IN THIS ARTICLE
- What Does a Data Analyst Do?
- Is It Hard To Become a Data Analyst?
- How To Become a Data Analyst
- How Much Can You Make as a Data Analyst?
- Becoming a Data Analyst: Examples To Learn From
- Data Analyst FAQs
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Right now, the demand for data analysts has never been higher. In fact, according to the US Bureau of Labor Statistics, employment of data analysts is projected to jump 25% by the year 2030, meaning data analytics has one of the highest growth rates in the country.
In this guide, we will cover everything you need to know to become a successful data analyst, including where to start, the specific steps you need to take, and the relevant data skills you should learn along the way.
What Does a Data Analyst Do?
A data analyst is responsible for gathering, cleaning, and analyzing large sets of data to extract meaningful insights and inform decision-making. They use statistical and computational techniques to identify patterns and trends in the data and present their findings to stakeholders in a clear and understandable way.
Become a Data Analyst. Land a Job or Your Money Back.
Transform real-world datasets into actionable recommendations. Master technical and strategic thinking skills and frameworks. Land a job — or your money back.
Is It Hard To Become a Data Analyst?
Becoming a data analyst isn’t hard per se, though it does require certain technical skills that might be more challenging for some than others. Additionally, because of continuing advancements in the field, data analysis is a career path that requires ongoing education.
How To Become a Data Analyst
Follow these steps to land your first job as a data analyst:
Complete a Course
One of the most efficient and comprehensive approaches to acquiring the necessary skills for a data analyst role is to enroll in an online Data Science Bootcamp. Through this focused learning path, you’ll gain in-depth knowledge and have the opportunity to receive guidance from mentors who are currently practicing in the field.
Understand the Fundamentals
The first step of your journey is making sure you have a firm grasp of the fundamentals. You want to make sure you understand the key principles of data analytics, the different types of data analysis, and the tools that data analysts use.
Meet the Educational Requirements
Data analysts spend a lot of time working with numbers. Because of this, many employers look for candidates with bachelor’s degrees in mathematics, statistics, computer science, or a related field.
However, you don’t necessarily need a formal degree to land a data analyst job. In fact, companies often hire candidates who have completed an online course in data analysis, or a data analytics bootcamp, or can demonstrate the requisite technical knowledge and skills. Look for the requirements listed in the descriptions of jobs that interest you.
Pick Up an Essential Programming Language (or Multiple)
Not all data analysts need to know how to code (though most data scientists do). In fact, at the start of your career, a cursory familiarity with the more popular querying languages should suffice. However, if you really want to become the best (most employable) data analyst you can be, consider learning one – or more – of the essential programming languages (i.e., Python, R, SQL).
Get Familiar With Data Analytics Tools
Data analysts use a wide variety of tools and applications to collect, manipulate, and analyze data. You should familiarize yourself with the most used analysis tools, including:
- Tableau. A popular data visualization tool used to perform data analysis, manipulation, and visualization
- Microsoft Excel. A well-known spreadsheet application commonly used by data analysts
- Microsoft Power BI. A free data visualization and business insight tool ideal for collaboration
- Google Analytics. A web-based analytics tool used to track website traffic
- Jupyter Notebook. An open-sourced web application that enables exploratory analysis using “big data” tools (e.g., Python, R, and Scala)
Develop Your Data Analyst Skillset
Having the right skillset is paramount to your becoming a data analyst. Make sure you’ve developed the following hard skills and soft skills:
- Statistical analysis and math skills. Data analysts work with numbers. A lot. Data analysts should have strong math skills and be comfortable analyzing data sets.
- Programming and querying languages. In order to process data and make it understandable for others, analysts use various programming and querying languages, such as Python and R. As a data analyst, you probably won’t have to build many programs, but being familiar with the commonly used languages and understanding how they function is essential.
- Microsoft Excel. MS Excel is a go-to tool for data analysts. It’s widely available, easy to use, and has a ton of useful features.
- Data visualization. If the insights derived from your analysis are incomprehensible, what is their value? A good data analyst can produce meaningful insights and present those findings visually in their most understandable form.
- Machine learning. One of the unofficial differences between data analysts and data scientists is that data scientists use machine learning to design new processes for data modeling. As a data analyst, you likely won’t have to do that. However, in order to work with data scientists effectively, you will need to be familiar with these processes and understand how they work.
