Why Bachelor of Data Analytics?
Got a head for numbers? Excel in the fast-paced world of big data and build a rewarding career with this 100% online degree.
Turn your passion into a lucrative career leading data-driven solutions for businesses, leveraging the global demand for professionals who can turn data into valuable insights.
You’ll develop a sought-after data analytics skillset strengthened by core information technology and statistics knowledge, and complemented by hands-on experience and practical learning opportunities. Graduate with the skills to interpret big data, engineer advanced solutions to complex challenges and apply your versatile qualification to the digital roles of tomorrow.
Overview
Our online data analytics degree is an opportunity to propel yourself into the booming field of data science. Take advantage of the strong demand for professionals who can transform large sets of data into meaningful insights. Use your skills to make informed decisions, drive business growth and increase competitive advantage.
From data visualisation and cloud computing to data mining and database administration, you’ll gain a holistic understanding of data analytics and its role in modern business. Enhance your knowledge of big data by honing your critical programming, maths and statistics skills and complete specialised courses examining data analytics in social media, digital marketing and sales patterns.
Study a curriculum designed in collaboration with industry and strengthened by practical experience and real-world case studies. Graduate with a highly competitive skillset aligned to current demand and informed by the latest industry innovations.
Key features
Understand the life cycle of data, including how information is created, gathered, processed, used and analysed with a degree co-developed by industry and expert academics. - Learn how to analyse and visualise rich data sources, identify data trends and generate data management strategies.
- Explore emerging trends such as cloud computing, machine learning, artificial intelligence, and text and social media analytics.
- Become fluent in R and Python coding languages and access data analytics software used by industry professionals.
- Study a 100% online degree co-developed by industry leaders and Adelaide University’s expert academics.
What you'll learn
Our Bachelor of Data Analytics focuses on innovative and future-focused trends emerging across the growing data analytics sector. Build advanced knowledge and skills employers are looking for and join an in-demand field.
Explore foundational topics across data analytics, complemented by key courses in information technology, maths and statistics. Discover specialist courses aligned to contemporary practice and become proficient in the tools and techniques used by industry professionals, such as R language, Tableau and Snowflake’s Data Cloud. Learn how to use cloud-hosting platforms to inform strategy, along with digital infrastructure and software including Amazon Web Services (AWS), Azure and Google Cloud. Maximise your employability with valuable skills in social media analytics, machine learning, artificial intelligence and predictive analysis.
Study diverse range of topics during your degree, including:
- Problem solving and programming
- Machine learning
- Big data in the cloud
- Data visualisation
- Data acquisition and wrangling
- Professional practice in data analytics
- Data driven web technologies.
Our practical, hands-on approach to learning means you’ll gain real-world experience. Complete a capstone project where you’ll collaborate with an organisation to solve a real business challenge and deliver a data-informed solution.
Graduate with the highly sought-after communication skills you’ll need as data analytics professional. You’ll be prepared to present ideas and reports to stakeholders across all levels of an organisation.
What courses you'll study
Complete 144 units comprising:
- 132 units for all Core courses, and
- 12 units for Electives
Complete 132 units for ALL of the following:
| Course name | Course code | Units | |
|---|---|---|---|
|
Course name
UO Problem Solving and Programming
|
Course code
COMP1021
|
Units
6
|
|
|
Course name
UO Object Oriented Programming
|
Course code
COMP1023
|
Units
6
|
|
|
Course name
UO Applied Data Structures
|
Course code
COMP2026
|
Units
6
|
|
|
Course name
UO Information Technology Fundamentals
|
Course code
INFO1020
|
Units
6
|
|
|
Course name
UO Professional Practice in Data Analytics
|
Course code
INFO1023
|
Units
6
|
|
|
Course name
UO System Requirements and User Experience
|
Course code
INFO1025
|
Units
6
|
|
|
Course name
UO Data Driven Web Technologies
|
Course code
INFO1026
|
Units
6
|
|
|
Course name
UO Experimental Design
|
Course code
INFO2027
|
Units
6
|
|
|
Course name
UO Cloud Platforms
|
Course code
INFO2028
|
Units
6
|
|
|
Course name
UO Data Acquisition and Wrangling
|
Course code
INFO2029
|
Units
6
|
|
|
Course name
UO Database for the Enterprise
|
Course code
INFO2030
|
Units
6
|
|
|
Course name
UO Capstone Project 1
|
Course code
INFO3013
|
Units
6
|
|
|
Course name
UO Capstone Project 2
|
Course code
INFO3014
|
Units
6
|
|
|
Course name
UO Machine Learning
|
Course code
INFO3016
|
Units
6
|
|
|
Course name
UO Data Visualisation
|
Course code
INFO3017
|
Units
6
|
|
|
Course name
UO Predictive Analytics
|
Course code
INFO3018
|
Units
6
|
|
|
Course name
UO Advanced Topics in Data Analytics
|
Course code
INFO3022
|
Units
6
|
|
|
Course name
UO Big Data in the Cloud
|
Course code
INFO3023
|
Units
6
|
|
|
Course name
UO Text and Social Media Analytics
|
Course code
INFO3024
|
Units
6
|
|
|
Course name
UO Fundamentals of Mathematics for Data Analytics
|
Course code
MATH1033
|
Units
6
|
|
|
Course name
UO Mathematics Essentials in Data Analytics
|
Course code
MATH1034
|
Units
6
|
|
|
Course name
UO R for Data Analytics
|
Course code
MATH2018
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
| Year 1 | |||
 |
Course name
UO Critical Approaches to Online Learning
|
Course code
SOCI3014
|
Units
6
|
|
Course name
UO Professional Practice in Data Analytics
|
Course code
INFO1023
|
Units
6
|
|
Course name
UO Information Technology Fundamentals
|
Course code
INFO1020
|
Units
6
|
|
Course name
UO Fundamentals of Mathematics for Data Analytics
|
Course code
MATH1033
|
Units
6
|
|
Course name
UO Problem Solving and Programming
|
Course code
COMP1021
|
Units
6
|
|
Course name
UO R for Data Analytics
|
Course code
MATH2018
|
Units
6
|
|
Course name
UO Data Driven Web Technologies
|
Course code
INFO1026
|
Units
6
|
|
Course name
UO Object Oriented Programming
|
Course code
COMP1023
|
Units
6
|
| Year 2 | |||
|
Course name
UO Mathematics Essentials in Data Analytics
|
Course code
MATH1034
|
Units
6
|
|
Course name
UO Data Acquisition and Wrangling
|
Course code
INFO2029
|
Units
6
|
|
Course name
UO Cloud Platforms
|
Course code
INFO2028
|
Units
6
|
|
Course name
UO Applied Data Structures
|
Course code
COMP2026
|
Units
6
|
|
Course name
UO Database for the Enterprise
|
Course code
INFO2030
|
Units
6
|
|
Course name
UO System Requirements and User Experience
|
Course code
INFO1025
|
Units
6
|
|
Course name
UO Data Visualisation
|
Course code
INFO3017
|
Units
6
|
|
Course name
UO Predictive Analytics
|
Course code
INFO3018
|
Units
6
|
| Year 3 | |||
|
Course name
UO Experimental Design
|
Course code
INFO2027
|
Units
6
|
|
Course name
UO Big Data in the Cloud
|
Course code
INFO3023
|
Units
6
|
|
Course name
UO Text and Social Media Analytics
|
Course code
INFO3024
|
Units
6
|
|
Course name
|
Course code
-
|
Units
6
|
|
Course name
UO Capstone Project 1
|
Course code
INFO3013
|
Units
6
|
|
Course name
UO Machine Learning
|
Course code
INFO3016
|
Units
6
|
|
Course name
UO Capstone Project 2
|
Course code
INFO3014
|
Units
6
|
|
Course name
UO Advanced Topics in Data Analytics
|
Course code
INFO3022
|
Units
6
|
Complete 12 units comprising:
- 12 units from Program electives
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
UO Critical Approaches to Online Learning
|
Course code
SOCI3014
|
Units
6
|
|
|
Course name
Elective 1
|
Course code
AUXX1011
|
Units
6
|
|
|
Course name
Elective 2
|
Course code
AUXX1012
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
| Year 1 | |||
|
Course name
UO Critical Approaches to Online Learning
|
Course code
SOCI3014
|
Units
6
|
|
Course name
UO Professional Practice in Data Analytics
|
Course code
INFO1023
|
Units
6
|
|
Course name
UO Information Technology Fundamentals
|
Course code
INFO1020
|
Units
6
|
|
Course name
UO Fundamentals of Mathematics for Data Analytics
|
Course code
MATH1033
|
Units
6
|
|
Course name
UO Problem Solving and Programming
|
Course code
COMP1021
|
Units
6
|
|
Course name
UO R for Data Analytics
|
Course code
MATH2018
|
Units
6
|
|
Course name
UO Data Driven Web Technologies
|
Course code
INFO1026
|
Units
6
|
|
Course name
UO Object Oriented Programming
|
Course code
COMP1023
|
Units
6
|
| Year 2 | |||
|
Course name
UO Mathematics Essentials in Data Analytics
|
Course code
MATH1034
|
Units
6
|
|
Course name
UO Data Acquisition and Wrangling
|
Course code
INFO2029
|
Units
6
|
|
Course name
UO Cloud Platforms
|
Course code
INFO2028
|
Units
6
|
|
Course name
UO Applied Data Structures
|
Course code
COMP2026
|
Units
6
|
|
Course name
UO Database for the Enterprise
|
Course code
INFO2030
|
Units
6
|
|
Course name
UO System Requirements and User Experience
|
Course code
INFO1025
|
Units
6
|
|
Course name
UO Data Visualisation
|
Course code
INFO3017
|
Units
6
|
|
Course name
UO Predictive Analytics
|
Course code
INFO3018
|
Units
6
|
| Year 3 | |||
|
Course name
UO Experimental Design
|
Course code
INFO2027
|
Units
6
|
|
Course name
UO Big Data in the Cloud
|
Course code
INFO3023
|
Units
6
|
|
Course name
UO Text and Social Media Analytics
|
Course code
INFO3024
|
Units
6
|
|
Course name
|
Course code
-
|
Units
6
|
|
Course name
UO Capstone Project 1
|
Course code
INFO3013
|
Units
6
|
|
Course name
UO Machine Learning
|
Course code
INFO3016
|
Units
6
|
|
Course name
UO Capstone Project 2
|
Course code
INFO3014
|
Units
6
|
|
Course name
UO Advanced Topics in Data Analytics
|
Course code
INFO3022
|
Units
6
|
Career outcomes
A career in data analytics is flexible, fast-paced, and transferrable to a range of global industries. As businesses harness data to remain competitive, demand for data analysts to effectively extract, translate, visualise, and communicate these insights is soaring.
Data analytics is not just reserved for big tech giants. Data analysts are required in almost every industry – including in health, education, retail, telecommunications, financial services and management consulting. This means your degree will open a world of career possibilities.
You could pursue a career as a data scientist, generating insights from data sets to guide high-level strategies for global organisations. Maybe you’ll work as a data architect, working with new technologies to capture and optimise data across healthcare, retail or the financial sector.
You could also pursue the following careers:
- Business intelligence strategist
- Information analyst
- Data visualisation specialist
- Market research analyst
- Financial analyst
- Machine learning engineer
- Healthcare data analyst
- Statistician
- Big data architect.
Industry trends
The explosion in device connectivity, digitisation and increasing data volumes, coupled with the rise of social media and new technologies, is fuelling exponential growth in big data and data analytics. As businesses harness the power of data to remain competitive, demand for data analysts who can effectively extract, translate, visualise, and communicate information is soaring.
A career in data analytics is lucrative and rewarding, with data analysts in Australia earning an average annual salary of over AUD$108,000 in 2024 (Talent.com, 2024). The digital nature of data analysis also allows for a versatile and flexible career, with professionals often consulting for global organisations from anywhere in the world.
Your study experience and support
Studying 100% online with Adelaide University means joining a dynamic community of learners – all supported by dedicated teams committed to your success. From day one to graduation, you’ll have access to comprehensive academic, student and technical support teams to ensure you get the most out of your online learning journey.
Student support services
Need help with enrolments, managing your study load, or setting your academic goals? Our student support team is here to assist. They’re your first point of contact for advice and are available seven days a week, including out-of-hours and on weekends. Get the help you need – when it suits you.
As an online student, you’ll also have access to our specialised on-campus student support services. Whether you’re looking for career advice, health and wellbeing support, international student assistance, accessibility services, or something else, we’ve got you covered. Visit the Support webpage to explore the services available.
Online academic support
From understanding course content to tackling assignments, writing, and referencing, our expert academics are here to guide you. Available seven days a week, they’ll provide personalised support to help you progress through your studies.
Tech support
We’ve got your back when it comes to technology. Our IT support team is available 24/7 to resolve any tech challenges you might face. With fast response times and tailored solutions, we’ll ensure nothing stands in your way. You’ll also enjoy free access to software downloads required for your program.
Study hours
Adelaide University’s 100% online programs offer the flexibility to fit your lifestyle. You can engage with course materials at any time that works for you – there’s no need to log in at set times. To stay on track, we recommend setting aside 10 to 15 hours per week for each course, but you can adapt your schedule and your study load to suit your needs.
Assessment
All assessments, including exams (if required) are conducted 100% online – so you’ll never need to travel to submit an assignment or sit an exam. Depending on your program, your assessments might include:
- An industry-relevant project or case study
- An online presentation
- Essays and reports.
