Updating for Course Architecture redevelopment

1/9/2015 - Updated for course architecture programs. Effective Semester 1, 2016.

22/03/17: Wray Buntine -- modification for new rules for assessment

12/06/2017: Admin - updating location of offering to reflect actual campus offerings at the ADE's request.

25/06/2018: Admin - adding reasons for change - Update to assessment removing the 30 minute reading and noting time from the exam.

19/9/2019: Admin - updating exam duration to include additional 10 minutes as per University requirement.

03/02/20: Admin - minor amendment to wording of workload activity. Removing mention of tutes and pracs, as they are not run in this unit.

25/09/2020 Admin: Update to include new assessment and teaching approach fields as per Handbook requirements.

This unit is core in the Data Science stream of the BCS. It is an elective for other students in the BCS.

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

1. explain the role of data in different styles of business;
2. demonstrate the size and scope of data storage and data processing, and classify the basic technologies in use;
3. identify tasks for data curation and management in an organisation;
4. classify participants in a data science project: such as statistician, archivist, analyst, and systems architect;
5. classify the kinds of data analysis and statistical methods available for a data science project;
6. locate suitable resources, software and tools for a data science project.

020399

This unit looks at processes and case studies to understand the many facets of working with data, and the significant effort in Data Science over and above the core task of Data Analysis. Working with data as part of a business model and the lifecycle in an organisation is considered, as well as business processes and case studies. Data and its handling is also introduced: characteristic kinds of data and its collection, data storage and basic kinds of data preparation, data cleaning and data stream processing. Curation and management are reviewed: archival and architectural practice, policy, legal and ethical issues. Styles of data analysis and outcomes of successful data exploration and analysis are reviewed. Standards, tools and resources are also reviewed.

Technological requirements

Students must regularly check Moodle for announcements. Some content will be provided via videos, audio, PDF and ePUBs so students must have a suitable laptop or similar to access the content.

On-campus

Active learning: students participate/interact with the learning process.

Lecture and tutorials This teaching and learning approach helps students to initially encounter information at lectures, discuss and explore the information during the tutorials/labs, and implement solutions in tutorials/labs.

Examination (2 hours and 10 minutes): 50% ; In-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

(a.) Contact hours for on-campus students:

(b.) Additional requirements (all students):

FIT