What is Data Analytics?
Data Analytics is all about finding meaning in numbers. Getting data to tell a story. Technically it’s the process of examining data sets to draw conclusions and help businesses make better decisions. Data Analysts comb through huge amounts of raw statistical info, finding patterns, analysing trends and testing theories.
It’s fair to say the world has never needed Data Analysts more. And that’s because we generate a truly staggering amount of data: approximately 2.5 quintillion bytes every single day. Without Data Analytics, all those numbers would be essentially meaningless – digital white noise – but Data Analysts can interrogate data to find useful insights.
How can our business improve efficiency? Where are our marketing dollars best spent? What are our customers interested in? What frustrates them? These are some of the questions Data Analysts try to answer.
Why become a Data Analyst?
There’s a bit of overlap between the fields of Data Science and Data Analytics. (Broadly speaking, Data Science is the umbrella term, while Data Analytics is a more specialised discipline).
There are plenty of reasons to become a Data Analyst. For one thing, it’s in demand: 75 per cent of Internet of Things (IoT) providers consider Data Analytics to be an essential skill, and 68 per cent of them are struggling to find employees with relevant experience. Data Analytics is also a broad, practical skillset.
Here are just a few careers that draw heavily on Data Analysis:
- IT Systems Analyst
- Data Analyst
- Operations Analyst
- UX Designer
- Data Engineer
- Digital Marketing Manager
- Transport Logistics Specialist
5 Reasons To Become A Data Analyst
It’s a growth area
The average salary for Data Analysts in Australia is $94,000 per annum, according to Indeed. Australia also has a well-documented Data Science skills gap, which gives new graduates a strong market position.
It’s in demand
The truth is, tertiary institutions can’t train Data Analysts fast enough. Data careers have grown 650% since 2012, and SEEK is projecting another 12.9% growth over the next five years. All of this points to Data Analytics being a secure, long-term profession.
Analytics is a highly coveted, competitive field. In 2012, Harvard Business Review named Data Scientist the “sexiest job of the 21st century”. Data Science and Analytics also rate incredibly high for job satisfaction: in fact, working with data has been America’s top job three years in a row.
It’s easy to start
Jumping into Data Analytics isn’t as hard as you might think. There are lots of Data Analytics for Beginners courses out there (RMIT Online has several). Once you’ve got some basic knowledge of Data Science, Python coding and predictive analysis, you’re ready to go.
In Data Analytics, you’re not bound to work in a particular industry, or even a particular role. You can use your skills to become a Data Analyst, of course, but you can also be Data Engineer, UX Designer or Digital Marketing Manager. The options are almost endless.
Data Analytics Careers
Why learn Data Analytics? There’s a bunch of reasons. Data Analytics has a job satisfaction of 4.0, according to SEEK, with healthy projected growth over the next five years. It’s a field that’s trending upwards, both in terms of demand and salary expectations.
It’s also a field of opportunity. There’s hardly an industry on Earth that doesn’t benefit from Data Analytics, and the qualification can open a lot of doors.
There are plenty of options for the skilled Data Analyst. Here are just a few:
- IT Systems Analyst | $73,000
- Operations Analyst | $67,000
- UX Designer | $73,000
- Data Engineer | $92,000
- Digital Marketing Manager | $81,000
- Transport Logistics Specialist | $71,000
How to learn Data Analytics for beginners
Learning Data Analytics does require some technical training. If you’re not familiar with number-crunching, you’ll need to learn SQL (Structured Query Language), some Microsoft Excel basics, plus statistical programming languages like R or Python. RMIT Online can get you up to speed, no matter your level of experience.
Our learning content is purpose built for online study and our curriculum is divided into easy-to-follow units. Each unit combines interactive webinars, 1-on-1 tutorials, group work and practical programming tasks. The ultimate goal is to give you the skills you need for a career in Data Analytics.
Here’s a taste of what you’ll need.
- Commitment. Our course content is divided into bite sized chunks, and designed to fit in around your schedule. We recommend studying a few hours every day to stay committed and on track.
- Notes. Your RMIT Online mentors will encourage you to take lots of notes. It’s a good way to flag any potential problems.
- Collaboration. As part of your course, you’ll be working with industry experts, as well as an online peer community.
- Knowledge. Analytics tools are evolving all the time. We’ll help you stay up-to-date with the latest methodologies.
- Resources. There are plenty of great data resources out there. These can help during the course, or even after completion.
Want to learn how to become a Data Analyst? No problem. Check out this blog for some helpful tips.
Learn about Data Analytics
This is the best place to start your Data Analytics journey. Read as much as you can. Ask questions. Contact one of our RMIT Online course counsellors. You can find all of our Data Analytics news and coverage below.
Data Analytics blogs
Want to read more about Data Analytics? Then check out our blog articles below.
RMIT Online Data Analytics Courses
RMIT Online is one of Australia’s top Data Analytics training providers. We offer a range of Data Analytics courses and Data Analytics certificates, depending on your career goals and experience. f you’re just starting your Big Data journey, have a look at our Graduate Certificate in Data Science. After that, you can broaden your knowledge with our Master of Data Science Strategy and Leadership and Data Privacy short course.
Topics and courses similar to Data Analytics
Data Analytics is such a versatile discipline. You can use it almost anywhere. It also touches on plenty of other fields, like Artificial Intelligence and Machine Learning, Python programming, Business Analytics and UX design. If you’d like to expand your CV, check out RMIT Online’s related courses below.