The field of data analytics is poised for significant growth in 2025. Whether you’re entering the industry or looking to advance your career, the field of data analytics continues to evolve, offering limitless potential and increasing demand. According to Statista, the global big data analytics market is projected to reach $103 billion by 2027, reflecting its growing importance across industries. So you’re wondering how to become a data scientist? Ironhack has designed this guide to break down a data analyst’s role, the skills needed to succeed, and the concrete steps to take as we move into 2025. Let’s get started.
What is a Data Analyst?
Data analysts leverage statistical and analytical techniques alongside data visualization tools to identify trends, patterns, and actionable insights. This gives businesses a competitive edge in understanding consumer behavior, market trends, and operational performance. The role of data analysts is more crucial than ever as data-driven decisions become central to success in every industry.
Pros of Becoming a Data Analyst
High demand: The field of data analytics is growing rapidly, with demand for data professionals rising across sectors. The U.S. Bureau of Labor Statistics projects a 35% increase in data science jobs by 2032, far outpacing other fields. This demand leads to competitive salaries, especially for those with specialized expertise. Diverse opportunities: Data analysts are needed in nearly every industry, from finance and healthcare to marketing and technology, providing versatile career paths aligned with your interests. Intellectually stimulating: The work involves solving complex problems using statistical analysis, data modeling, and critical thinking. It’s ideal for professionals who thrive on creative problem-solving and enjoy intellectually challenging work.
Challenges of the Role
Technical skill requirements: Data analysts must master tools like SQL, Python, and Tableau, which can be a steep learning curve for those without a technical background. Long hours: Cleaning, processing, and analyzing large datasets can be time-consuming, particularly when projects are under tight deadlines. Tasks like data preparation may also feel repetitive for some. Significant pressure: Data analysts provide insights that directly inform business decisions. This responsibility comes with pressure to deliver accurate and reliable results, as errors can have significant consequences.
What are the responsibilities of data analysts?
Data analysts help organizations make informed, data-driven decisions through: Data collection: Gathering data from sources like databases, surveys, and spreadsheets to ensure relevance to the analysis. Data cleaning and preprocessing: Transforming raw data into usable formats by correcting errors, handling missing values, and removing inconsistencies. Data analysis: Using statistical techniques to identify trends, patterns, and correlations within datasets, extracting actionable insights. Data modeling: Building mathematical models and applying machine learning algorithms, such as regression analysis and clustering, for predictive analysis. Data visualization: Communicating findings effectively through charts, dashboards, and graphs using tools like Tableau, Matplotlib, and Power BI to engage stakeholders. Ethical considerations: Ensuring compliance with data privacy regulations, such as GDPR or CCPA, and handling data responsibly.
How to Become a Data Analyst
If you’re considering a career as a data analyst, the path typically includes a combination of education, skill development, and practical experience. Here’s where to start:
Qualities of a Successful Data Analyst
Soft Skills:
Attention to detail: Ensuring data accuracy and reliability by meticulously reviewing datasets and results.
Critical thinking: Analyzing data to solve complex problems using logical, data-driven approaches.
Time management: Managing multiple projects, meeting deadlines, and prioritizing tasks efficiently.
Hard Skills:
Statistical analysis: Proficiency in methods like hypothesis testing and regression analysis to draw meaningful conclusions.
Data manipulation: Mastering tools like SQL and libraries such as Pandas (Python) or dplyr(R) to process and analyze data.
Data visualization: Creating clear visualizations using tools like Tableau, Matplotlib, or Seaborn to present findings to non-technical audiences.
In all, if you want to be a data analyst, it's crucial to possess a balance of hard and soft skills. Data analysts must be able to handle the complexity of the data analysis process and communicate their findings to non-technical stakeholders.
Becoming a data analyst
Knowing that the field of data analytics continues to expand, 2025 may be the perfect year to jumpstart your career as a data analyst. But how long does it take to become a data analyst? That depends on your education, your experiences, and your commitment to pursuing data-related opportunities.
First off, education is key. Most data analysts enter the field with:
Bachelor’s degree
Many data analysts hold a bachelor’s degree in fields such as mathematics, statistics, computer science, information technology, or engineering. A solid foundation in mathematics and statistics is critical for analyzing data and drawing meaningful conclusions. In fact, roles requiring these technical skills are projected to grow significantly, with the U.S. Bureau of Labor Statistics estimating a 35% increase in data science-related positions by 2032 (BLS).
Online courses and certifications
If you didn’t study a related field in university, don’t worry. Today, you can build strong data analytics skills through online courses and certifications. Platforms like Ironhack’s Data Analytics Bootcamp provide hands-on experience with tools such as SQL, Python, and Tableau, preparing you for a career in data analytics in just a few months. According to a report by LinkedIn, continuous learning through courses and certifications has become one of the top ways professionals upskill in tech-driven industries.
Apply for entry level data analyst jobs
Are you wondering how to become a data analyst with little to no experience? We have answers for that too. There are many entry level data analyst jobs for which you undoubtedly qualify. That said, Ironhack has a couple recommendations for you as you pursue data scientist jobs, especially at entry level:
Design a compelling resume: Craft a resume that communicates your technical proficiency, analytical skills, relevant certifications, and any practical experience you have gained. Emphasize your transferable skills, and show off projects, internships, or volunteer work that demonstrate your data analysis capabilities. According to Indeed, recruiters spend just 7 seconds reviewing a resume, so clarity and impact are key.
Cast a wide net: Apply for entry-level data analyst positions even if you don’t meet all the listed requirements. The tech industry evolves so quickly that employers often value soft skills—like a willingness to learn, adaptability, and flexibility—more than specific technical expertise. A study by LinkedIn revealed that 57% of employers prioritize soft skills when hiring candidates for entry-level positions. If you’re the right cultural fit for the company, they’ll likely invest in training you. Don’t be intimidated by a lengthy job description.
Show up prepared: Be well-prepared to discuss your technical skills, experiences, and problem-solving skills during the interview. Ask individuals in your professional network about what you should expect from the interview process. And be ready to communicate your knowledge and passion for the field.
By following these steps, you will be in a great position to secure an entry-level data analyst position. If you want to gain more knowledge or experience, there are many online courses and certificate programs that can equip you with the necessary skills to be successful in an entry level position. Our number one recommendation for folks interested in entering the field is bootcamps.
Ironhack offers both online and in-person bootcamps in data analysis. Our bootcamps are specially designed by professionals in the field in order to equip our students specifically with the skills and knowledge that are in high demand. We invest in your success through our career coaching programs and we count on a strong alumni network to support our students entering the field. That said, what are you waiting for?
