for vaccinations of various age
groups in each country.
4 vaccinations-by
History of observations for various types of vaccines
used in each country.
5 vaccinations.csv Country-by-country data on global COVID-19
vaccinations. Each line represents an observation date.
Refer to for the details.
6 country_data/Australia.csv Daily observations of vaccination in Australia.

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7 country_data/United States.csv Daily observations of vaccination in the US.
8 country_data/France.csv Daily observations of vaccination in France.
9 country_data/Israel.csv Daily observations of vaccination in Israel.

Table 1: List of data files
To complete the tasks in the following sections, you are required to review and analyse the dataset
that is available in the named files.
Part B: Designing the Database (10%)
Task B.1 Produce an ER diagram for a relational database that will be able to store the given
It is important to note that the given CSV files are not necessarily representing a good design for a
relational database. It is your task to design a database that will adhere to good design principles
that were taught throughout the course. This means your database schema will not match the
structure of the CSV files and, therefore, you will require to manipulate the structure of the dataset
(and not the data itself) to import it into your database. Importing the data is required to complete
Task C.2.
The ER diagram must be produced by
Lucidchart similar to the exercises that were completed in in
the course. UML notation is expected and using other notations will not be acceptable. Including a
high-quality image representing your model is important, which can be achieved using Export
function of Lucidchart.
You are also required to transform the ER diagram into a database schema that will be used in the
next part of the assignment.
Creating a good database design typically involves some database normalisation activities. You
should document your normalisation activities and support them with good reasoning. This
typically involves explaining what the initial design was, what the problem was, and what changes
have been made to rectify the issue.
The expected outcome of completing this task is one PDF file named model.pdf containing the
following sections.
1. Database ER diagram and, if needed, a reasonable set of assumptions.
2. Explanation of normalisation challenges and the resulting changes.
3. Database schema.
Part C: Creating the Database and Importing Data (10%)
Task C.1 Produce one SQL script file named database.sql. This script file requires all the SQL
statements necessary to create all the database relations and their corresponding integrity
constraints as per your proposed design in Part B. The script file must run without any errors in

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SQLite Studio and contain necessary commenting to separate various relations. Note that this
script is not supposed to store any data into the relations.
The expected outcome of completing this task is one script file with the specific name of
Task C.2 Create a database file named Vaccinations.db. Import the given dataset into your
To complete this task, you may need to change the format of the CSV files to match the attributes
of your designed database. You can use a spreadsheet editor such as Microsoft Excel.
The next step is to
import the spreadsheets into the database you create in SQLite Studio. To
complete this task, use the menu option
Tools – Import in SQLite.
The expected outcome of completing this task is one database file named Vaccinations.db, which
must contain all the data that is stored in the CSV files named in Table 1.
Part D: Data Retrieval and Visualisation (15%)
Now that you have created and populated a database, it is time to create some queries to
investigate the data in various ways. In addition to writing the required queries, you are also asked
to produce data visualisation for the results of your queries.
The tasks in this section represent the queries that must be supported. Each query must consist of
one SQL statement. It would be acceptable to use several nested queries, combine several SELECT
statements with various operators etc. However, it would not be acceptable to have multiple and
separated queries for each task.
After you have written each query, you are expected to produce a data visualisation for each result
set. You have the freedom to choose the tool for creating your visuals (e.g., Excel, Google Charts,
Tableau) as well as the visualisation techniques (e.g., charts, plots, diagrams, maps). Completing
this portion of the work will require that you understand the nature of the results of each query,
undertake research to choose a visualisation tool you are comfortable with, decide about the best
technique to visually represent each result set, and produce the visualisation.
Answers to tasks in
Part D that are not supported by a visualisation can achieve up to 80% of the grade associated
with each task.
The expected outcome of completing this task
is as follows.
1. One SQL script file named Queries.sql containing
all the queries developed for the tasks in
this section. It is important that you add comment lines to separate the queries and
indicate which task they belong to. Note that valid SQL comments must not generate
errors in SQLite Studio. The marker of your work will use this file to execute and test your
1. A PDF file named QuerieResults.pdf containing the following elements for each task.
a. The SQL query

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b. a snapshot of the first 10 results of your query. The snapshot must also show the
total number of results retrieved by the query. A sample snapshot is provided
below for your reference.
Figure 1: Sample results snapshot with total rows
c. Data visualisation
List of Tasks
Task D.1 For any two given dates (i.e., you can assume any two dates, e.g., 1 April and 3 April), list
the dates, the total number of vaccines administered in each observation date in each of all
countries, and the difference between the administered vaccines. Each row in the result set must
have the following structure. (Note: OD2 is after OD1)

Date 1 (OD1)
Vaccine on
OD1 (VOD1)
Date 2
Vaccine on
OD2 (VOD2)
Difference of

Figure 2: Column Headers in the Result Set for Task D.1
Task D.2 Find the countries with the cumulative numbers of COVID-19 doses administered by each
bigger than the average doses administered by all countries. Produces a result set containing the
name of each country and the cumulative number of doses administered in that country. Each row
in the result set must have the following structure.

Figure 3: Column Headers in the Result Set for Task D.2
Task D.3 Produce a list of 10 countries with the biggest numbers of vaccine types, with the type of
vaccines (e.g., Oxford/AstraZeneca, Pfizer/BioNTech) administered in each country. For a country
that has administered several types of vaccine, the result set is required to show several tuples

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reporting each type of vaccine in a separate tuple. Each row in the result set must have the following

Figure 4: Column Headers in the Result Set for Task D.3
Task D.4 There are different data sources used to produce the dataset. Produce a report showing the
total number of vaccines administered according to each data source (i.e., each unique URL). Order
the result set by source name and URL. Each row in the result set must have the following structure.

Source Name Total Administered Vaccines Source URL

Figure 5: Column Headers in the Result Set for Task D.4
Task D.5 How does various countries compare in the speed of their vaccine administration? Produce
a report that lists all the observation dates in 2022 and, for each date, list the total number of people
fully vaccinated in each one of the 4 countries used in this assignment.
[Date, Australia, United States, England, China]

Date Australia United States England China

Figure 6: Column Headers in the Result Set for Task D.5
Submission Format
You are required to submit the files with the exact names as below.
1. Model.pdf
2. Database.sql
3. Vaccinations.db
4. Queries.sql
5. Queries.pdf
In the previous sections of the assignment, the expected content of each of the files is explained in
Referencing guidelines
Use RMIT Harvard referencing style for this assessment.
You must acknowledge all the courses of information you have used in your assessments.
Refer to the
RMIT Easy Cite referencing tool to see examples and tips on how to reference in the
appropriated style. You can also refer to the library referencing page for more tools such as
EndNote, referencing tutorials and referencing guides for printing.
Academic integrity and plagiarism
Academic integrity is about honest presentation of your academic work. It means acknowledging
the work of others while developing your own insights, knowledge, and ideas.
You should take extreme care that you have:

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Acknowledged words, data, diagrams, models, frameworks and/or ideas of others you have
quoted (i.e., directly copied), summarised, paraphrased, discussed, or mentioned in your
assessment through the appropriate referencing methods.
Provided a reference list of the publication details so your reader can locate the source if
necessary. This includes material taken from Internet sites.
If you do not acknowledge the sources of your material, you may be accused of plagiarism because
you have passed off the work and ideas of another person without appropriate referencing, as if
they were your own.
RMIT University treats plagiarism as a very serious offence constituting misconduct.
Plagiarism covers a variety of inappropriate behaviours, including:
Failure to properly document a source
Copyright material from the internet or databases
Collusion between students
For further information on our policies and procedures, please refer to the University website.
Assessment declaration
When you submit work electronically, you agree to the assessment declaration.