Course Title: Data Analytics

Part A: Course Overview

Course Title: Data Analytics

Credit Points: 12.00


Course Coordinator: Krista Bayliss

Course Coordinator Phone: +61 3 9925 6070

Course Coordinator Email: rmit.training.fs.team.leaders@rmit.edu.au

Course Coordinator Location: Level 4, B108


Pre-requisite Courses and Assumed Knowledge and Capabilities

None.


Course Description

Today, businesses and organisations rely on information curated from a large range of data sources. In this course, students are introduced to methods, techniques and tools which convert and sort data into meaningful visualisations. Given specific data sets, students will organise, synthesise and analyse data, test the validity of the information produced, whilst respecting the legal and ethical considerations in data collection, storage and communication.   Students will produce charts, graphs and infographics which best represent the patterns, trends and relationships between data sets and generate a report which meets the needs of an intended audience.


Objectives/Learning Outcomes/Capability Development

See Learning Outcomes.


Program Learning Outcomes:

  1. Apply the rules of, and expectations for, academic study and assume responsibility for your own actions to work effectively as an individual and/or as a member of a group;
  2. Develop and express ideas through independent reading, the creation of images, and the collection and interpretation of data and information; 
  3. Communicate ideas with clarity, logic, and originality in both spoken and written English;
  4. Construct coherent arguments, narratives or justifications of issues, problems or technical processes when undertaking analytical, practical or creative tasks; and
  5. Use a range of contemporary digital and learning technologies, tools and methods common to the discipline.

Course Learning Outcomes:

  1. Investigate different data types to guide data storage and database design.
  2. Identify and collect data from a range of sources, specific for an intended project, purpose and audience.
  3. Clean and analyse data in line with specific requirements using spreadsheets. 
  4. Use data visualisation software tools to present data trends and information providing insights for an audience.


Overview of Learning Activities

This course includes a blend of didactic, active, and collaborative learning activities designed to meet the needs of international students. The course encourages the process of inquiry, application and reflection through student centred learning and teaching activities including practical work in studio environments and laboratories . In doing so, there will be a focus on the development of critical and analytical thinking skills that promote problem solving, independent research skills and group work. Students will develop their technology skills through engagement in formative and summative assessments. The course will maximise the use of the learning management system by incorporating flipped and blended methodologies. This may be complemented by guest lectures, excursions and speakers with discipline specific work life expertise to further connect content to the professional world and generate opportunities for reflective practice.


Overview of Learning Resources

Various learning resources are available through RMIT’s learning management system,  Canvas. In addition to assessment details and a study schedule, you will also be provided with links to relevant course information, class activities and communication tools. 

Other learning resources are also available online through RMIT Library. Visit the RMIT library website for further details. Academic and learning support is provided through Study Success at RMIT Training. The Foundation Studies home group program will also provide support, navigating university systems, advice on living and studying in Melbourne as well as explaining RMIT university policy and procedures.

Additional resources and/or sources to assist your learning will be identified by your course coordinator and will be made available to you as required during the teaching period.


Overview of Assessment

Assessment Type Assessment Description   Weighting
Application Tasks - Database

Students will be given a scenario that will require them to:

  1. Interpret organisational requirements to design the data tables, defining relationships
  2. Create the database in Excel based on the proposed design
  3. Design the data entry forms and reports using SQL
 40%
Application Task - Spreadsheets

Students will develop a data visualisation solution to a research question.

  1. Written report of the analysis of the research question and proposed solution 10%
  2. Data cleansing, storage and analysis using spreadsheet functions for the proposed solution (15%)
  3. Visual representation of the proposed solution using infographics and charts presenting findings to the research question (15%)
 40%
Structured Tasks

Two written tasks (structured questions) in class exercises that demonstrates skill development taken from any of the following areas; data visualisation – Tableau or other (10%) and security (10%).

 20%