Fundamentals of Data Management
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
OR
SWE20004 Technical Software Development
OR
COS30043 Interface Design and Development
27-October-2024
09-February-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 |
TOTAL | 150 |
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 |
TOTAL | 300 |
Assessment
Type | Task | Weighting | ULO's |
---|---|---|---|
Online Tests | Individual | 0% | 1,2,3,4 |
Portfolio | Individual | 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.