Outline

Overview

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.

Details

Academic unit	Computer Science
Unit code	ISYS2120
Unit name	Data and Information Management
Session, year ?	Semester 2, 2021
Attendance mode	Normal day
Location	Remote
Credit points	6

Enrolment rules

Prohibitions ?	INFO2120 OR INFO2820 OR COMP5138
Prerequisites ?	INFO1113 OR INFO1103 OR INFO1105 OR INFO1905 OR INFO1003 OR INFO1903 OR DECO1012
Corequisites ?	None
Assumed knowledge ?	Programming skills
Available to study abroad and exchange students	Yes

Teaching staff and contact details

Coordinator	Matloob Khushi, matloob.khushi@sydney.edu.au

Type	Description	Weight	Due	Length
Final exam (Open book)		50%	Formal exam period	2 hours
Outcomes assessed:
Tutorial quiz	Weekly in-tutorial quizzes	10%	Multiple weeks	n/a
Outcomes assessed:
Assignment	Assignment 1	10%	Week 04	n/a
Outcomes assessed:
Assignment	Assignment 2	5%	Week 07	n/a
Outcomes assessed:
Tutorial quiz	SQL quiz	10%	Week 07	n/a
Outcomes assessed:
Assignment	Assignment 3	15%	Week 12	n/a
Outcomes assessed:
= group assignment ? = Type C final exam ?

Assessment	Week Due	Weight (%)
Weekly in-tutorial quizzes	Weeks 1-6, 8-12	10
SQL quiz	Week 7	10
Assignment 1	Week 5	10
Assignment 2	Week 7	5
Assignment 3	Week 12	15
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 sydney.edu.au/students/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:

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.

Special consideration

If you experience short-term circumstances beyond your control, such as illness, injury or misadventure or if you have essential commitments which impact your preparation or performance in an assessment, you may be eligible for special consideration or special arrangements.

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.

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction and Administrativa	Lecture (2 hr)
Week 02	The role of data and information management in the enterprise; The Relational Data Model; Simple SQL (SELECT-FROM-WHERE); Entity-Relationship notation for expression of a conceptual data model	Lecture and tutorial (4 hr)
Week 03	Converting an ER conceptual design to a relational schema; SQL schema definition commands (including simple integrity constraints)	Lecture and tutorial (4 hr)
Week 04	Relational algebra and its relationship with SQL; More Complex SQL	Lecture and tutorial (4 hr)
Week 05	Conceptual Data Modelling; Extended Entity-Relationship notation; relational schema design choices for inheritance	Lecture and tutorial (4 hr)
Week 06	Evaluating and improving relational schema; Relational design theory (functional dependencies, Boyce-Codd Normal Form; schema decomposition	Lecture and tutorial (4 hr)
Week 07	Views; Access control; Data Security; Triggers and sophisticated integrity mechanisms	Lecture and tutorial (4 hr)
Week 08	DB Applications (architecture, technology choices, development approaches)	Lecture and tutorial (4 hr)
Week 09	Transactions	Lecture and tutorial (4 hr)
Week 10	Analytic Processing; Data warehouse	Lecture and tutorial (4 hr)
Week 11	Information models and ontologies; Data integration	Lecture and tutorial (4 hr)
Week 12	Indexing and database system tuning	Lecture and tutorial (4 hr)
Week 13	Revision	Lecture and tutorial (4 hr)

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

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.

Outcomes
Graduate qualities

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

LO1. work effectively in a team with members whose skills and interests differ
LO2. understand the SQL mechanisms for basic concepts of data security and privacy
LO3. design a schema which says how information about a particular domain will be stored in a relational DBMS (given a conceptual data model), also be able to apply normalisation theory to evaluate or improve a relational schema, and be able to capture business rules as integrity constraints in a database schema
LO4. 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
LO5. work with data stored in a relational database management system, and understand table definitions including integrity constraints, extract information through SQL queries, modify information through SQL queries, and use views and permissions for security
LO6. understand how application software can use data stored in a DBMS, and understand the basic architectural alternatives for data management applications
LO7. understand the basic concepts of transaction management
LO8. understand the relational data model
LO9. connect general database concepts to both theoretical abstract formulations, and details of specific software platforms.

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
Learning outcomes

Closing the loop

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

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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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Current students

Overview

Details

Enrolment rules

Teaching staff and contact details

Assessment

Assessment criteria

Late submission

Special consideration

Academic integrity

Weekly schedule

Attendance and class requirements

Study commitment

Learning outcomes

Graduate qualities

Outcome map

Closing the loop

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

ISYS2120: Data and Information Management

Overview

Details

Enrolment rules

Teaching staff and contact details

Assessment

Assessment criteria

Late submission

Special consideration

Academic integrity

Weekly schedule

Attendance and class requirements

Study commitment

Learning outcomes

Graduate qualities

Outcome map

Closing the loop

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect