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Unit outline_

ISYS2120: Data and Information Management

Semester 2, 2022 [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

Academic unit Computer Science
Credit points 6
Prerequisites
? 
INFO1113 OR INFO1103 OR INFO1105 OR INFO1905 OR INFO1003 OR INFO1903 OR DECO1012
Corequisites
? 
None
Prohibitions
? 
INFO2120 OR INFO2820 OR COMP5138
Assumed knowledge
? 

Programming skills

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Alan Fekete, alan.fekete@sydney.edu.au
Type Description Weight Due Length
Final exam (Record+) Type B final exam Final Exam
Final Exam, done online through Canvas
50% 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
10% Multiple weeks n/a
Outcomes assessed: LO3
Assignment group assignment Assignment 1 (Relational schema)
Produce a relational schema from a conceptual model
5% Week 04
Due date: 28 Aug 2022 at 23:59
n/a
Outcomes assessed: LO2 LO4 LO9
Assignment group assignment Assignment 2 (Conceptual Model)
Produce a conceptual model for a domain
5% Week 07
Due date: 18 Sep 2022 at 23:59
n/a
Outcomes assessed: LO4 LO9
Assignment group assignment Assignment 3 (Data-backed Application and Security)
extend skeleton code base for extra functionality and security
15% Week 11
Due date: 23 Oct 2022 at 23:59
n/a
Outcomes assessed: LO5 LO6 LO9
Assignment group assignment Assignment 4 (Concepts)
Answer questions on unit concepts, especially those using theory
5% Week 12
Due date: 30 Oct 2022 at 23:59
n/a
Outcomes assessed: LO4 LO5 LO6 LO7 LO8
Online task Weekly online quizzes
Online quizzes, due weekly
10% Weekly n/a
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8
Group assignment with individually assessed component = group assignment with individually assessed component ?
Type B final exam = Type B final exam ?

Assessment summary

Assessment

Week Due

Weight (%)

Weekly online quizzes

Weekly

10

SQL tasks

Multiple weeks

10

Assignment 1 

Week 4

5 (1 for individual contribution, 4 for the group outcome)

Assignment 2 

Week 7

5 (1 for individual contribution, 4 for the group outcome)

Assignment 3 

Week 11

15 (5 for individual contribution, 10 for the group outcome)

Assignment 4 

Week 12

5 (1 for individual contribution, 4 for the group outcome)

Final Exam

Exam Weeks

50

 

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

Description

High distinction

85 - 100

 

Distinction

75 - 84

 

Credit

65 - 74

 

Pass

50 - 64

 

Fail

0 - 49

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

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 weekly online quizzes or SQL tasks. On Assignments, for every calendar day up to and including ten calendar days after the due date, a penalty of 5% of the maximum awardable marks will be applied to late work (except with academic plan, special consideration, or simple extension).

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.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

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 and tutorial (4 hr) LO2 LO3 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 and tutorial (4 hr) LO3 LO4
Week 04 Relational algebra and its relationship with SQL; More Complex SQL (including subqueries, handling of nulls, outer joins) Lecture and tutorial (4 hr) LO2 LO3 LO8
Week 05 How to produce a conceptual data model for a domain; review of conversion from conceptual model to relational schema Lecture and tutorial (4 hr) LO2 LO4
Week 06 Evaluating and improving relational schema; Relational design theory (functional dependencies, Boyce-Codd Normal Form; schema decomposition) Lecture and tutorial (4 hr) LO2 LO4 LO8
Week 07 DB Applications (architecture, technology choices, development approaches) Lecture and tutorial (4 hr) LO5
Week 08 Data security and privacy - goals, attacks, protection mechansims (views; access control; triggers and sophisticated integrity mechanisms; stored procedures, anonymization, data perturbation) Lecture and tutorial (4 hr) LO6
Week 09 Application architecture Tutorial (2 hr) LO5
Week 10 overview of dbms implementation concepts (physical storage including indexes, buffers; query processing); performance tuning Lecture and tutorial (4 hr) LO7 LO8
Week 11 More on dbms implementation concepts, including transactions and security and privacy support Lecture and tutorial (4 hr) LO7 LO8
Overview of enterprise-scale data management; data integration Lecture and tutorial (4 hr) LO1 LO5 LO8
Week 13 Revision, exam preview Lecture and tutorial (4 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, directed computer laboratory exercises, self-learning SQL exercises (`SQL Challenge`), assessed assignments, and a small practical database project. 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, an SQL online tutorial, and also practice in problem-solving related to the content.
  • Independent Study: Work on assignments and homeworks, reading material from notes/references, etc; this should allow students to engage with the material and to integrate it into their understanding. 5 hours independent study is expected each week.
  • Project Work (own time): Group Work on a practical database application project assignment (extra to time provided in Lab sessions). 3 hours of project work is expected each week.

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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

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

Assignment percentage has been adjusted and final exam will be conducted online.

Disclaimer

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

To help you understand common terms that we use at the University, we offer an online glossary.