Data analysis has become a huge contributor to the success of most businesses out there today.  As you know, we spend a large chunk of our professional and personal time online. We use websites and web applications for things ranging from meetings and research to tasks like shopping, ordering food, and connecting with our friends. Every second that we spend online creates a large amount of data, which can be used to analyze our preferences and behaviors.

Data analysis refers to the process of collecting, cleaning, and analyzing this data to draw valuable insights from it. These insights and conclusions can be further used by businesses to make important decisions. Basically, if businesses know how their target audience acts online, they can market to them better.

We've got a list of some of the most common ways to get started in data analysis, and the pros and cons of each.

What Data Analysts Do

Data analysts are professionals who process raw data related to products, customers, and a company’s performance. Then, they translate this data into an easy to understand format for business stakeholders. Once they’ve seen the data, their job is to gather insights from it. Once these insights have been made, business managers are able to make informed decisions to benefit the business.

Train to Become a Data Analyst

As more businesses realize the importance of using data to understand their market and customers, the demand for data analysts has grown significantly. More and more organizations are using data analytics to help their businesses grow.

If you’re interested in pursuing a career in data analytics, it’s safe to say that you’ll be entering a challenging and rapidly evolving field. As the field grows, so will your career opportunities; so rest assured that working in this field will be super rewarding.

To start a career in data analytics, you need to learn the necessary skills. There are a variety of paths you can take to do this. It’s important that you find the one that fits your lifestyle the best! You want to enjoy your education journey so that you can get the most out of it.

We’ve listed the different ways that you can train to become a data analyst below.

Education Paths

There are multiple paths that you can follow to get an education to become a data analyst. Depending on where you’re at in your career, you can go for the path that suits you the best. For example, if you just graduated from high school, maybe you’d prefer to go to get a college degree in data analytics or a related field. However, if you’re a working professional who wants to change your field to data analytics, then online training programs and online courses might be a better fit for you.

Here are some of the different paths that you can take for your education and training in data analysis:

Bachelor’s Degree If you choose to get a bachelor’s degree, there are a few options. Some preferred disciplines for an undergraduate degree include computer science, mathematics, statistics, and information technology. If you have a set of high professional goals in this field, you can pursue a master’s or a doctorate later on in your studies. Further education can help you move ahead in your career, and help you qualify for senior roles in data analytics.

Master’s Degree – A master’s degree in data analytics is not necessary, but it can be useful for upper-level data analyst jobs. If you’re a professional with a background in STEM and you’re interested in the process of gathering, organizing, and analyzing data, then a master’s degree in data analytics might be a good option for you. This degree focuses on data operations and advanced analytics.

In a master’s degree, you’ll learn how to:

A Ph.D. in data analytics can open up high-level career avenues for you. However, most of the time people pursuing a doctorate work in the field of research. Most of the career opportunities for doctorates are limited to academic positions and research roles in corporate organizations.

Online Courses and Training Programs

There’s a rise in online courses and training programs for data analysts. This mode of education can be taken by anyone from any part of the world. It’s especially well-suited for working professionals who want to change their career path and start a new career in data analytics.

Professionals with a strong inclination towards mathematics and statistics might love the field of data analytics. If that’s you, you should consider online courses and training programs to strengthen your knowledge and provide you with the skills you need. Advantages of online courses include:

Data analytics bootcamps are another way to start learning this in-demand tech skill. They’re short-term programs that’ll provide you with intensive education and skills required to land a data analyst job. This mode of learning and training has become more popular recently thanks to the convenience of learning at home, with a flexible schedule, and the appeal of learning skills that lead directly to a long-term career.

Our Data Analytics Bootcamp teaches you to master the following skills in only 6 months:

There are many advantages of learning through bootcamps. First of all, bootcamps are cheaper than traditional college degrees. Our Data Analytics course doesn’t even charge you until you’ve landed your first job in the field. Bootcamps are also useful because the entire learning experience stays relevant to the subject. You can focus on what you want to learn instead of being required to take irrelevant filler courses. Because bootcamps provide you with a lot of information in a short amount of time, they’re quite intense, and many people prefer that style of learning.

However, there are some drawbacks to learning in bootcamps as well. Since bootcamps compress the coursework and teach it all in a period of six to eight months, you could get exhausted by the workload.

Certifications in data analysis can help your resume to stand out in the competitive job market. They can also help you pave your way for new job opportunities, and even help you get a hike in your salary. Certifications also validate your skills.

However, since certifications are industry-based, you should first choose where you want to specialize. A bachelor’s degree in computer science, math, or statistics is necessary to qualify for certain certification exams too.

Data analyst certifications are provided by a ton of reputable platforms and universities. Some important certifications include:

Train Yourself in Data Analytics

Despite the large amount of knowledge needed to thrive in this career, there’s been a rise in the number of self-taught data analysts. This mode of learning requires a lot of hard work, patience, and dedication. However, you’ll have the flexibility and freedom to learn at your own pace. After you gain knowledge in business and statistics as well as the additional skills that you need, you can go for certifications that will validate your understanding of the field. Once you’ve done this, you can start to build a portfolio and apply for data analyst internships and jobs.

However, some disadvantages of this method include a lack of guidance and mentorship. You might end up wasting a lot of time digging through irrelevant resources and tutorials. Without a structured learning process of assignments and tests, you may also get lost in the sheer amount of information available online.

Despite the cons, there are a lot of professionals who have overcome the challenges and successfully started their careers in data analytics by learning on their own. Just go in armed with all the resources you need.  

Skills Data Analysts Need to Know

Regardless of which path you follow to learn the full range of data analytics skills, there’s a baseline of information that you need to know. As data analysts deal with a large quantity of data daily, they need to be proficient in a certain set of skills.

Some of the technical skills that a data analyst should know are:

Structured Query Language (SQL) SQL is a database language used for handling large datasets that can’t be handled in Excel. It’s ideal for managing and storing data, and relating multiple databases, among other things.

Data Visualization Data visualization refers to the skill of presenting the findings of data in the form of graphics and illustrations.

Data Cleaning – Data cleaning is one of the most crucial steps while compiling machine learning models. A dataset that’s thoroughly cleaned and organized can even beat fancy algorithms.

Python – Python is a high-level programming language that offers a plethora of specialized libraries, all are related to artificial intelligence.

Machine Learning The field of data science is abuzz with new applications for artificial intelligence and predictive analytics. A knowledge of machine learning has practically become a prerequisite for data analysts.

So as you can see, there are plenty of options available to become a data analyst. You can train and learn the skills in a variety of ways, so find the one that suits you best. If you’re still unsure of which direction to go, you can reach out to our admissions teaml for some help deciding on the best path toward a tech career.

If you still want to learn more about the field of data analytics before making any big leaps, our data analytics blog is jam-packed with useful information. We’ve already done the heavy lifting: learn everything you need to know before you decide if this is the right field for you.

Share this article