- Class Number 3569
- Term Code 3340
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- AsPr Qing Wang
- Class Dates
- Class Start Date 13/03/2023
- Class End Date 19/05/2023
- Census Date 07/04/2023
- Last Date to Enrol 31/03/2023
- John Luo
- RUIBIAO ZHU
- Sichao Li
- Tim Arney
This course is an introduction to database concepts and the general skills for designing and using databases, with a focus on relational database concepts and techniques. Current industry developments of database systems such as NoSQL databases will be introduced at the end of the course.
Upon successful completion, students will have the knowledge and skills to:
- Interpret and explain the basic concepts of the relational model and understand its mathematical foundation,
- Apply SQL language to define, query and manipulate a relational database,
- Apply conceptual database modelling methods such as entity-relationship model to design a relational database,
- Research, justify and apply database design methods on functional dependencies and normal forms to evaluate the quality of a relational database design,
- Interpret and discuss query processing and optimisation, transaction and security management in a relational database management system,
- Reflect upon state of the art of database management systems and big data management challenges.
This course will provide students with the opportunities:
1. To develop knowledge of a range of theoretical database concepts and practical skills;
2. To learn about some latest industry and research development in the field of databases.
Examination Material or equipment
It will be announced on the course website.
A laptop or desktop is needed for accessing the course materials on Wattle and for completing the assignments.
The recommended (not required) textbook for this course is
Fundamentals of Database Systems, 7th Edition, R. Elmasri and S. Navathe, Global Edition, 2017
This book has also been published under different titles and with different front covers (see below, 4th, 5thor 6th editions, etc.). These earlier versions are also fine for this course. The textbook is available from the Co-op bookshop. Some copies of this book (including both 7th and earlier editions) are available in the reserve section of the Hancock Library.
The course website is available through Wattle: http://wattle.anu.edu.au. All the lecture slides, lecture recordings, lab exercises, tutorial materials, announcements, and supplementary reading materials will be made available through Wattle. The course convener will update the course website as and when required. Students are expected to regularly check the course website for the latest information.
Students will be given feedback in the following forms in this course:
- written comments
- verbal comments
- feedback to whole class, groups, individuals, focus group etc
ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.
|Week/Session||Summary of Activities||Assessment|
|1||Week 1 Introduction to Database Systems Lectures and workshop: (1) present an overview of the course structure and content; (2) introduce the general concepts of databases, database management system and database system; (3) review the mathematical concepts behind databases, including sets, tuples, the Cartesian product of sets and relations. Lab 1: Setup Your Lab Environment||None|
|2||Week 2 Relational Data Model and SQL (1) Lectures and workshop: (1) introduce the relational data model; (2) describe integrity constraints over relations, including domain constraints, key constraints, entity integrity constraints and referential integrity constraints; (3) introduce the Data Definition Language (DDL) of the Structured Query Language (SQL). Lab 2: SQL Basics||Quiz|
|3||Week 3 Relational Data Model and SQL (2) Lectures and workshop: (1) introduce the Data Manipulation Language (DML) in SQL and focus on insert, update, delete; (2) describe simple SQL queries using Data Manipulation Language (DML); (3) describe advanced SQL queries using Data Manipulation Language, including set operations, join operations, subqueries and views. Lab 3: Advanced SQL.||Quiz|
|4||Week 4 Entity-Relationship Model Lectures and workshop: (1) discuss the general database design process; (2) present the basic modelling constructs of the entity-relationship (ER) model, including entities, relationships and constraints; (3) describe some additional features that have been proposed in the enhanced entity-relationship models; (4) discuss how an entity-relationship model can be converted into relations in the relational data model. Lab 4: ER Modelling||Quiz, Assignment 1|
|5||Intensive Week - Topic 1: Database Design - Functional Dependencies Lectures and workshop: (1) discuss some desirable properties of a “well-designed” database; (2) introduce the notion of functional dependency and discuss how to identify functional dependencies of a database; (3) explain how functional dependencies provide a formal way of analysing database design, for example, find keys. Tutorial 1: Database Modelling||Quiz|
|6||Intensive Week - Topic 2: Database Design - Normalisation Lectures and workshop: (1) introduce what is normalisation (including different normal forms) and de-normalisation, and discuss their trade-offs; (2) describe how to normalise a relation schema into Boyce-Codd Normal Form (BCNF); (3) describe how to normalise a relation schema into Third Normal Form (3NF). Tutorial 2: Functional Dependencies||Quiz|
|7||Intensive Week -Topic 3: Relational Algebra Lectures and workshop: (1) introduce the language of relational algebra and its main relational operators; (2) discuss how to write relational algebra queries. Tutorial 3: Normalisation||Quiz|
