A digital world combined with data capture make analytics an essential, in-demand skill. Create rewarding career opportunities by studying for a Graduate Certificate in Data Analytics online. You'll learn how to convert data into useful, insightful information that businesses want.
We having exploding volumes of data available to us but not enough expertise to use it properly. The demand for analytical skill will keep growing as businesses strive to convert raw data into information and insights that decision makers can exploit.
Skilled data analysts are some of the most sought-after professionals in the world. Because the demand is so strong, and the supply of people who can truly do this job well is so limited, data analysts command huge salaries and excellent perks, even at the entry-level. - Investopedia
A postgraduate course is useful to build skill foundations for an analytical career or gain specialist training. A grad cert also serves as a platform for further study. Online learning means your analyst education is available part-time when you want, with courses designed for working professionals.
The four-subject Graduate Certificate in Data Analytics is the shortest course in this field that's accredited by Australian universities. An accelerated, 100% online course allows you to earn the postgraduate qualification over 8 months of part-time study. You can choose elective units to gain a broad introduction or build knowledge in targeted, specialist areas.
Graduate Certificate in Analytics at UNSW Online
Choice and flexibility are features of the Graduate Certificate in Analytics from UNSW Online. You select four from the 14 subjects contained in the Master of Analytics program. Each subject is 100% online and can be completed part-time over 7 weeks. Without needing time off work, you can do this course in under 8 months. Subjects include: introductory data analysis, predictive analytics, data visualisation and communication, managing customer analytics, and big data management. The course is open to graduates (any discipline) and professionals with 3+ years of experience.
If you like the sound of an analytics career but are drawn to the company decision-making side of it, a business analytics graduate certificate may be a good option.
The difference between data and business analysts can be subtle. Generally, a business analyst will be removed from database operations and more concerned with boardroom activities. They pragmatically seek to exploit data to inform business managers and leaders.
A grad cert in business analytics will tend to emphasise the use of analytical tools for reporting and presentations... READ MORE
An alternative to analytics is data science, for which similar postgraduate courses are available. in this discipline, you'll likely need to go beyond a grad cert however.
Data scientists focus more on combining, structuring and cleaning large datasets. As well, data they may write machine learning algorithms for statistical data analysis and to generate artificial intelligence.
While the analytics and data science professions overlap, data science is more challenging in terms of the skills required. The job also tends to be more coding intensive... READ MORE
You have flexibility about what you study in a Graduate Certificate of Data Analytics. The UNSW Graduate Certificate in Analytics offers 14 subjects, from which you only need to choose four.
To give you an idea of course structure, here are a couple of example courses we've constructed from the UNSW analytics program.
Example course: "data analytics essentials"
- Introductory Data Analysis
- Principles of Programming
- Big Data Management
- Data Visualisation and Communication
Example course: "business analytics"
- Introductory Data Analysis
- Business Analytics and Consulting
- Financial Modelling
- Decision Making in Analytics
As a flexible, short course, a grad cert in data analytics produces different learning outcomes depending on the subjects you take. Since this is a practical discipline, you should, however, expect to come away with applied skills for immediate use. Some examples are the ability to:
- identify methods by which quantitative or qualitative data can be analysed and presented
- use business analytics tools to produce descriptive, predictive and prescriptive analytics
- develop people management strategies to make analytics processes successful
- complete programming tasks for structuring data, debugging results, and creating reports
- use data visualisation techniques to identify data patterns and present visual narratives.
For career success, the learning should continue after the course. Having gained foundational knowledge, graduates are primed for further training. They're also well positioned to adapt or add to their skill set to meet specific workplace demands.
Earning a grad cert in the field of applied data analytics qualifies you for data analyst and related jobs. You can become a data or business analytics specialist or use your skills to complement a career as an adviser, manager or decision maker.
How competitive you'll be in the labour market depends on your other qualifications and prior experience. If you lack professional experience and a relevant degree, further study to earn a grad dip or master's degree may be advisable to boost your career trajectory.
Job opportunities in Australia are abundant for skilled analysts. Any search for "data analyst" jobs in major employment directories returns thousands of results. We found 17,333, 2,672 and 38,338 job vacancies at Seek, Indeed and Jora respectively (on 23 August 2022). While not all these jobs may be ideal for grad dip graduates, there are clearly plenty of jobs available.
Analytical expertise is in demand across the Australian economy; wherever data-driven decisions advantage firms. Some examples of industries with high demand include digital marketing, software development, pharmaceuticals, management consulting, cyber security, manufacturing, financial services, telecommunications, e-commerce services, retail, healthcare, and public services.
Entry requirements for a data analytics graduate certificate are typically that you have a bachelor degree (any discipline) OR significant experience in a relevant role. The course has relatively relaxed admission requirements and often serves as a pathway for entry into masters programs.
