How to become a data analyst

If you are looking for a versatile career skill that can be applied to a range of different high-paying, in-demand jobs, you may want to consider learning data analytics. Per the Bureau of Labor Statistics, data-related jobs are projected to grow 35% from 2022 to 2032, nearly twelve times faster than the national average of about 3% growth. Almost every industry is becoming more and more attentive to how data collection and analysis processes can help them better achieve their business goals, so learning data analytics is a great way to put yourself in demand regardless of the kind of field you want to enter. This article will provide you with an understanding of what skills you’ll need and what kind of training is necessary to become a data analytics professional.

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What skills will I need to find a data analytics job?

There are two general paths that aspiring professionals can learn when looking to find a job in a data-related field. They can either focus on the practical or theoretical side of the coin, more colloquially, they can focus on data analytics or data science. In short, analysts turn existing data into business action whereas scientists build the pipelines and models responsible for creating and collecting that data. There is enough overlap between the two that professionals on either side of the coin will be able to generally do some of the same professional tasks, but by and large, there are enough differences between them that you’ll need to specialize somewhat early in the process to become more skilled at your specific set of skills.

Data Analysts are the professionals who take data and apply it to practical, real-world scenarios, usually at the behest of an individual company, firm, or institution. They are the ones who run the numbers on a marketing campaign, product launch, new business initiative, team-building strategy, or basically anything that industries do that calls for the collection of raw data. They are also the ones who interpret that data and use their related skills to make recommendations based on the analyses. This means that they will also likely want to pick up a lot of knowledge about the specific field or fields in which they are aiming to work (so someone working in a marketing department as a data analyst needs to understand the industry in which they are operating, while an analyst for the Chicago Cubs will probably need to understand baseball).

Data Scientists deal with the more theoretical aspects of data collection and analysis, usually focusing on building and maintaining the tools and infrastructure that other data professionals utilize to collect, read, and interpret data. For example, Tableau is a data visualization application that allows users to organize and translate their data into interactive dashboards and rhetorical presentations. A data analyst will use Tableau to make a relevant, specific dashboard that they can use to read their own databases and provide stakeholders with relevant information based on the output of Tableau. A data scientist programmed and built the systems that allow Tableau to easily and quickly read specific databases and update itself based on changes to that data. The data science side builds and perfects the tools that the data analytics side puts to practical use in a professional context.

Regardless of which path you choose, data analytics careers are high-paying and in demand since data training is so important to producing consistent results for everyone, from businesses to investment firms to sports franchises. Depending on location and experience, a Data Analyst can anticipate a salary of around $108,000 dollars per year, with higher salaries available for professionals who can work with more complex data and machine learning-related projects. In addition, relative to other career fields, data jobs are on the rise. 

Things you’ll need to become a data analyst

If you are preparing for a career change and you are looking for a position in data analytics, there are a few things you’ll want to make sure that you have:

• A certificate or degree: You’ll need some evidence of your professional training, whether that is your college degree or a certificate from a professional training program
• A compelling portfolio: One of the most important things you’ll need is evidence of your work beyond your degree. This is most often demonstrated through a digital portfolio (often hosted on a personal website) that contains the work you’ve done in capstone projects or in the professional field of data analytics. A few possible projects that make for good sample portfolios include:
• Charts and graphs tracking commodity values
• Heat maps designed to isolate important correlations in data
• 3D and dual-type chart models in Tableau
• An understanding of your field: It is very likely that you’ll be asked to interview for the position, during which time you’ll need to demonstrate an understanding of the industry in which you plan on working and the company that you are interviewing to work at.
• Persuasive skills: While it is primarily a quantitative and math-driven field, successful data analysts need to know how to make their data tell a story and provide a persuasive and actionable plan for invested stakeholders.

Where to learn data analytics skills

If you are looking to start learning data analytics skills to start a professional career, you’ll find that you have a lot of different options, ranging from self-teaching the skills with on-demand classes to college programs related to data. With so many options, it can seem overwhelming at first, but this also means that you will be able to easily find the kind of data analytics training that suits your professional goals. 

Students can self-teach data analytics using self-paced and on-demand training programs, though this is likely to be the least effective overall method because it is the method that relies the most heavily on your own commitment to the studies and your own ability to pick up the skills on your own. On the other end of the spectrum, you can enroll in a college degree program in something like computer science or business administration which will likely cover some amount of professional data analytics training. This is likely to be the most immersive option but also the most expensive and most time-consuming.

A solid middle ground between these two is a professional training program like those offered by schools like Noble Desktop, General Assembly, and Fullstack Academy. Available online or in-person, these classes are accelerated, career-focused data training seminars that aim to provide students with practical, real-world skills that they can use in the professional field as soon as they graduate. Students will receive training from professional instructors just like they would in a college setting, but the accelerated nature of the courses means that they will cost less than a single college semester (and likely be done quicker than one semester would). 

These programs also tend to offer students various career support services to help them on the job market, including mentoring sessions, networking opportunities, and even job placement support. These vary from program to program but are worth considering as part of your training. One of the best ways to navigate all of the different course options available to you is by reading through the guide to data analytics classes in NYC to see what is available for both those local to the city and those learning remotely from home. 

Cost and financing options

One of the most substantive issues that you’ll need to address is the cost of your course, which can often be several thousand dollars. With that in mind, most training programs offer some options for financing your training or they offer installment plans for students looking to spread out the cost of these courses. The financing options available will differ between programs, so be sure to check with the various service providers you are looking into to see which financing options make the most sense for your situation.