Considering a new career in data analytics and wondering how to get started as an entry-level data analyst? Don’t know where to start? Find out everything you need to know in order to get an entry-level data analytics job in this guide.
Maybe you’re a fresh graduate launching your career; perhaps you’re bored in your current role and are seeking a change; possibly your circumstances changed during the pandemic and now you’re looking for new opportunities. Whatever the reason, people are turning to data analytics in droves.
As a career option, data analytics ain’t bad! There are tons of ways to train the necessary skills (from free tutorials to paid courses) and the job is in increasing demand (meaning job security). Data analytics is also challenging enough to remain interesting, while paying well enough to justify the learning curve. But to enjoy all these benefits, you’ve got to get your foot in the door first, which begs the question: What’s the best way to get started as an entry-level data analyst?
In this post, we’ll attempt to answer this question, breaking the topic down into the following categories:
- What does an entry-level data analyst do?
- Is it possible to become a data analyst with no experience?
- What skills do I need to get started as an entry-level data analyst?
- How to get started as an entry-level analyst: Your step-by-step guide
- Where to look for entry-level data analyst jobs
- Wrap-up and further reading
Ready to find out more? Let’s proceed.
1. What does an entry-level data analyst do?
In one way or another, all data analysts aim to do the same thing: probe data to discover hidden patterns or trends. They can then use these to create actionable insights, which aim to solve a particular business problem.
The skills involved in creating these insights vary depending on the seniority of the role. As a junior data analyst, though, you won’t be expected to take on sole responsibility for mission-critical tasks, such as implementing data management systems or creating complex data models. Instead, you’ll be given important (but smaller) jobs that are nevertheless important to the process. For instance, an entry-level data analyst’s job duties might include:
- Mining data from selected sources
- Managing these data (organizing, cleaning, and storing them in relational databases)
- Conducting basic analyses, perhaps using insight tools like MS Power BI, MS Excel, and Tableau
- Querying data in relational databases using tools like SQL (as a junior data analyst, you’ll be trained on the job)
- Generating reports that present your findings in a clear, concise format, accessible to senior stakeholders
- Helping build new data integration across in-house systems
- Honing your broader skills such as pattern recognition and problem-solving
- Learning the broader purpose, aims, and processes of your business (and industry)
Since every job is different, it’s impossible to pin down the exact responsibilities. However, this offers a pretty good taste of what you’ll be expected to do.
As you can see, the tasks for a junior data analyst can be quite broad. As you move into mid-level and senior-level data analytics roles, you’ll take on more responsibility for things like software implementation and customization, as well as more general management responsibilities and more complex data analytics tasks, like data engineering.
2. Is it possible to become a data analyst with no experience?
We won’t beat around the bush: yes, you can become a data analyst with no experience. However, this does depend on what you mean by ‘experience’. If you mean time spent in a past data analytics role, then no, you don’t need any experience to land an entry-level data analyst job.
However, if you mean the basic underlying skills that prove you know what you’re doing and that you’re interested (and competent) enough to pursue a career in data analytics, then yes: you do require some experience. But don’t be put off, there are many ways to gain this expertise.
There are two main reasons that you don’t need work experience. These are:
- There’s a big shortage of data analytics skills
- Data analytics relies heavily on transferable (i.e. non-technical) skills
Let’s briefly explore each of these in more detail.
The data analytics skills shortage
For several years, there’s been a huge shortage of skills in the global labor market. This is particularly prevalent in the area of digital skills, which, of course, includes data analytics. Disrupting the broader job market, the COVID-19 pandemic has only exacerbated this trend.
According to accounting firm Deloitte, demand for data analysts in the U.S. is outstripping supply. This is mainly because, over the past decade, organizations have been prioritizing their focus on data analytics skills, but there has been little progress in training these skills. While these data are specific to the U.S., they largely reflect global trends.
Source: Deloitte
While these issues aren’t necessarily good news for the economy, they are great for entry-level data analysts seeking their first job! Organizations are far more likely to hire junior data analysts without experience, for the reason that they have little choice. But there’s an upside to this: by hiring fresh talent, companies can upskill employees in their specific procedures and industry skills. This means targeted training for employees and happier workers within a company. Everyone wins!
Data analytics’ reliance on transferable skills
Another reason you’ll be able to land an entry-level data analyst job without experience is that data analytics relies heavily on transferable skills. Technical skills (as outlined in section 3) are important, however, they are also teachable. Meanwhile, skills like active listening, complex problem solving, and the ability to exercise judgment are harder to train, which makes them far more valuable. Plus, they’re indispensable in a field like data analytics.
According to another analysis by Deloitte, employees with more transferable skills are most likely to end up in the jobs with the brightest futures, which includes jobs in data analytics. As you can hone these transferable skills, you’ll stand out to an employer, even if you don’t have any previous data analytics expertise.
Learn more: Is it possible to get a job as a data analyst with no experience?
3. What skills do I need to get started as an entry-level data analyst?
As a junior data analyst, the skills you need to land an entry-level job can be broadly placed into two categories: transferable skills and technical skills.
Transferable skills for entry-level data analysts
We touched on transferable skills in section 2, but for good measure, here’s a more comprehensive list of what employers tend to look for:
- Complex problem-solving skills
- Creative, critical thinking skills
- Interpersonal and written communication skills
- Active listening
- Awareness, empathy, and emotional intelligence
- Motivation and ability to meet deadlines
- Ability to work in a team
Technical skills for entry-level data analysts
Being a good team worker is one thing, but no amount of empathy or active listening will get around the fact that data analytics is still a technical job! You’ll need a basic understanding of data analytics theory and some practical knowledge of the tools required. Interestingly, contrary to popular belief, these skills aren’t always what people think they are.
According to the Initiative for Analytics and Data Science Standards (a U.S.-based non-profit that develops and maintains professional standards in the industry), there’s some discrepancy between the technical skills that data analysts promote on their LinkedIn profiles and those that employers actually include in their job postings.
Source: IADSS
Based on the graph, we can see that many employees emphasize skills that aren’t the top priority for employers. For instance, MS Office skills are the top skills that employees promote, even though these rarely register in jobs ads (although MS Excel does).
With this in mind, we’ve highlighted some of the top skills that employers actually do seem to be looking for.
- SQL: Structured Query Language (SQL) is a domain-specific programming language, used for querying and managing data held in relational databases. To get started as an entry-level data analyst, you’ll at least need to know SQL basics.
- MS Excel: Even if you’re not a data analyst, you’ve probably used MS Excel at some point, perhaps for some basic financial accounting. However, you may not have used many of its data analytics features. It has a wide range of calculation and graphing tools, as well as pivot tables that can be used for organizing, sorting, cleaning, and quality-assuring data. It’s a must-have for any junior data analyst.
- Tableau: The proprietary visualization software, Tableau, is used by many organizations for business intelligence purposes. If you land an entry-level job with an organization that uses it, you’ll have to upskill fast! If you can evidence that you know the basics already—perhaps using Tableau Public—all the better.
- Hadoop: Apache Hadoop is a collection of open-source software libraries used to network computers. It allows users to manage and store big data across numerous computers. Hadoop is one of the best-known distributed computing frameworks there is and it’s commonly used in data analytics. If you want to get a job as an entry-level data analyst, you don’t need to be an expert in Hadoop. However, you should at least know what it is and how it is used.
- Python: While Hadoop isn’t a must-have for getting a junior data analytics job, Python is. Python, a statistical programming language, is widely used in data analytics and you can’t really get started without it. Fortunately, it’s pretty easy to learn. And once you’ve got the basics, you’ll improve fast.
- ETL: ETL stands for extract, transform, load. This is a set of procedures for transferring data from one or more sources into a destination system. There are many tools to support the ETL process; some data analysts use Python.
While you may not be expected to have mastered all of these skills to land an entry-level job, you’ll at least need to know what they are and how they are used.
4. How to get started as an entry-level analyst: Your step-by-step guide
Okay, we’ve covered what a junior data analyst does and what skills you need to know to land your first job, but what about the practical aspects? The following guide will help you figure out how to get an entry-level data analytics job, fast.
Step 1: Research the different kinds of industries you can work in
Assuming you feel comfortable knowing what data analytics involves, make sure you have an idea of where you’d like your career to take you. For starters, check out the top industries that are hiring data analysts right now and see which areas spark the most interest for you. Meanwhile, if you’re primarily driven by a healthy salary, then you should check out which industries tend to pay the highest data analyst salaries.
All these factors will help you decide which industry you might want to work in. Don’t worry about it too much, though. While having an idea of where you want to work will help focus your efforts, you can always change track later. Fortunately, data analytics skills are highly transferable between industries and job roles.
Step 2: Take a certified course (or gain another qualification)
Once you’ve determined an industry that you might want to work in, the next step is to ensure you have a baseline of data analytics skills. There are two main options here. The first is to get a degree in a data-related field. However, if you’re a recent graduate—or are taking a side-step from an established career—you might balk at the idea of spending much time and money going back to college.
An increasingly popular alternative to college is to take an online certified course. While these can be quite intensive, they’re generally cheaper than a full degree, more flexible, and provide you with targeted data analytics skills in a matter of months, rather than the years it takes to get a college degree, which isn’t strictly necessary for entry-level data analytics roles, anyway. Sounds intriguing? Then compare the top data analytics bootcamps on the market right now.