For the Graduate Certificate in Analytics from UNSW Online, the entry requirements are a bachelor degree (any discipline) or 3+ years of relevant professional or managerial experience.
Successfully completing the course with a WAM of 65+ qualifies you for entry into the Graduate Diploma and Masters program.
English language proficiency requirements apply if you're an international student from a non-English speaking background with international qualifications.
Fully online programs are unsuitable for international students coming to Australia to study on a student visa.
Key dates: Intakes are available in January, March, May, July, September and October.
FEE-HELP loans from the Australian Government are automatically available for Australian students to cover tuition fees. Loans are paid back gradually based on your annual taxable income.
The pathways to become an analyst are many but it's generally recommended that you start with a bachelor degree in a relevant discipline.
1. Complete a relevant bachelor degree
The obvious undergraduate degrees to go for are computer science, information technology or similar, or a statistics or mathematics degree. In Australia, these disciplines are generally available as majors within a Bachelor of Science degree. You can choose subjects from the different departments to create the ideal program for a data analytics career. For example, you could finish up with a Bachelor of Science with a double-major in Computer Science and Statistics.
2. Invest in postgraduate education
After finishing your degree, you may be ready to apply for entry-level jobs and to build your career from there. If you have any important knowledge or skills gaps, especially if your bachelor program was not ideal, further study may be beneficial if not essential. That's where a Graduate Certificate of Data Analytics comes into play, with the option to continue on for a graduate diploma or masters.
3. Do further professional development as required
You can also build up your skill set through free online courses and self-education. This is may be an important part of your professional development, especially to gain specific skills that you find you need at work.
Being able to code is a requirement to be a good data analyst. However, you generally won't have to do heavy coding as a daily part of your job.
Three programming languages commonly used are SQL for database access, Python for data modelling and Tableau for visual presentations. Familiarity with these and related or comparable languages may be sufficient for the vast majority of roles.
Minimal coding knowledge may be needed if your job is mainly to use analytical tools on well-defined datasets. As an analytics manager, you also don't have to program as a routine part of your job.
If you love programming and advanced statistics, you may prefer to work as a data scientist. If you mainly want to help steer the strategic directions of businesses, and avoid programming, a business analytics career may be ideal.
A key difference between analytics and data science is the amount of coding required. Data scientists are responsible for cleaning and combining raw, unstructured and often messy data sets. They also do data mining to make datasets functional, and build machine learning and statistical models to identify relationships between variables. All this requires advanced programming skills.
Data analysts are more interested in identifying historical patterns in data to give practical, easily understood information for data-driven decision making. They may also be involved in business analytics, where the focus is squarely on solving business problems. In this role, the job is to interpret data patterns for the benefit of answering specific business questions.
You can think of data analytics as sitting somewhere in the middle, where you need to be skilled at coding and other technical tasks while also keeping a close eye on how the information will ultimately be used. You won't be buried in code each day but also should feel comfortable with programming.
For postgraduate courses in data analytics and similar, online study is designed for working professionals. You'll study as part of a virtual class, meaning you'll have classmates that you can connect with online. There'll likely be weekly assignments and other tasks to keep you on track.
All content will be available for easy access online. You generally won't have to be online at specific times, meaning your studies won't interfere with work or other commitments.
For accelerated courses, the usual study pattern is to complete one subject every couple of months. The unit is completed from start to finish during a study period of 6-7 weeks. Exams are usually not part of it, with assessment based on assignments, quizzes, projects, etc. Studying part-time this way, you can do six subjects per year.
Lecturers, tutors and any other instructors will be available online at certain times. You'll also be assigned a student success advisor to help with any non-academic matters.
If you have any interest in extracting value out of data, an analytics course seems worthwhile. An advantage of graduate certificate programs is that they are relatively short, consisting of four subjects, and give you the option to continue studying for a graduate diploma or masters degree.
With data having become so vital to business performance, it's hard to see a downside to gaining skills in this field. You also have the flexibility to adjust your education program to make it broad and introductory or focused on specialist skills.
By earning the grad cert, you position yourself to work as a data analyst. The kinds of jobs you could go for include advertising analyst, big data specialist, business analyst, business intelligence specialist, customer success analyst, database analyst, financial analyst, information security analyst, market research analyst, marketing analyst, operations analyst, organisational development specialist, pricing analyst and sales analyst.
Working with data analytics
In many other roles, knowledge of and familiarity with data analytics are important. You may work in partnership with analysts, manage them, be involved with commissioning their work or use their results. To do your job effectively, you should appreciate the potential for analytics as well as the processes involved in gathering data and producing analytical reports.