Graduate Certificate in Data Analytics Online

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 an analytics grad cert 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.

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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.

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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 patterns for the benefit of answering specific business questions.

You can think of 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.

Related: Skills for Data Science and the Data Scientist

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.

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If you have any interest in extracting value out of data, a data analytics course is generally worthwhile. Key advantages of graduate certificate programs are that they are relatively short, consisting of four subjects, and give you the option to continue studying for a grad dip 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.

Specialist roles

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.