Data Analysts: What Do They Do, and Why Are They In Demand?
What are data analysts, anyway?
Learn more about what they do, and figure out whether this job is the right one for you.
What is a data analyst?
Data analysts look through data, discover trends and use this pertinent information to help clients with their decision-making. They organise and analyse statistical data using a variety of tools for the benefit of businesses.
When it comes to pure data analytics, there are four types of analytics that businesses use. You should be familiar with the purpose of each if you decide to go down this pathway.
Data analyst job description
Data analysts concern themselves with finding the answers that businesses want, like how to enhance customer satisfaction. They do this by distributing surveys or extracting information from the relevant database for data collection. Then, they verify that data for accuracy.
Once they finish their analysis and undertake the proper market research, they compile reports in straightforward terms to share these insights with the relevant team leaders and company stakeholders.
There is a high demand for data analysts, and employers are willing to pay a high wage for one.
Data generation is increasing every second and customers always expect businesses to know exactly what they want. For this reason, data analyst salaries are high even in entry-level positions. Typically, entry-level data analysts in Australia earn $78,075 per annum.
Who employs data analysts?
Data analysts can work in a range of environments. Though they mainly work in investment banks and private equity firms, you can also find them in:
Degree or VET
A bachelor’s degree in statistics, economics or mathematics is usually required to become a data analyst. Some workers have a relevant VET qualification instead, such as a Certificate or Diploma.
A master’s degree in data science or data analytics is beneficial if you want to advance your career, though it isn’t technically necessary, as ‘data analyst’ is an entry-level position. However, if you want to become a data scientist, you should definitely consider a masters, as it is a more advanced role, where you’ll be dealing with more complex datasets. Work experience, ideally while completing the degree, is also integral to increasing your prospects. Browse masters level data courses.
Short courses & bootcamps
For a less traditional route, you have the option to complete short courses, like a graduate certificate in cybersecurity or a certificate in data science collection. These can fill in any gaps in your knowledge, such as learning a new programming language or allowing you to specialise in a particular branch of data analysis, like cybersecurity. They’re especially relevant if you’re already working, since these courses are flexible enough to slot easily into your schedule while also teaching you industry-relevant skills. You can also use them to get credit for your bachelor’s or as a cost-effective way to see if you want to continue down this pathway.
What skills do you need?
Data analysts need a very specific skill set, particularly with computer applications, like:
And programming languages, such as:
Other soft skills data analysts need include:
Your job revolves around being presented with a problem, asking related questions and finding answers to them to inform their company’s business decisions, in addition to solving any technical issues along the way.
Analysts will typically communicate through phone calls and emails with their colleagues, data suppliers and stakeholders, along with their written report.
Attention to detail
Data analysts will need to read lots of code, and ensure that the coding used contains no errors.
Data analysts should have a firm understanding of statistical analysis, such as regression analysis.
Converting all the data into something more accessible, such as through visual aids.
A day in the life of a data analyst
One of the best ways to determine whether a job is right for you is to take a deep dive into a typical workday. Here’s an account from Jesse, a data analyst at a marketing company:
A normal day in my life as a data analyst is going to be broken up into three key activities: briefing, research and presentation.
The first of these activities, briefing, is the simplest. I meet with a co-worker or stakeholder who has a question that they would like answered. Perhaps they would like to know how effectively our business appeals to different demographics, or perhaps they would like to know how innovations in our business are being received by our clients.
Regardless of what it is, they have an abstract question, and my role is to take this abstract question, break it down and devise a way to answer it empirically using data.
This brings me to the second activity, research, which takes by far the largest amount of my time. I obtain all relevant data to the question at hand, then use my skills, knowledge and technology to break down this data and find out what it is really telling us.
Finally, the most often overlooked — yet extremely important — step: presentation. Improperly presented data can be misleading and deceiving. Thus I work to present the data and my findings in a way that is as clear, concise and accurate as possible.
When this is ready, I once again meet with the one who initially came to me with the question. I explain my findings and do everything in my power to answer their initial question.
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