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Unit of study_

ISYS2120: Data and Information Management

Semester 2, 2023 [Normal day] - Camperdown/Darlington, Sydney

The ubiquitous use of information technology leaves us facing a tsunami of data produced by users, IT systems and mobile devices. The proper management of data is hence essential for all applications and for effective decision making within organizations. This unit of study will introduce the basic concepts of database designs at the conceptual, logical and physical levels. We will place particular emphasis on introducing integrity constraints and the concept of data normalization which prevents data from being corrupted or duplicated in different parts of the database. This in turn helps in the data remaining consistent during its lifetime. Once a database design is in place, the emphasis shifts towards querying the data in order to extract useful information. The unit will introduce the SQL database query languages, which is industry standard. Other topics covered will include the important concept of transaction management, application development with a backend database, and an overview of data warehousing and OLAP.

Unit details and rules

Unit code ISYS2120
Academic unit Computer Science
Credit points 6
INFO2120 OR INFO2820 OR COMP5138
INFO1113 OR INFO1103 OR INFO1105 OR INFO1905 OR INFO1003 OR INFO1903 OR DECO1012
Assumed knowledge

Programming skills

Available to study abroad and exchange students


Teaching staff

Coordinator Alan Fekete,
Type Description Weight Due Length
Supervised exam
hurdle task
Final Exam
Final Exam in-person on campus, hand-writing on paper
60% Formal exam period 2 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8
Online task SQL tasks
Online tasks to write SQL queries that have given output
5% Multiple weeks n/a
Outcomes assessed: LO3
Participation Hand-written summaries
Handwrite summary of key points from lecture content, scan, upload
5% Multiple weeks Half-page handwritten each week
Outcomes assessed: LO1 LO8 LO7 LO6 LO5 LO4 LO3 LO2
Participation Involvement in group work
Provide contributions to group consultation sessions with tutor
5% Multiple weeks n/a
Outcomes assessed: LO1 LO9 LO8 LO7 LO6 LO5 LO4 LO3 LO2
Assignment group assignment Assignment 1 (Relational schema)
Produce a relational schema from a conceptual model
5% Week 04
Due date: 27 Aug 2023 at 23:59
Outcomes assessed: LO2 LO4 LO9
Assignment group assignment Assignment 2 (Conceptual Model)
Produce a conceptual model for a domain
5% Week 07
Due date: 17 Sep 2023 at 23:59
Outcomes assessed: LO4 LO9
Assignment group assignment Group aspect of Assignment 3 (Data-backed application and security)
Produce group report covering security aspects of the web application
5% Week 11
Due date: 22 Oct 2023 at 23:59
Outcomes assessed: LO3 LO5 LO6 LO9
Assignment Individual aspect of Assignment 3 (Data-backed Application and Security)
extend skeleton code base for extra functionality and security
5% Week 11
Due date: 22 Oct 2023 at 23:59
Outcomes assessed: LO3 LO5 LO6 LO9
Assignment Assignment 4 (Concepts)
Answer questions on unit concepts, especially those using theory
5% Week 12
Due date: 29 Oct 2023 at 23:59
Outcomes assessed: LO4 LO5 LO6 LO7 LO8
hurdle task = hurdle task ?
group assignment = group assignment ?

Assessment summary


Week Due

Weight (%)

SQL tasks

Multiple weeks


Hand-written summaries

Multiple weeks


Involvement in group work

Multiple weeks


Assignment 1 

Week 4


Assignment 2 

Week 7


Assignment 3 - individual work

Week 11


Assignment 3 - group work

Week 11


Assignment 4 

Week 12

Final Exam

Exam Weeks



Assessment criteria

Minimum Pass Requirement

It is a policy of the School of Computer Science that in order to pass this unit, a student must achieve at least 40% in the written examination. For subjects without a final exam, the 40% minimum requirement applies to the corresponding major assessment component specified by the lecturer. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average.


The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range


High distinction

85 - 100



75 - 84



65 - 74



50 - 64



0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Late work is not accepted for SQL tasks, hand-written summaries, and involvement in group work. Where special consideration (or Academic Plan) is granted for these assessments, reweighting of other relevant tasks will be applied. Late submissions for assignments will incur a penalty of 5% of the maximum awardable marks for each day, or part-day, past the due date, up to a maximum of 7 days (as after this time, feedback on on-time submissions will be available, resulting in an unfair advantage if submissions after this time were accepted). After 7 days late submissions will not be accepted. Where special consideration is granted for these assessments, extensions of a maximum of 7 days will be permitted. After 7 days, reweighting of other relevant tasks will be applied.

Academic integrity

The Current Student website  provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.  

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Week 01 Introduction, Administrativa, Overview of the relational approach to data, role of data and dbms in organisations, and relevant job roles Lecture (2 hr) LO1 LO2
Week 02 Core SQL constructs (SELECT-FROM-WHERE, aggregates, joins); Entity-Relationship notation (and extensions) for expression of a conceptual data model Lecture (2 hr) LO2 LO3 LO4
Getting to know one another; Group formation; Entity-relationship diagrams Computer laboratory (2 hr) LO4
Week 03 Converting an ER conceptual design to a relational schema; SQL schema definition commands (including simple integrity constraints); SQL modification syntax (INSERT, DELETE, UPDATE) Lecture (2 hr) LO3 LO4
Convert ER diagram to relational schema Computer laboratory (1 hr) LO4
Week 04 Relational algebra and its relationship with SQL; More Complex SQL (including subqueries, handling of nulls, outer joins) Lecture (2 hr) LO2 LO3 LO8
Relational algebra; SQL grouping and aggregation; Computer laboratory (1 hr) LO3 LO8
Week 05 How to produce a conceptual data model for a domain; review of conversion from conceptual model to relational schema Lecture (2 hr) LO2 LO4
Group adjustment; evaluation of conceptual data model Computer laboratory (1 hr) LO4
Week 06 General feedback on Asst1; Evaluating and improving relational schema; Relational design theory (functional dependencies, Boyce-Codd Normal Form; schema decomposition) Lecture (2 hr) LO2 LO4 LO8
Relational design and normalisation; Computer laboratory (1 hr) LO4 LO8
Week 07 Data security and privacy - goals, attacks, protection mechansims (views; access control; triggers and sophisticated integrity mechanisms; stored procedures, anonymization, data perturbation) Lecture (2 hr) LO6 LO8
Access control; integrity; privacy Computer laboratory (1 hr) LO3 LO6 LO8
Week 08 DB Applications (architecture, technology choices, development approaches); security for DB applications Lecture (2 hr) LO5 LO6
Data-backed application code Computer laboratory (2 hr) LO5
Week 09 Group adjustment; practice with SQL without ongoing automated testing. Computer laboratory (2 hr) LO3
Week 10 General feedback on Asst2; overview of dbms implementation concepts (physical storage including indexes, buffers; query processing); performance tuning Lecture (2 hr) LO7 LO8
DBMS implementation; Computer laboratory (1 hr) LO7 LO8
Week 11 More on dbms implementation concepts, including transactions and security and privacy support Lecture (2 hr) LO7 LO8
Database implementation; Computer laboratory (1 hr) LO7 LO8
Week 12 Overview of enterprise-scale data management; data integration Lecture (2 hr) LO1 LO5 LO8
Data integration and analytics; Computer laboratory (1 hr) LO1 LO8
Week 13 General feedback on Asst3; Revision, exam preview Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8
Exam preparation Computer laboratory (1 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8

Attendance and class requirements

  • Study commitment: A variety of learning situations will be employed during the unit of study, including lectures, on-line demos, tutorials or directed computer laboratory exercises, self-learning SQL exercises (`SQL Challenge`), online formative quizzes, assessed assignments. To benefit fully from this unit it is necessary to participate fully in all aspects of the unit of study.
  • Laboratories/tutorials: Laboratory and Tutorial work includes hands-on use of DBMS and practice in problem-solving related to the content.
  • Independent Study: Work on assignments, reading material from notes/references, preparing hand-written summaries, etc; this should allow students to engage with the material and to integrate it into their understanding. 4 hours independent study is expected each week.
  • Project Work (own time): Group Work on assignments. 3 hours of project work is expected each week, as well as a 20 minute meeting of the group to consult with a teacher.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. understand the concept of a DBMS, differences from other ways to store and share data, DBMS role in organisations, and the types of work done with a DBMS
  • LO2. understand the relational data model: connect relational data to real world facts, and vice versa; know limitations and benefits of the relational model approach
  • LO3. work with data stored in a relational database management system: understand table definitions including integrity constraints, extract information through SQL queries, modify information through SQL queries
  • LO4. design a suitable schema which says how information about a particular domain will be stored in a relational DBMS: create a conceptual data model for a domain, produce relational schema (including integrity constraints) from a conceptual model, apply normalisation theory to evaluate or improve a relational schema
  • LO5. understand how application software can use data stored in a relational DBMS, and understand the basic architectural alternatives for data management applications
  • LO6. understand goals, threats, and protection techniques, for ensuring data security and privacy, including use of SQL views, access control, integrity constraints, stored procedures
  • LO7. understand some concepts of dbms implementation that impact on application quality and performance, including query processing, index structures, transactions
  • LO8. connect general database concepts to both theoretical abstract formulations, and details of specific software platforms.
  • LO9. work effectively in a team with members whose skills and interests differ

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities

This section outlines changes made to this unit following staff and student reviews.

This semester, some lab time previously devoted to groups working on assignments, has been replaced by time for the group to consult with a tutor. Assessments have been adjusted to focus on individual practice of all essential skills and understanding; also practice in hand-writing has been introduced to prepare students for the final exam which is hand-written on paper.

Recommended reading is from one at least of the following 4 textbooks:

“Database Systems Concepts” (7th edition, 2019), by A. Silberschatz, H. Korth, S. Sudarshan; Published by McGraw-Hill; isbn: 0078022150

“Database Management Systems” (3rd edition, 2002), by R. Ramakrishnan , J. Gerhke; Published by McGraw-Hill, isbn: 0072465638; in library at 005.74 177A

“Database Systems: The Complete Book” (2nd edition, 2008), by H. Garcia-Molina, J. Ullman, J. Widom; Published by Pearson; isbn: 0131873253; in library: at 005.74 233A

“Database Systems: An Application-Oriented Approach, Complete Version” (2nd edition, 2005) by M. Kifer, A. Bernstein, P. Lewis; Published by Pearson, isbn: 0321268458; in library: at 005.74 221B

Another useful reference is:

SQL Cookbook: Query Solutions and Techniques for All SQL Users (2nd edition, 2020) by A. Molinaro, R. de Graaf; Published by O'Reilly, isbn: 1492077445;



The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

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