Overview

This unit introduces students to a range of skills, techniques, technologies and fundamental computer science concepts related to managing data within software systems. Students will learn how to organise data, efficiently search and sort information, as well as apply techniques to optimise these operations. Data management is a critical component in most software systems – knowledge and skills gained in this unit can be applied to a range of different solution domains from enterprise systems to smaller desktop and mobile applications.

Requisites

Prerequisites
COS10009 Introduction to Programming

OR
SWE20004 Technical Software Development
OR
COS30043 Interface Design and Development

Teaching Periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Teaching Period 1
Location
Online
Start and end dates
11-March-2024
09-June-2024
Last self-enrolment date
24-March-2024
Census date
05-April-2024
Last withdraw without fail date
26-April-2024
Results released date
02-July-2024
Semester 2
Location
Hawthorn
Start and end dates
29-July-2024
27-October-2024
Last self-enrolment date
11-August-2024
Census date
31-August-2024
Last withdraw without fail date
13-September-2024
Results released date
03-December-2024
Teaching Period 3
Location
Online
Start and end dates
04-November-2024
09-February-2025
Last self-enrolment date
17-November-2024
Census date
29-November-2024
Last withdraw without fail date
27-December-2024
Results released date
04-March-2025

Learning outcomes

Students who successfully complete this unit will be able to:

  • Appreciate set theory, ternary logic, and algorithmic complexity in the context of data management
  • Select and apply appropriate techniques, tools and methods to sort, search and transform data stored in a variety of data formats
  • Explain the role of data types, data representation, indexing and schemas in managing data, and use methods to validate that data matches an expected schema
  • Select and apply appropriate methods to efficiently store, insert and retrieve data appreciating the underlying trade-offs between different strategies

Teaching methods

Hawthorn

Type Hours per week Number of weeks Total (number of hours)
Live Online
Lecture
2.00 12 weeks 24
On-campus
Class
2.00 12 weeks 24
Specified Activities
Various
1.00 12 weeks 12
Unspecified Activities
Independent Learning
7.50 12 weeks 90
TOTAL150

Sarawak

Type Hours per week Number of weeks Total (number of hours)
Online
Directed Online Learning and Independent Learning
12.50 12 weeks 150
On-campus
Lecture
2.00 12 weeks 24
On-campus
Class
2.00 12 weeks 24
Specified Activities
Various
1.00 12 weeks 12
Unspecified Activities
Independent Learning
7.50 12 weeks 90
TOTAL300

Assessment

Type Task Weighting ULO's
Online TestsIndividual 0% 1,2,3,4 
PortfolioIndividual 100% 1,2,3,4 

Hurdle

As the minimum requirements of assessment to pass a unit and meet all ULOs to a minimum standard, an undergraduate student must have achieved:

(i) An aggregate mark of 50% or more, and (ii) A pass grade for the non-reportable (pass/fail) test. Students who do not successfully achieve hurdle requirement (ii) will receive a maximum of 45% as the total mark for the unit.

Content

Data Fundamentals

  • Set theory
  • Data types, schema and validation
  • Ternary logic and dealing with null values

Data representation

  • Tabular representation (Text, CSV)
  • Hierarchical representation (XML and JSON)
  • Relational representation and basics of normalisation

Data processing and retrieval

  • Searching, sorting and algorithmic complexity
  • Text processing tools and techniques
  • Importing, exporting and transforming data
  • Indexing, B+ -Trees, algorithms and trade-offs
  • Querying with regular expressions, SQL and tree-matching expressions
  • Transactions and concurrent data access

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.