UO Big Data in the Cloud

Undergraduate | 2026

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Area/Catalogue
INFO 3023
Course ID icon
Course ID
203929
Level of study
Level of study
Undergraduate
Unit value icon
Unit value
6
Course level icon
Course level
3
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Inbound study abroad and exchange
Inbound study abroad and exchange
The fee you pay will depend on the number and type of courses you study.
Yes
University-wide elective icon
University-wide elective course
Yes
Single course enrollment
Single course enrolment
Yes
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Note:
Course data is interim and subject to change

Course overview

The aim of this course is to interoperate with cloud based information systems in order to extract meaningful data for analysis and publish visualisations. The aim of this course is topics covered in this course include: overview of big data analytics; characteristics of big data; analysis flow for big data; big data manipulation techniques: batch analytics (Hadoop Map-Reduce), real-time analytics, interactive querying; big data languages/tools: Pig, Oozie, Spark, Strom, Hive; big data search: Solr, Elasticsearch; big data applications (e.g. recommendation systems, time series analysis, text analytics); and web framework: Django.

Course learning outcomes

  • Analyse how data analytics on big data can be used within an organisation to improve current processes and decision making, and to enhance the organisation's capabilities or products.
  • Describe the data analytics lifecycle for big data and apply it to constrained problems in big data analytics.
  • Select an appropriate big data analytics tool and apply it to a problem involving big data.
  • Communicate appropriately with professional colleagues through visualisation and report.

Prerequisite(s)

N/A

Corequisite(s)

N/A

Antirequisite(s)

N/A