Learn more: Data bootcamp vs. data degree: Which is best for you?
Step 3: Polish up your portfolio
Have a rough idea of the industry or job role you’d like to work in? Check. Certified the appropriate data analytics skills? Check. Next up: polishing your portfolio!
Having a top-notch data analytics portfolio to accompany your applications will help highlight your genuine interest in the field. We know what you’re thinking: as an entry-level data analyst you don’t have any expertise! That’s true, but it doesn’t mean you can’t put together some sample projects. Even having one or two well-presented pet projects will be a huge help for showing employers that you have more than just a passing interest in the field.
We’ve written a series of posts on this, so we won’t go into more detail here. But for further guidance, check out how to build a data analytics portfolio, explore some data analytics portfolio project ideas and take the plunge with 10 great places to find free datasets for your next project.
Step 4: Start looking for jobs
Now that you’ve done the groundwork and have created a solid portfolio, you’re ready to start actively looking for junior data analytics jobs. In section 5, we outline some places where you might want to start your job search. As for the job descriptions themselves, you’ll have to read a few to get a feel for whether they are entry-level roles. This isn’t always immediately obvious.
As you read through some job ads, see if you can learn to spot how the responsibilities for entry-level data analyst jobs differ from more senior positions. To help, check out some different data analyst job descriptions and what they really mean. Keep an eye on the job titles, too. From ‘novice financial analyst’ to ‘level 1 healthcare consultant’, junior data analytics jobs might be hiding behind a different name!
Step 5: Perfect your resumé and cover letter
While nobody’s expecting you to tweak your portfolio for every job application, the same isn’t true for your resumé and cover letter. A headache though it might seem, it’s important to amend the wording and order of your resumé to align with the requirements of each job application. As for the cover letter, you should ideally write this from scratch every time. Focus on why your experience will benefit the company or organization you’re applying to.
Learn more: How to write a great data analyst resumé (with examples)
Step 6: Apply, network, and persist!
Next up, start sending out your applications for entry-level data analytics jobs. Don’t worry if it takes a long time to apply for the first few roles—things will speed up as you get more practice. Ultimately, even with all the right skills, a great portfolio, resumé, and cover letter, applying for data analytics is kind of a numbers game. You’ll probably have to send out a lot of applications before you get a positive response. But each time you do, see if you can make a new contact. Applying for jobs is hard work, but it’s also a great networking opportunity. Even if you don’t get through the application process on your first go, keep applying and employers will start to notice you. Persist, persist, persist!
5. Where to look for entry-level data analyst jobs
Last but not least, where should you go to find junior data analytics jobs? One of the key steps we highlighted in the previous section was finding suitable job postings. In this section, we provide a list of options for finding junior-level data analyst jobs. Be sure to also check out this ultimate guide to entry-level data analyst jobs.
Generic job boards offering entry-level data analytics positions
Entry-level jobs are a dime a dozen on the following job sites, but be aware that the quality of postings is quite variable, since job descriptions are sometimes written by HR managers without data analytics experience. You can generally spot these by the fact that they list more ‘generic’ job responsibilities, without referencing specific tools or procedures. Nevertheless, the sheer number of jobs on these sites makes them worth checking out:
- Entry-level data analyst jobs at Glassdoor.com
- Entry-level data analyst jobs at Indeed.com
- Entry-level data analyst jobs at Monster.com
- Entry-level data analyst jobs at Linkedin.com
- Entry-level data analyst jobs at Ziprecruiter.com
Data specific job boards offering data analytics jobs
We also recommend visiting sites that focus more specifically on jobs in data analytics. While these often attract recruiters seeking candidates for more senior-level roles, there’s no harm in taking a look:
Entry-level data analytics jobs on company websites
Maybe you’re committed to the idea of working for a particular company or organization. If so, check out the careers section on their website. Even if you can’t find the job you’re looking for, a company’s job listings often provide insight into which areas of the business are growing. If you see a lot of data-related roles coming up, why not contact them directly and see if they might be open to hiring you as a data analytics intern or apprentice?
6. Wrap-up and further reading
In this post, we’ve explored everything you need to know to get an entry-level data analytics job. You should now know what a junior data analyst does and the basic skills they require. Our step-by-step guide will also help you get started. Remember to take a proactive approach, train and certify your skills, and apply for as many jobs as you can.
To learn more about data analytics, sign up for this free, 5-day introductory data analytics short course. You’ll receive a short course on everything data analytics-related, delivered daily right to your inbox. We can also recommend the following introductory topics: