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Train to Become a Data Analyst

General Assembly
August 28, 2024

Our Data Analyst Career Guide Series:

“Everybody needs data literacy, because data is everywhere. It’s the new currency; it’s the language of the business we need to be able to speak.”

Data’s not just a brilliant character on Star Trek: The Next Generation. Although, like space, data is something of a final frontier for businesses looking to get ahead and thrive. Everyone knows if your data’s no good, you’re going nowhere —which is why the demand for data analytics professionals is forecast to grow 35% by 2032 in the US, with similar trends around the globe.

The surge in demand for data professionals spans various sectors, including technology, healthcare, finance, retail, and more. Data analytics is not just about crunching numbers—it’s about uncovering insights that lead to better business strategies, operations, and outcomes.

Best of all? The learning path is flexible. 

Whether you choose a traditional degree or a certified training program like we offer at General Assembly, the key is to find a learning path that aligns with your goals and lifestyle. With the growing demand for data analytics professionals, now is the perfect time to start your training and build a successful career in this dynamic field.

What are the education requirements for a data analytics career? 

While a degree in data science, statistics, business analytics, or a related field can be beneficial, it’s not always essential. Increasingly, data analysts are building prolific careers through targeted training and certification programs.

Here’s a closer look at your options:

  1. Formal education:
    • A traditional four-year bachelor’s degree in data science, computer science, mathematics, or a related field shows employers you can make a commitment to education and stick with it. You’ll get a solid foundation in analytical thinking, programming, and statistical methods.
    • Advanced degrees (Master’s or PhD) can further enhance your expertise and open doors to higher-level positions in the absence of in-field experience.
  2. Certifications and short courses:
    • Employers increasingly turn to online institutions for training and prospecting. For example, General Assembly’s Data Analytics Bootcamp delivers comprehensive 12-week training courses that’ve been used by Adobe, Humana, and Microsoft. A flexible 32-week part-time Data Analytics Bootcamp is also available.
    • Learners can also dive into quick-hit programs—like the Python Programming Short Course—to build specific skills that directly apply to their work.
    • Certifications in specific tools and technologies such as SQL, Python, R, and data visualization tools (Tableau, Power BI) are also highly valued.
  3. Practical experience:
    • Internships, projects, and hands-on experience are critical. Employers look for candidates who can demonstrate their ability to apply theoretical knowledge to modern day-to-day challenges.
    • Participating in data analytics competitions, developing a portfolio of work, and contributing to open-source projects can also enhance your resume.
  4. Soft skills:
    • Communication, problem-solving, and critical thinking skills are key to becoming a good data analyst. Invariably, your interview process will require you to demonstrate the ability to interpret data and communicate your findings effectively to stakeholders.

Is a data analytics degree worth it?

Time, money, effort—the decision to invest finite resources in a particular educational path is a deeply personal choice. Is your goal to deepen your theoretical knowledge, or quickly gain practical skills required on the job? 

Pros of a data analytics degree:

  1. Comprehensive knowledge:
    • A degree program covers a broad range of topics, providing a strong foundation in both theoretical and practical aspects of data analytics, which can benefit your long-term career growth, especially if you want to work your way up to CIO.
  2. Networking opportunities:
    • Universities often offer internship opportunities that allow you to explore different industries, data analytics roles, and potential employers, helping you make more informed decisions before applying for jobs.
  3. Credibility and recognition:
    • A degree from a reputable institution can add credibility to your resume and help you stand out to potential employers.

Cons of a data analytics degree:

  1. Financial expense:
    • Traditional degree programs can be expensive, with tuition fees, textbooks, and other expenses adding up. Student loans and financial debt are considerations that can’t be overlooked.
  2. Time commitment:
    • Earning a degree typically takes several years, which can delay your entry into the workforce. Full-time programs may not be feasible for those who need to work while studying.
  3. Outdated curriculum:
    • The rapidly evolving field of data analytics means that some university curricula may become outdated quickly.

Why choose a data analytics bootcamp? Discover the benefits over traditional college.

In contrast, General Assembly’s full-time and part-time data analytics programs meet the demands of modern jobseekers with:

  1. Accelerated learning: 
  • Data analytics bootcamps are designed to teach you practical skills swiftly so you can enter the workforce sooner. Full-time bootcamp participants can progress from beginner to job-ready in just 12 weeks, while part-time learners can fit their coursework into a flexible 15-hour-per-week schedule over 32 weeks, accommodating their personal and professional commitments.
  1. Industry-relevant skills:
  • Bootcamps emphasize current industry practices and tools, ensuring you learn relevant skills that are directly applicable to today’s job market. For example, General Assembly’s Data Analytics Bootcamp teaches data cleaning, SQL, data visualization with Tableau, and statistical analysis—skills that employers actively seek.
  1. Cost-effective:
  • Bootcamps are often significantly more affordable than a single semester at a public college, making them a cost-effective alternative. Additionally, bootcamps typically offer financial assistance options—such as scholarships, grants, VA benefits, and employer subsidies, or provide flexible payment plans—to further reduce the barrier to entry.
  1. Job–seeker support:
  • The best data analytics bootcamps provide access to industry professionals and potential employers through networking events, workshops, and job placement assistance. Working with career services professionals, you’ll receive assistance writing a resume, putting together your portfolio, preparing for interviews, and researching dream jobs where you’ll put those data analytics skills to good use right away.

But who says these paths are mutually exclusive? In fact, 85.4% of General Assembly bootcamp enrollees have a bachelor’s degree or higher and are looking to either change careers or keep up with evolving skill requirements.

How long does it take to become a data analyst?

Several factors influence the timeframe to become a data analyst, such as:

  1. Prior experience:
    • If you already have a background in a related field or some programming skills, you may be able to accelerate your learning process.
  2. Learning style:
    • Some people may learn faster through intensive, immersive programs, while others may prefer a more gradual approach through part-time courses.
  3. Commitment and dedication:
    • The amount of time you can dedicate to your studies will significantly impact how quickly you can complete a program and start your career.

The educational path you take matters, too. 

  • Bachelor’s degree:
    • If you’re taking the traditional route, take note: the National Center for Education Statistics found that 64% of students take six years to finish their “four-year” degrees. A number of factors affect time-to-graduation, including changing majors, dropping classes, credits lost in transfer, or taking insufficient credits per semester.
  • Master’s degree: 
    • An additional two years for a master’s degree can deepen your expertise and specialization in areas like machine learning, big data, or business analytics. Advanced education can open doors to higher-level positions and specialized data roles, such as quantitative analyst, machine learning engineer, or operations research analyst.
  • Bootcamp: 

Accelerate your path to data analyst

In today’s rapidly evolving job market, traditional degrees are increasingly seen as optional rather than essential for breaking into the data analytics field. According to a report by the Burning Glass Institute, the proportion of jobs requiring a college degree fell from 51% in 2017 to 44% in 2021. 

To fill crucial skills gaps, companies are dropping degree requirements in favor of skills-based hiring, preferring candidates who demonstrate proficiency in tools and technologies such as SQL, Python, R, and data visualization platforms like Tableau or Power BI. This shift reflects the industry’s growing recognition that hands-on skills and the ability to adapt to new technologies are more critical than ever.

General Assembly stands out as a leader in data analytics education, providing flexible, industry-relevant training options that cater to various learning styles and schedules.

Want to get on the fast track for data analysis education? Sign up for our next info session.

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