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Elements of Data Processing (COMP20008)
Undergraduate level 2Points: 12.5On Campus (Parkville)
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About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 1
Semester 2
Chris Ewin
Overview
Availability | Semester 1 Semester 2 |
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Fees | Look up fees |
AIMS
Data processing is fundamental to computing and data science. This subject gives an introduction to various aspects of data processing including database management, representation and analysis of data, information retrieval, visualisation and reporting, and cloud computing. This subject introduces students to the area, with an emphasis on both tools and underlying foundations.
INDICATIVE CONTENT
The subject's focus is on the data pipeline, and activities known colloquially as 'data wrangling'. Indicative topics covered include:
- Capturing data (data ingress)
- Data representation and storage
- Cleaning, normalisation and filling in missing data (imputation)
- Combing multiple sources of data (data integration)
- Query languages and processing
- Scripting to support the data pipeline
- Distributing a database over multiple nodes (sharding), cloud computing file systems
- Visualisation and presentation
Intended learning outcomes
Having completed this subject the student is expected to:
- ILO 1 - Be able to describe the relationship of the data pipeline to data science
- ILO 2 - Be able to develop and critically evaluate alternative approaches to components of typical data pipelines
- ILO 3 - Apply data processing methodologies to preparing data while managing data quality, system scalability, and usability for decision making
- ILO 4 - Communicate effectively about data processing methodologies in oral form
Generic skills
On completion of this subject, students should have developed the following generic skills:
- An ability to apply fundamental knowledge in reasoning and problem solving
- An ability to undertake problem identification, formulation and solution
- The capacity to solve problems, including the collection and evaluation of information
- The capacity for critical and independent thought and reflection
- Profound respect for truth and intellectual integrity, and for the ethics of scholarship
- An expectation of the need to undertake lifelong learning, and the capacity to do so.
Last updated: 16 August 2023