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Almost every sector uses data to solve problems and understand trends and developments. But raw data is not enough to work with – organizations need talented data analysts to extract meaning from the data they have to work with. If you are a solution-focused individual with the ability to find patterns, a career in data analysis may be for you.
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In this article, we will not only cover the above steps in more detail, but we will also consider what a career path to becoming a data analyst might look like along with the skills needed for it. Every data analyst career path will look a little different depending on their chosen industry and specific role. However, the following steps are highly recommended for anyone who wants to become a data analyst.
How To Become A Data Analyst In 2023: 5 Steps To Start Your Career
As with any scientific career, data analysts require a strong foundation in mathematics to succeed. It may be necessary to review and, if necessary, improve your mathematical skills before learning how to become a data analyst. Check out the list below for some important areas of study!
As arguably the most important area of expertise for data scientists, the field of statistics underpins all aspects of data analysis. Having an understanding of statistics means being able to analyze large data sets for high-level insights. General statistical concepts to know include probability distributions, statistical properties, and Bayesian statistics.
College-level algebra is often used in data analysis. In particular, linear algebra is necessary for professionals who aim to work with machine learning and/or AI, as most algorithms use it. Due to the rise in machine learning and integration with AI in data science, these basics are likely to become more important over time, as well.
Similar to algebra, calculus is essential for working with AI, and can be used to help teach pattern recognition to machines. Functions such as color descent or derivatives are among the most common in data science.
How To Become A Data Analyst: Education & Skills Guide
Mathematics is the backbone of computer systems used to analyze data, making understanding essential. The study of discrete mathematics requires abstract thinking and the knowledge of reasoning that accompanies mathematical thinking. Related areas of study include logic, evidence, and data structures.
Regardless of career path, employers will expect a certain level of education from incoming data analysts. There are many ways for learners to meet these data analyst educational requirements. While a college degree is the most common – with a master’s degree in data science or a doctorate expected for advanced data analysts – other paths are available if you are willing to work and dedicate yourself. Data science can often provide a faster turnaround in building foundational skills and greater flexibility for analytics professionals looking for an alternative to traditional education.
College degrees, whether achieved online or in person, offer comprehensive coverage of data science and analytical principles. A growing number of colleges and universities are offering courses that include specializations in fields such as analytics, data engineering, or artificial intelligence. However, for some entry-level positions, even a degree in mathematics, statistics, economics, or computer science can be a good starting point.
That said, some aspiring data analysts may not have the time, resources, or inclination to pursue a four-year degree and may be better served by an alternative education path. If you are wondering how to become a data analyst without a degree, you may want to consider data analysis.
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Data analysis is a faster and often less expensive option compared to the formal level. Although fast and rigorous, it prepares you with job-ready skills and takes as little as three to six months to complete. Learning from one of these courses means gaining the foundation of the most sought-after data skills in the market and benefiting from a supportive and collaborative learning environment. Additionally, most offer flexible enrollment options, such as online classes, for those who want to continue working while they learn how to become a data analyst.
I want to… Which best describes your goals? Start a new career, change your career path, advance your current career, start/build a business, don’t like to talk about anything else, start a new career, change your career path, improve your career, become an entrepreneur, finish your first job, don’t like to talk about anything else
Neither path is strictly “right” – both have advantages for different lifestyles, skill levels and learning preferences. For example, someone with existing experience looking for a quick career pivot may be better suited for the quickest job readiness.
The holistic nature of data analytics often requires aspiring analysts to hone their soft skills as well. Data professionals may be able to extract useful information from large volumes of data, but this means nothing if they cannot use it in a professional environment.
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No matter where you are in your career, you should be able to explain your findings to a diverse audience. Data analysts work with data that affects all levels of the organization, so being able to communicate findings to colleagues with different levels of technical knowledge is essential.
Data analysts should be critical thinkers and problem solvers who can see all angles of a problem and find appropriate solutions. With this comes a thorough understanding of the organization, its needs, and what can be done to improve operations. A curious nature is also an ideal trait for those seeking a career as a data analyst; After all, at its core, this field focuses on asking questions and uncovering information.
Although it may seem counterintuitive, soft data analysis skills can be taught. Some online courses can provide everything from a basic overview to an intensive study of soft skills related to business. Seeking advice or feedback from professional colleagues can also give you a path for improving your particular skills.
Even if you already have a job as a data analyst, your education may not be over. As mentioned earlier, senior positions in the field may require a master’s degree or even a doctorate. The position may require three to six years of additional learning. Of course, this increased investment comes with strong returns – more experience and education can increase your earning potential and growth (PDF, 1.9 MB) in your data analyst career path.
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Of course, the growth rate and demand may vary by industry. While a bachelor’s or bachelor’s degree may open up more opportunities for you, it may not be necessary when pursuing an entry-level role.
Then, once you’ve completed a study program that fits your goals, learning preferences and lifestyle, you can start looking for a job. Data analysts are in demand in almost every industry you can think of – from healthcare and marketing to big tech and finance. Your chances for employment as an information specialist are very close.
If you have completed a project as part of your studies or elsewhere, you may want to consider compiling your best work into a portfolio. Update it often as you complete more work and include it in your application – interested employers are more likely to be compelled by what you can do than any cover letter.
You should also think about networking in the field of data analysis. Depending on your location, some cities may offer conferences for current industry professionals, and conferences are a great way to learn about industry updates and make more contacts.
Master Of Analytics
Additionally, you’ll want to update your resume and online presence with the most recent information possible, including any educational certifications or analyst credentials you’ve recently acquired. If you have time, it can be worth combining all this information into a personal website to send to prospective employers.
It can be scary to take your first steps in a competitive industry, but there are many opportunities for skilled data analysts, even if you are new to the workforce! Go into your job hunt with goals in mind for desired salary, company culture, and industry. Are you willing to earn more analyst certification to stand out? Can you relocate if necessary? Being able to answer these questions definitively can appeal to employers.
When searching, tailor your document to the company you are applying to. Some roles may focus on specific skills, so don’t be afraid to highlight them when applying. This is especially important considering the breadth of expertise required in the field of data analysis.
Most importantly, don’t be deterred by rejection! If you are passionate about data analysis and have the education to perform well, you may find an opportunity that fits your needs. Even if you feel unqualified for the position, apply anyway – a little practice can help you land the next interview.
Data Analytics Program
While most data analysts share common expertise, an analyst’s specific responsibilities and daily schedule may vary by industry and their specific role.
Although widely used to indicate the classification of data
