Data analytics skills are in huge demand. And after the global disruption of the last few years, both recent graduates and established professionals are looking to future-proof their careers. Again, data analytics is a great option. In fact, according to the U.S. Bureau of Labor Statistics, computer and information research roles (including junior data analysts) are expected to grow by 22% by 2030.
Data analytics is a diverse and evolving field that requires a broad set of skills. But it also offers flexible career choices, with numerous pathways towards your dream job. In this introductory guide, we will explore everything you need to know to become a junior data analyst. Once you’re done, you should have a solid idea of the skills you’ll need, the training options available, and how much you might be able to earn. We’ll answer:
- What is data analytics?
- What does a junior data analyst do?
- What skills do junior data analysts need?
- How much can junior data analysts earn?
- Where can I find junior data analyst job descriptions?
- How to become a junior data analyst: a step-by-step guide
- Key takeaways
We’ll presume no prior knowledge here, so read on to learn everything you need to know about becoming a junior data analyst!
1. What is data analytics?
Data analytics is the process of examining datasets to uncover patterns and trends. Using these insights, data analysts can then devise actionable steps to drive informed business decisions. Commonly, data analytics predicts (or, at least, makes well-informed guesses) about what might happen in the future.
Data analytics has existed in one form or another since humans first started scribbling onto clay tablets with a stylus. Data analytics as we know it today, however, largely emerged with the dawn of modern computing in the 1960s. The arrival of the internet—and the vast amounts of data that come with it—have further revolutionized the field. Once primarily reserved for the natural sciences, data analytics is now transforming every industry: from finance to education, property management, product design, agriculture, healthcare, and more. In short: where there’s data, there’s potential for data analytics.
The 21st century boom in data analytics has seen the development of many specialized software systems to carry out the most arduous data analytics tasks. Far from making the role obsolete, however, this has freed up individuals to dive deeper and create ever-more data-driven strategies. From smart supply chains to managing web content, detecting fraud, and more, data analytics has countless applications in the modern world, and new ones are constantly emerging.
2. What does a junior data analyst do?
As an entry-level position, a junior data analyst usually carries out the more routine aspects of the data analytics process. Nevertheless, they play a vital role in supporting the delivery of data-informed actionable insights that drive a business forward.
While many junior data analyst responsibilities may seem menial, their foundational importance to the overall process can’t be overlooked—there’s no making cups of tea here! A junior data analyst’s main responsibilities usually include:
- Collecting relevant data
- Documenting which information requires further processing
- Cleaning and ordering data into appropriate storage systems
- Learning to extract and interpret statistics from datasets
- Creating charts, graphs, and dashboards
- Supporting more senior staff with report writing
Although exact responsibilities vary depending on the job description, these are typical requirements for any entry-level data analyst. In contrast, junior data analysts are not usually responsible for higher-level strategy, determining which business questions need tackling in the first place or delivering presentations to senior decision-makers. But these are all things you can work towards.
3. What skills do junior data analysts need?
No reasonable employer will expect a junior analyst to know everything. However, you will need an essential baseline of skills to get started in this profession. Beyond that, there’s much you can learn on the job. Industry-specific software or processes, for example, are often better learned in-role, under the supervision of an expert manager.
But before you get to that point, here’s a list of the fundamental skills all junior data analysts require:
- Strong mathematical and statistical skills: Data analytics involves plenty of number crunching. You should be mathematically literate, particularly in the area of statistics.
- Relational databases: Most data is stored in databases. In particular, you’ll need to understand relational databases (which simply means that data are stored in columns and rows. In contrast, non-relational databases store data in document format.)
- Structured Query Language (SQL): Managing relational databases requires knowledge of SQL. This coding language allows you to retrieve data, insert, update, or delete records in bulk. It’s a core tool for all data analysts.
- Microsoft Excel: We’ve all used Microsoft Excel at one point or another, but do you know the full extent of its statistical functionality? From pivot tables to conditional formatting, filtering, and other functions, aim to familiarize yourself with Excel’s essential data analytics features.
- Python or R: While full-on coding isn’t always necessary for data analytics, you’ll still need to tweak algorithms and amend custom software programs. As the easiest one to learn, Python is the most common language used by junior data analysts. However, R is also popular with those requiring more robust statistical functionality.
- Critical thinking: Nobody can prove their critical thinking skills with a certificate alone, so you should aim to cultivate a critical thinking mindset in other ways. This will help you connect and probe disparate data, thinking analytically to extract meaningful insights.
- Data visualization: All data analysts need to understand the fundamentals of data visualization. Fortunately, Python has hundreds of libraries of pre-existing code to help. These include Matplotlib, Seaborn, and Plotly. Microsoft Excel also offers visualization functionality.
- Communication and presentation skills: It’s one thing to understand what a dataset is telling you. It’s another entirely to communicate this to non-technical decision makers. All data analysts must be able to clearly present their findings using presentation software, dashboards, and reports.
- Machine learning and artificial intelligence: While junior data analysts needn’t be experts in machine learning or AI, some understanding of their underlying principles and theory is beneficial.
Although this sounds like a broad set of skills for a beginner, don’t worry! There are many online courses designed specifically to walk you through these essential skills. Even people with little or no background in data will find it easy to comprehend these topics with the right guidance.
4. How much can junior data analysts earn?
Several factors impact how much you earn as a junior data analyst. These include your geographic location, the company you’re working for, the industry, and your past experience. Due to data analytics being in high demand, most junior analysts can earn a competitive salary regardless. This makes any upfront investment in training well worthwhile.
The following salary comparison sites hint at how much junior data analysts in the United States can earn. Since these are updated in real time, be sure to click the links to see the most up-to-date estimates:
- SimplyHired: $31,000
- Glassdoor: $33,000
- Payscale: $42,000
- Salary.com: $50,000
- Salary Expert: $68,000
- Indeed: $80,000
As you can see, there’s some variation here, so it’s good to take these estimates with a pinch of salt. However, taking an average does offer a representative flavor of what you might expect. Doing so tells us that junior data analysts in the U.S. can earn anywhere in the region of $50,000. Even starting on less than this isn’t bad for an entry-level position.
To dive deeper into factors such as how geography, industry, and even job title can affect your earning potential, check out this guide to junior data analyst salaries.
5. Junior data analytics job descriptions
Once you’ve acquired the skills you need to become a data analyst, the next step is the one we all dread… job hunting! This can be intimidating, especially as a beginner in a skilled profession like data analytics. It’s made even harder by the fact that job descriptions rarely follow the same format. But feel reassured—in reality, most junior data analyst job descriptions tick off the same conditions. The trick is learning to spot these requirements, which may be worded differently or compiled under different headings.
In this section, we’ve compiled a list of the different types of requirements usually outlined in junior data analyst job descriptions, so you know what to look out for.
Education
In terms of educational requirements, data analysts usually require an undergraduate degree. Ideally, this will be in math, statistics, or a computing-related subject. However, as long as you have an additional data analytics certification to evidence your skills, any degree will normally do. While for higher-level roles, hiring managers may request a subject-specific qualification such as a master’s degree, that’s not usually something you need to worry about at this stage.
Applied skills
Junior data analyst job descriptions will usually highlight a particular set of hard skills. As per section 3, these include knowledge of databases, data mining, SQL, Python, data viz, and sometimes proprietary data-related software like Google Analytics. Often, these skills are described using generalized terminology such as ‘computing skills’ to encourage you to apply. Some jobs prioritize one or two of these skills, meaning you can pick up other vital skills on the job. Something to keep in mind when you’re applying.
General skills
While your focus may be on acquiring the relevant technical skills, many employers also prioritize general business and workplace employability skills. We’re talking about things like teamwork, communication, time management, and a general ‘can-do’ attitude—standard job competencies for the 21st century. These are often surprisingly hard to come by, as traditional education systems don’t tend to teach them very well. While you can learn many technical skills via a certified course, don’t forget to highlight your employability skills too, evidencing them where possible with examples (more on this in section 5).
Experience
Sometimes junior roles cite the need for ‘at least one year’s experience in a data analytics role’. This is a common problem for new entrants to the job market—if all jobs require experience how can you land a job to gain that experience? One way is by doing an internship. But since these aren’t always paid, we understand they’re not an option for everyone. Once again, taking a certified course can be an excellent solution. A well-designed bootcamp usually includes a portfolio project (or several) to help build your skills and provide you with the evidence to prove them. While this may not be the same as ‘a year’s work experience’, it does show willingness and commitment, which is often sufficient.
When to apply and when not to apply
Senior data analytics roles often require highly-specific industry or domain-related knowledge. This is rarely true for junior positions. As such, don’t be afraid to apply for a role—even if you don’t think you tick off 100% of the qualifications it asks for. This doesn’t mean you should apply for any old job if you lack all the qualifications. But if you can cover the basics, demonstrate a track record of success, and a willingness to learn (and have a portfolio) you’ll be surprised how far these can take you. The worst thing that can happen is that you won’t make it to an interview… so give it a go!
6. How to become a junior data analyst: a step-by-step guide
Now we’ve covered what skills you’ll need, how much you might earn, and how to navigate job descriptions; what are the next steps towards becoming a junior data analyst? Here’s our five-step guide:
1. Familiarize yourself with the fundamentals
While pretty much anyone can learn the necessary skills to become a data analyst, it’s inevitably a time (and potentially cost) commitment. Before diving deeper, familiarize yourself with the fundamental theory of data analytics to see if it’s for you. For instance, you might want to research the different types of data analysis or learn what outliers are, among other things. Don’t forget to look at the general skills and software you’ll need to learn, too. There are tons of free online tutorials you can dip into to pick up this know-how, without any commitment to splashing the cash.
2. Consolidate your learning with a structured course
Once you’ve decided that data analytics is right for you, it’s time to take your learning to the next level. One option is to apply for an undergraduate or a master’s degree in a relevant data-related subject. Let’s face it, though—that’s an expensive, time-consuming route for a junior role.
A better option is to take a structured online course. These are generally more affordable than full-time degrees and faster, too, packing in all the need-to-know skills you need to get started. A well-designed course will lead to an industry-recognized certification, practical experience, and support with job applications and interviews. You’ll also build a resume and portfolio. Better yet, some courses offer a job guarantee or accept employer scholarships, meaning your employer can foot the bill. To learn more, check out the top online data analytics courses or this round-up of the best data analytics bootcamps.
3. Refine your soft skills
As we’ve mentioned, employers don’t just want technical skills. They also want ‘soft’ employability skills. Things like: communication, critical thinking, problem-solving, writing and language, teamwork, digital literacy, and leadership, to name a few. Seek out any opportunities you can to refine these skills. These opportunities don’t always have to be work-related.
For instance, perhaps you’re the captain of a local sports team. How has this contributed to your leadership skills? Maybe you took a gap year abroad. How did being in a different country contribute to your intercultural understanding? If possible, seek out volunteer positions or project work. Get creative! See how you can find ways to access some of these learning opportunities to bolster your application.
4. Build professional connections
As they say: “It’s not what you know. It’s who you know.” This is as true for data analytics as any profession. Try to network with like-minded individuals, or find an experienced mentor. Networking opportunities are invaluable for better understanding the industry and finding job opportunities. You can do this virtually by attending online webinars or by building a professional network on LinkedIn. Alternatively, find some local data analytics groups on meetup.com. You may be surprised by how much a supportive community of data professionals can help as you embark on your new career.
5. Perfect your portfolio and resume
Lastly, when you’re ready to start applying for jobs, you’ll need a resume and a portfolio of work. Your resume may be the only thing a recruiter looks at, so it’s vital to get this right. Check out some tips for creating a job-winning data analyst resume in this guide.
Meanwhile, as a junior data analyst, having a portfolio of work may seem premature. It doesn’t need to be jam-packed with real work experience, though. It can also include pet projects that show off your skills. To see what we mean, check out these exemplary data analytics portfolios from real data analysts. To inspire your own projects, you can also browse these data analytics portfolio project ideas.
7. Key takeaways
There we have it! Our comprehensive guide to becoming a junior data analyst. Hopefully, by demystifying the topic, we’ve shown that going from complete novice to qualified data analyst isn’t as intimidating as it might seem—it’s simply a case of breaking the process into more manageable steps.
In this post, we’ve learned that:
- Data analytics involves examining datasets to uncover trends and create actionable insights that drive smarter decision-making.
- Junior data analysts usually carry out more elemental aspects of the role, such as collecting, processing, and storing data, and supporting more senior team members.
- Common skills for junior data analysts include strong math skills, databases, SQL, Python, and Excel, and excellent critical thinking, communication, and data visualization skills.
- The average starting salary for a junior data analyst in the U.S. is around $50,000 a year. Not too shabby!
- Before looking for junior data analytics job descriptions, you should consider taking a certified short course, networking with other data analytics professionals, and building a portfolio of projects.
The next step on your journey to becoming a junior data analyst? Researching the topic further! To learn more about what a career in data analytics might entail, check out this free, 5-day short course or read the following introductory guides: