Data analysts leverage data to solve problems and answer questions. Sounds simple, right? With the right learning path, skills, and expertise—it can be.
In this guide, we’ll delve into the role and outline the exact process of how to become a data analyst. We’ll explore the data analyst career roadmap—from job requirements and learning paths to job hunting in today’s market. We’ll also touch on the subject of how to become a data analyst with no experience.
Table of Contents
Why Start a Career as a Data Analyst?
How to Find a Data Analyst Job
How to Become a Data Analyst with 365 Data Science
Why Start a Career as a Data Analyst?
The data analytics market is projected to grow by 29.4% from 2023 to 2030. This high demand translates to robust job security and ample career opportunities for data analysts.
Data analyst salaries are also competitive. According to Glassdoor, a data analyst in the U.S. can earn an average salary of \$108,000 per year.
That sounds great, but you may be wondering: “What is a data analyst?”. In this career, you'll play a crucial role in guiding strategic decision-making within your organization. Your work will directly influence product development, marketing strategies, and operational efficiencies.
There's a unique satisfaction in knowing your analyses can have a tangible impact on an organization and the people you work with.
Data analyst skills are also highly transferable, offering you the flexibility to work in various sectors and even remotely. Whether you're passionate about healthcare, finance, or e-commerce, there's likely a data analyst role that suits your interests.
What Do Data Analysts Do?
The duties of a data analyst can vary by industry and job title, but several core responsibilities are common across the board.
Here’s a look at what data analysts typically do:
- Collect and process data: Data analyst requirements include working with databases, spreadsheets, or third-party platforms to collect and process data, ensuring its quality and relevance.
- Analyze data and develop models: Data analysts use statistical techniques and tools to discover patterns and trends, and develop models to predict future outcomes.
- Create reports and dashboards: The data analyst career includes making findings accessible to stakeholders by selecting key metrics and visualizing them in dashboards for real-time insights.
- Communication and collaboration: Data analysts collaborate with other departments to identify problems and determine the best solutions. They communicate their findings to both technical and non-technical stakeholders, justifying recommendations and guiding decision-making.
Types of Data Analysts
The field of data analytics is broad, with various specializations catering to different industries, types of data, and stages of the data analysis process.
Depending on your field, data analyst qualifications include both general and specialized knowledge.
This diversity means that you can find a niche that aligns closely with your interests and skills.
General Data Analyst
A general data analyst performs a wide range of tasks without an initial specialty. They require versatility and readiness to tackle new challenges, methodologies, tools, and techniques.
Business Data Analyst
Business analysts focus on analyzing data to make strategic business decisions, working closely with different departments to improve processes, products, services, and software.
Our Business Analyst Career Track is the perfect start if you’re interested in this field. We provide comprehensive courses covering all the fundamental and specific skills you’ll need to make strategic business decisions. You’ll also complete projects to showcase your skills to potential employers—even without prior job experience.
Specialized Data Analysts
- Marketing analysts specialize in analyzing market trends, customer behaviors, and campaign performance. Their analyses can span various topics—from customer segmentation to sales forecasting.
- Financial analysts are experts in analyzing financial data to help businesses and individuals make investment decisions. They assess the performance of stocks, bonds, and other types of investments, providing insights that inform budgeting, forecasting, and financial planning.
- Operations analysts focus on improving the efficiency and effectiveness of an organization's operations while reducing costs.
- Healthcare data analysts specialize in analyzing data from healthcare settings to improve patient care, outcomes, and operational efficiency.
Data Analyst Requirements
Landing a job as a data analyst typically involves a mix of formal education, practical experience, and a demonstrated proficiency in relevant tools and techniques.
While the specific data analyst job requirements can vary depending on the industry and the employer, here are some key educational and qualification benchmarks aspiring data analysts should aim for.
Education & Qualifications
The biggest question is:
"Do I need a degree to become a data analyst"?
For most data analyst jobs, the answer is yes—a bachelor’s degree is often the minimum educational requirement. Fields of study may vary, but employers generally prefer STEM degrees.
The most common fields of study, based on over 1000 data analyst job openings, are statistics, computer science, and math. But this year’s research has shown that employers are aware that other degrees also cover many of the skills needed for data analysis—making transitioning from another field much simpler.
Some of these fields included general sciences like chemistry and physics, while other degrees for data analysts were seemingly unrelated, like architecture. For more information, check out the full job market research article.
“But how can I get a job as a data analyst without a degree?”
While this is more difficult, it is definitely possible. You just need to get your foot in the door to build your skills and gain experience.
Internships serve as excellent stepping stones, allowing you to build your skills and gain experience without extensive education. They are particularly beneficial if you can demonstrate to your company that you are capable of handling a full-time position.
The industry values skills and know-how over degrees, so don’t let your educational background keep you from considering a career in data analysis.
There are so many ways to fill data analyst job requirements in this digital age—through specific data analyst programs, bootcamps, projects, and free resources. All of these are available at 365 Data Science—sign up now!
Technical Skills
Data analytics is a fast-paced field, with new developments, tools, and technologies emerging constantly.
Don’t try to learn everything at once. Instead, master the critical skills required as a data analyst and commit to continuous improvement.
The data analyst learning path consists of three core areas: data querying, data analysis, and data presentation.
The skills required for a data analyst vary by company, but here’s a good starting point:
- Query data: Proficiency in SQL is essential. Our 2024 market research found SQL mentioned in over 50% of data analyst job postings. Start with our SQL course.
- Analyze data: Python, cited in over 30% of job postings, is vital. Also, grasp Excel (over 40%) for quick insights or companies preferring spreadsheets.
- Present data: Data visualization skills are crucial. Knowledge of a business intelligence tool (such as Power BI or Tableau) is highly recommended. In our research data, Power BI is the most sought-after data visualization tool at 29%, while Tableau follows closely behind at about 26%.
Soft Skills
You can’t consider the question of how to get into data analytics without mentioning soft skills.
While many candidates have the technical know-how, the right soft skills set you apart and demonstrate your value to your company.
Talk to different people in your organization, ask the right questions, and just be genuinely curious about the company and the data you are analyzing. This curiosity will naturally lead to deeper, more meaningful analyses.
A few other soft skills for data analysts are:
- Communication: Being able to communicate technical findings to non-technical stakeholders.
- Attention to detail: A keen eye for detail to ensure accuracy in analysis and data management.
- Problem-solving: Creative thinking and the ability to approach problems logically to find effective solutions.
Data Analyst Learning Path
We’ve structured this comprehensive learning path that will take you from the fundamentals to the specialized skills—helping you figure out how you can become a data analyst.
Our Data Analyst Career Track covers these steps and teaches you all the skills to land a job. Sign up for free today.
Step 1: Learn Statistical Foundations
The first step in your data analyst education is to build a solid foundation in statistics. This knowledge is crucial for data analysis, regardless of your specialization later in your career.
Study the fundamentals of statistics, focusing on descriptive statistics, probability, distributions, hypothesis testing, and regression analysis.
To get an idea of what kinds of skills you might be asked about in an interview, check out our blog article: Top Probability & Statistics Interview Questions.
Step 3: Master Excel
Excel is a powerful tool for data analysis, particularly for generating fast insights. This is a critical requirement for data analysts, appearing in over 40% of postings in our 2024 job market research.
Learn to use formulas, functions, pivot tables, and charts. Gradually move on to more advanced features like VLOOKUP, INDEX/MATCH, and macros.
Step 4: Get Familiar with SQL
SQL is essential for querying databases and is a requirement for nearly every data analytics job. In fact, SQL appeared in over 50% of the 2024 job data analyst postings we researched this year.
Start with basic SQL commands and get a good understanding of the fundamental structure of relational databases. After that, you can progress to more complex queries and concepts.
This article outlines some of the most frequently asked SQL interview questions to help you understand what kinds of skills employers are seeking.
Step 5: Learn Programming
Programming skills in Python and R are important qualifications for data analysts. These languages appeared in about 30% and 25% of job postings respectively.
In terms of data analyst courses, start with our Introduction to Python, where you’ll learn the basic syntax and data structures. Then, move on to libraries like Pandas, NumPy, Matplotlib, and Seaborn.
For a more comprehensive deep dive, our Python Programmer Bootcamp is an all-in-one course that covers everything you need to know.
In addition, here are two excellent (and free!) books you can check out:
- A great choice for beginners is "Automate the Boring Stuff with Python" by Al Sweigart.
- If you’re interested in learning R, check out "R for Data Science" by Hadley Wickham and Garrett Grolemund.
Step 6: Data Visualization
Data analysis is not just for the interest of the analyst. You need to be able to present your findings to both technical and non-technical stakeholders—making data visualization a key requirement for data analysts.
Practice creating visual reports and dashboards using Tableau or Power BI, focusing on choosing the right type of visualization for your data.
Both Tableau and Power BI offer free resources and tutorials on their websites. Additionally, our Tableau and Power BI courses will quickly get you up to speed with these tools.
Step 7: Work on Real Projects
Apply your skills to real-world datasets to solve actual problems. This will allow you to apply what you have learned and find out if there are any gaps in your knowledge.
Many jobs require some amount of experience. In fact, our job market research found that 2-4 years is the most frequently mentioned experience level. But how can you become a data analyst with no experience?
Projects are an excellent means of demonstrating to employers that you not only have the knowledge but can also apply it. You can create projects using your own data or access pre-made projects on our platform.
Our projects allow you to work on a variety of topics, from machine learning to data visualization, using various tools such as Python and SQL.
You can also participate in competitions, like those on Kaggle or DrivenData or consider contributing to open-source projects. The UCI Machine Learning Repository is another great source for datasets.
Finally, GitHub is a great place to find datasets and share your work, and it also allows you to learn more about Git.
How to Find a Data Analyst Job
Now that you understand the necessary skills to succeed in the data analyst career, here's a step-by-step guide to help you land your first job.
Step 1: Acquire the Essential Skills and Qualifications
Follow the learning path in the previous section to get a good understanding of the essential tools and technologies you’ll need as a data analyst.
Step 2: Get Certified
Certifications can provide a competitive edge.
Remember, your ability to master the concepts contained in a certification is far more valuable than just passing the exam and saying you’re certified. The certification may help you to land the interview, but your skills are what will land you the job.
The 365 Data Science Data Analyst Career Track is a specific data analyst program that covers all your bases when it comes to technical skills. Upon completion, you'll earn a certificate that you can showcase on your resume.
Step 3: Build a Strong Data Analyst Portfolio
Having a strong portfolio ready when you start applying for data analyst entry-level jobs showcases your skills and differentiates you from all the other candidates.
Choose projects that showcase a range of skills—data cleaning, analysis, visualization, and predictive modeling.
Don't use the same tired datasets that everyone has seen a hundred times (like the Titanic and Iris datasets).
Instead, look for unique and diverse datasets that may even push you outside of your comfort zone as you work towards a solution.
Our projects offer the opportunity to work with a variety of unique datasets covering the diverse topics and tools that make up the data analyst job requirements. Because these projects are prepared for you, you can start working on them immediately without the need for extensive research.
For each project, clearly outline the problem you aim to solve, the dataset you used, your approach, and the insights gained in your resume. If you encountered a problem along the way, add that, too, as this will highlight your problem-solving skills.
Step 4: Create a Winning Resume and Cover Letter
Your cover letter and resume are where you get to make a great first impression. So make it count!
Don’t think of your resume and cover letter as static documents you create once and send out a hundred times. Tailor your resume to the job you are applying to. Be specific.
If you're applying to a specialized role like marketing analyst, highlight any marketing-related projects you worked on in your previous experience. Emphasize the outcomes of your project. How did you use your skills and expertise to bring value?
Lastly, be honest. Only list skills and experiences you genuinely have—you may be tested during the interview process.
Craft your resume quickly and easily with our Data Analyst Resume Template available on our website.
Step 5: Start Applying for Entry-Level Jobs and Internships
Getting an internship is the best way to lay a solid foundation for your data analyst career.
Not only will you be able to gain practical experience across various industries, but you will also make connections with the people you work with, who can offer guidance, mentorship, and even job referrals.
Similarly, an entry-level position at a company gets your foot in the door so that you can gain much-needed practical experience and prove you have what it takes to move up in the company.
You may not get the job of your dreams when you're just starting out. But remember, a career is not built in an instant—it takes time, passion, and dedication to your work.
Step 6: Prepare for the Interview
The last step in this “How to Become a Data Analyst” guide is to ace your interview.
If you've landed an interview, you know you've made a good first impression. Now, you must prove to the company that you're the real deal.
The interview is also an opportunity for you to assess whether the company and position are a good fit for your career goals.
Start preparing for the interview by reviewing the role, the company, and the specific requirements of data analysts in this firm. This will help you to tailor your responses to show you're a good fit.
Be ready to answer technical questions or solve problems related to data analyst skills. This could include writing an SQL query, explaining data cleaning steps, or discussing how you would approach a given dataset or problem.
Review our article—25 Data Analyst Interview Questions & Answers 2024—for common data analyst interview questions.
Finally, prepare a list of questions for the interviewer about the role, team, company culture, or recent projects. This demonstrates your interest in the position and company.
Mock interviews with friends or mentors can also help ease nerves.
Data Analyst Career Roadmap
Now you know how to become a data analyst. But if you do embark on this career, what will it have in store for you?
Data Analyst Salary Expectations
The salary expectations for junior or entry-level data analyst roles in the United States vary widely based on several factors, such as location, education, certifications, and additional skills.
The average salary for a data analyst in 2024 according to Glassdoor is about \$108,000.
Our research agrees. But only a third of the job postings provided a salary range, suggesting that the actual salary range could align more closely with the range cited on Glassdoor.
To further understand data analyst salaries, here is a breakdown by years of experience provided by Glassdoor.
- 0-1 years – \$70K - \$117K/yr
- 1-3 years – \$80K - \$134K/yr
- 4-6 years – \$86K - \$144K/yr
- 7-9 years – \$88K - \$150K/yr
- 10-14 years – \$89K - \$162K/yr
- 15+ years – \$102K - \$190K/yr
Data Analyst Career Progression Opportunities
Your data analyst career can take many different paths, depending on your goals and interests.
You could move into different departments or industries, or progress into a managerial or leadership position. Alternatively, you could use your experience as a data analyst to move into other roles, such as data science, data engineering, business intelligence, consulting, and so on.
Your career progression will be unique to you. It could involve acquiring new skills, gaining experience, and sometimes pivoting to roles that align more closely with your interests and strengths.
Data Analyst Job Outlook
The rise in tech layoffs in recent years might seem scary but don't let that put you off from a career as a data analyst.
The job outlook for data analysts is very positive. Let's take a look at some numbers from various sources:
- The data analytics market size is projected to grow from \$7.03 billion in 2023 to \$303.4 billion by 2030. The predictive analytics segment, in particular, is expected to see the sharpest increase (Market Research Future).
- The projected data analyst job growth rate is 11% from 2018-2028, which translates to about 108,400 new jobs for data analysts over the next decade (Zippia).
- The U.S. Bureau of Labor Statistics estimates that the data analyst career will grow 23% between 2022 and 2032 (US Bureau of Labor Statistics).
How to Become a Data Analyst with 365 Data Science
The 365 Data Science program offers one of the best learning experiences, with hands-on data analytics courses, exercises, and projects throughout each course. This approach offers a blend of technical skills and real-world applications.
The instructors at 365 Data Science are experts in their field—working at top-tier tech companies like Meta, Netflix, and Google. You can be confident that the skills and tools you learn from our courses are relevant to the tech industry's current requirements.
If you want to learn more about how to become a data analyst, sign up and check out our data analysis career tracks today.
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