|8||Intensive Week - Topic 4: Query Processing and Optimisation Lectures and workshop: (1) introduce how SQL queries are processed in a relational database; (2) describe three optimisation approaches that are commonly used by the query optimiser in a relational database. Tutorial 4: Relational Algebra||Quiz|
|9||Intensive Week - Topic 5: Database Transactions Lectures and workshop: (1) introduce what is a transaction in a relational database; (2) discuss the ACID properties of transactions in a relational database; (3) discuss concurrent transactions and several problems that can be prevented by concurrency control. Tutorial 5: Query Processing and Optimisation||Quiz|
|10||Week 6 Database Security Lectures and workshop: (1) discuss the main objectives of database security and general techniques for securing databases against different types of threats; (2) present three main approaches to access control: discretionary access control, mandatory access control and role-based access control; (3) introduce the concept of SOL injection attack and principle, and some prevention techniques for protecting against SOL injection attacks.||Quiz, Assignment 2|
|11||Week 7 NoSQL Databases (1) Lectures: (1) present an overview of the development of database systems, and the differences between relational databases and NoSQL databases; (2) iIntroduce the key concepts of key-value data stores based on Amazon's Dynamo; (3) introduce the key concepts of column-oriented data stores based on Google's Bigtable.||Quiz|
|12||Week 8 NoSQL Databases (2) Lectures and workshop: (1) introduce the key concepts of document-oriented data stores based on MongoDB; (2) introduce the key concepts of Apache Hadoop (Hadoop Distributed File System and MapReduce) and Hive. Lab 5: Programming Hive||NoSQL Test|
|13||Week 9 Revision||Final exam|
Refer to the course Wattle site for further information.
|Assessment task||Value||Due Date||Return of assessment||Learning Outcomes|
|Quizzes||5 %||*||*||1, 2, 3, 4, 5|
|Assignment 1||20 %||09/04/2023||23/04/2023||1, 2|
|Assignment 2||20 %||23/04/2023||07/05/2023||3, 4, 5|
|NoSQL Test||5 %||07/05/2023||08/05/2023||6|
|Final Exam||50 %||*||*||1, 2, 3, 4, 5|
* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details
ANU has educational policies, procedures and guidelines , which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Integrity Rule before the commencement of their course. Other key policies and guidelines include:
- Academic Integrity Policy and Procedure
- Student Assessment (Coursework) Policy and Procedure
- Special Assessment Consideration Guideline and General Information
- Student Surveys and Evaluations
- Deferred Examinations
- Student Complaint Resolution Policy and Procedure
- Code of practice for teaching and learning
The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.
Moderation of Assessment
Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.
Assessment Task 1
Learning Outcomes: 1, 2, 3, 4, 5
There will be 10 online quizzes on the course Wattle site. Only one attempt is allowed for each quiz.
Assessment Task 2
Learning Outcomes: 1, 2
The assessment covers SQL programming. It should be done individually and no group work is allowed. The detailed specification will be made available on the course Wattle site, one week before the due date.
Assessment Task 3
Learning Outcomes: 3, 4, 5
The assessment covers the entity-relationship model, functional dependencies, normalisation relational algebra, query processing, and optimisation. It should be done individually and no group work is allowed. The detailed specification will be made available on the course Wattle site, one week before the due date.
Assessment Task 4
Learning Outcomes: 6
The assessment covers NoSQL databases. It should be done individually and no group work is allowed. The detailed specification will be made available on the course Wattle site, one week before the due date.
Assessment Task 5
Learning Outcomes: 1, 2, 3, 4, 5
This assessment covers all the topics except NoSQL databases. More information will be made available on the course Wattle site in Week 9. To pass the course, it is required to obtain at least 40% of the final exam marks.
Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.
The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.
The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.
The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.
Refer to the course Wattle site for online submission information of assignments.
Hard copy submission should be approved by the Associate Dean (Education).
Late submission not permitted. If submission of assessment tasks without an extension after the due date is not permitted, a mark of 0 will be awarded.
The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.
Extensions and Penalties
Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.
Distribution of grades policy
Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.
Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.
Support for students
The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).
- ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
- ANU Access and inclusion for students with a disability or ongoing or chronic illness
- ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
- ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
- ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
- ANUSA supports and represents undergraduate and ANU College students
- PARSA supports and represents postgraduate and research students
Data Management and Analysis, Graph Algorithms, and Graph Machine Learning
AsPr Qing Wang