- Analytical thinking. Data analysis involves collecting raw data and refining it into meaningful information. Once the data has been refined, analysts analyze it to uncover some deeper truth and value. This can only be done through analytical thinking.
- Problem-solving skills. Well-developed problem-solving skills help data analysts recognize the nature of the problem before them, what the best data analysis tools and techniques are to solve the problem, and the solution to the problem itself.
- Presentation skills. Data analysts need to effectively present their insights in a way that everyone—especially non-technical stakeholders—can understand. Strong presentation skills will enable you to convey your findings and predictions in a compelling manner that your audience will care about.
- Communication and interpersonal skills. Data analysts rarely work in a bubble. In fact, as an analyst, you’ll likely interact with a variety of different people, including colleagues and coworkers, managers, and subject matter experts. Having strong communication and interpersonal skills will help facilitate collaboration among different parties.
Get To Know Other Data Analytics Students
Pursue Volunteer, Open-Source, or Freelance Projects To Build Your Portfolio
Building a strong portfolio is one of the best and most surefire ways to demonstrate your analytical skillset. Pursue volunteer opportunities, find freelance work, or work on a personal project to highlight your analytical knowledge.
If you are thinking about showcasing a personal project in your data analyst portfolio but don’t have one readily available and you’re not sure where to start, consider using a publicly available data set. You can find all kinds of datasets on sites like Data.gov and Datahub.io.
Finding a dataset that covers a topic you are already interested in is helpful. But more importantly, choose data that can best be analyzed by the methods you are most proficient with—this will allow you to showcase your strengths to their fullest potential as an analyst or data scientist.
In addition to personal projects, you will also want to fill your portfolio with projects that demonstrate your analytical skillset and showcase your ability to tackle real-world problems as part of a team.
That’s where volunteer work and freelance projects come in. Look for opportunities that will allow you to collaborate with others while working on the different phases of the data analysis life cycle. Not only will this experience make a good impression on potential employers, but it will also help strengthen the data analytics skills you need to be successful.
Build Your Network
Good networking can help you get your foot in the door, develop valuable relationships with experienced professionals, find a mentor, and more. Consider these resources to start building your professional network today:
- LinkedIn. The well-known social networking service for professionals makes it easy to find and connect with data analysts and other like-minded individuals.
- Online Communities. Online communities aren’t just great for meeting people with similar interests. They are also a great source of support and useful information.
- Conferences and Meet-Ups. Attending a data analyst conference or meet-up will allow you to network in person, which is a great way to make lasting impressions that could benefit you down the road.
Find a Mentor
No matter your profession, a mentor can provide guidance and feedback to help you achieve your career goals. Through them, you can learn lots of valuable insights, including how other analysts started out, the different career paths an analyst can take, as well as the pros and cons of those varying paths. As a mentee, you will benefit from your mentor’s learn real-life experience and gain actionable insights you can use to chart your ideal career path.
One way to find a good mentor is to use your professional network. Reach out to contacts to let them know you are looking for an experienced data analyst to become your mentor. Use professional networking platforms like LinkedIn to potential mentors and approach them about a mentorship.
Before you reach out to someone about becoming your mentor, be sure to have a specific goal in mind. Be prepared with detailed questions and answers to potential questions, as well. Your potential mentor will likely ask questions about your personal and professional life, including what your career goals are, where you would like to be, and why you want them to mentor you.
It is also a good idea to come up with a plan or structure for how you imagine your mentorship would work. You should be clear from the beginning about how much time you would like to spend with your mentor, the type of guidance you are looking for, and so on. Establishing what you are looking for early on is crucial if you want to get the most out of your mentorship as possible.
Consider an Internship
Landing an internship as a data analyst is arguably one of the best ways to break into the industry. As an intern, you’ll work on real-world projects, further develop your analytical skills, and gain valuable insights into the world of data analytics. Internships also provide excellent networking opportunities. Internships also give aspiring analysts the kind of hands-on experience that looks great on a resume.
Polish Your Resume, Prep for Interviews, and Start Applying
Now that you’ve honed your skillset and compiled a professional portfolio, it’s time to start your application prep. Talk to your mentor: have them sign off on your portfolio and help you with interview prep. Tap into your network for job leads and begin applying for entry-level data analyst jobs.
How Much Can You Make as a Data Analyst?
While not the most important factor in your exploration of how to become a data analyst, being able to earn a living should be high on your list of considerations. As with most professions, salaries vary based on several factors, including geographic location, relevant work experience, etc. That being said, here are the current national averages for data analyst salaries:
Entry-Level Data Analyst
Mid-Level Data Analyst
Job opportunities for mid-level data analysts include an annual salary of $69,343 per year.
Senior Data Analyst
The average salary for a senior data analyst is around $102,820 per year.
Becoming a Data Analyst: Examples To Learn From
Curious to see how others began their career as data professionals? Check out the following videos for an inside look at how two successful analysts made the leap into the data field:
Data Analyst Career Switch | How I Became a Data Analyst
In this video, Wale shares how he pivoted from being an engineer to a data analyst without going back to school.
How I Became a Data Analyst (Without a Related Degree)
Want to learn how to become a freelance data analyst without a degree? Then this video is for you.
Data Analyst FAQs
We’ve got the answers to your most frequently asked questions:
Can I Become a Data Analyst Without a Degree?
Yes. Though some job listings for data analyst positions do list a bachelor’s degree as a prerequisite, it’s very possible to become a data analyst without a degree. For instance, in lieu of advanced degrees, many companies hire graduates from data bootcamps.
Can You Learn Data Analytics on Your Own?
Yes, but it’s not for the faint of heart. A structured learning plan taught by a skilled instructor is the easiest path to take—something you’ll realize the first time you run into a problem you can’t solve on your own.
That doesn’t mean you have to enroll in an undergraduate program or earn your bachelor’s degree to become an analyst. Online courses and data analytics bootcamps can provide you with the structure, support, and skillset you need to become a skilled data analyst.
Is It Worth Getting a Data Analytics Certificate?
If you are interested in a career in data analytics, then a certificate can be a valuable investment to help you stand out against a growing demand for qualified professionals.
There are many different data analytics certificate programs available, so it is important to choose one that is right for you. Some factors to consider include:
Curriculum: Consider whether the program teaches skills that are relevant to the position you are seeking. For example, someone looking for a data analyst position doesn’t necessarily need a Certified Ethical Hacker certification.
Faculty: How experienced are the people teaching the course? Any quality bootcamp should have teachers with at least a decade in the industry who are up to date on its most recent developments.
Cost: Data bootcamps vary widely in terms of cost, but fall between ~$6k on the lower side and upwards of ~$20k on the higher end. Consider also what kind of payment options these plans have (e.g. monthly, one-time payment)
Accreditation: Most bootcamps are not accredited, meaning that the certifications you get from them are not officially recognized as meeting industry standards. Make sure to check what accreditations a bootcamp offers before signing on.
Does Data Analytics Require Coding?
Coding is not a required skill for most data professionals, though having a surface-level familiarity and understanding of common programming languages is recommended. The most common languages include Python, R, and SQL.
Is Data Analysis a Stressful Job?
Data analysis can be a stressful job, but it is not always so. Some of the factors that can contribute to stress in a data analyst’s job include:
Tight deadlines: Data analysts often have to work under tight deadlines, which can lead to pressure and stress.
Complex data: Data analysts may be required to analyze complex data sets, which can be time-consuming and challenging.
High stakes: The results of data analysis can have a significant impact on a company’s bottom line, which can add to the stress of the job.
However, there are also a number of things that data analysts can do to reduce stress in their jobs, such as:
Setting realistic expectations: Data analysts should set realistic expectations for themselves and their deadlines.
Taking breaks: Data analysts should take breaks throughout the day to avoid burnout.
Delegating tasks: Data analysts should delegate tasks to others when possible.
Seeking help: If a data analyst is feeling overwhelmed, they should seek help from their manager or a colleague.
Overall, data analysis can be a stressful job, but it can also be a rewarding one. By taking steps to manage stress, data analysts can enjoy a successful and fulfilling career.
Is Data Analytics Math-Heavy?
Yes. While you don’t necessarily need a degree in mathematics to get started, you will need to be familiar with some key areas and concepts. The most common types of math you’re likely to encounter as a data analyst include linear algebra, probability, calculus, and statistics.
Since you’re here…
Switching to a career in data analytics is possible, no matter your background. We’ve helped over 10,000 students make it happen. Check out our free data analytics curriculum to gauge your interest, or go all-in with our Data Analytics Bootcamp.