How To Become a Big Data Analyst (With Salary Expectations)

By Indeed Editorial Team

Updated November 23, 2022

Published September 29, 2021

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

If you're skilled in data analysis, then a career as a big data analyst may interest you. Big data analysts help companies of all sizes analyze huge sets of data and provide findings that help them make informed decisions. Understanding what tools are used in big data analysis and the job's education requirements can help you better prepare for this career.

In this article, we explain what a big data analyst is, explore what they do, provide a step-by-step guide on how to become a big data analyst, and share the national average salary and job outlook.

What is a big data analyst?

As the name suggests, a big data analyst applies technical skills to analyze large data sets and provide insights that companies use to improve decision-making. Analyzing big data requires specific training to get accurate results. On a typical day, big data analysts use several analytical tools to find valuable information and communicate their findings to stakeholders. They may discover hidden trends, patterns in data, and correlations between large sets of data.

What does a big data analyst do?

The primary role of a big data analyst is to translate large data sets into digestible and reliable information. They do so by studying the market, collecting data and analyzing it, and then turning it into coherent formats such as graphs and reports. A company may also hire a big data analyst to interpret previously collected data.

A big data analyst needs the right tools to process large data sets in a short period and share their findings. Formal training ensures you can use big data tools comfortably on different projects. Some common tools include coding languages, database management systems, and open-source software frameworks. A gig data analyst's responsibilities include researching, mining data, programming and coding, extracting valuable information, organizing data, and presenting their findings.

How to become a big data analyst

Earning certain academic and experience qualifications can help prepare you for this field. Here is a breakdown of how to become a big data analyst:

1. Education and training

You'll need a degree in computer science, finance, economics, statistics, math, or information management. Consider earning your bachelor's degree in any of these fields. If you're unsure which degree program is right for you, consider speaking to a career counsellor who understands the big data analyst career path.

Note that the amount of time you need to complete a degree program varies based on several factors. The learning institution you choose and whether you're studying full- or part-time may determine how soon to earn your degree, although it typically takes three to four years.

2. Gain data analyst experience

The next step is to gain valuable experience. You become more employable when you have prior experience. You need to prove to potential employers that you have an applied skill set, which is why you benefit from finding relevant work experience as soon as you finish your degree. Internships offer a good opportunity to gain hands-on experience. You'll have an opportunity to work alongside experts in the industry as you prepare for the various responsibilities that are awaiting you.

3. Advancing in your career

Your willingness to continue learning is vital in advancing as a big data analyst. Data analysis evolves, and if you wish to remain competitive, updating your knowledge has to be a top priority. You can take action to maintain an upward trajectory in your career, including:

Take as much on-the-job training as possible: Most companies empower their employees through in-house training. Focus on training related to big data, as it's vital in building the skills needed to support your career growth, although courses on other topics can make you a more versatile employee and improve your employability.
Consider getting a master's degree: An advanced degree in a discipline like data analytics, data science, or data management offers more job opportunities and makes it easier to advance in your career. It provides exposure to the latest knowledge, trends, and analytical tools from professionals in the field.
Enrol in certificate programs: Certificates are a good alternative to a degree and give you an inclusive overview of the subject in a shorter period of around 12 months. Some of the short programs you may want to consider include Complex Data, Data Abstraction, Simple Data, and Object-Oriented design.

Skills needed to become a data analyst

Besides earning the right certifications, some skills will make you more desirable to employers. Below are those you must have or that have the potential to improve your chances of securing a data analyst position:

Communication: Preparing and presenting reports are some of the core activities in the life of a data analyst. You need excellent written and verbal communication skills to compile comprehensive reports and explain complex data to others.
Creativity: Analyzing large data sets is complex and requires several specialized tools. Creativity is needed to use different tools for effective data analysis.
Teamwork: Be prepared to deliver when you're working alone and when you're part of a team. You may often find yourself working alongside other experts such as researchers, statisticians, and IT experts.
Critical thinking: While analytical tools handle a large component of the work, your ability to deconstruct information into smaller bits to draw valuable conclusions from is crucial. You must be able to interpret all the data and share valuable results.
Willingness to learn: The big data analysis field keeps evolving, and to remain productive you must be prepared to update your knowledge and skills regularly.
Data visualization: As a big data analyst, you need to understand how to scale visualization. You must also demonstrate expert knowledge using various visualization tools to present your findings in the best way possible.
Attention to detail: The accuracy of your conclusions is crucial as a big data analyst. How attentive you are with your analysis largely determines the validity of your findings.
Curiosity: Curious people like to find out why something happened differently, which often helps them develop new ideas. One task for big data analysts is to find new patterns and behaviours in the data they analyze; curiosity helps them question their daily routine and can result in new findings.
Business acumen: Different industries have different needs. You must demonstrate how you can handle the needs of a business. This requires understanding how a business operates in order to ensure your work can help the business meet its goals.

Big data analyst salary

A glimpse at what a big data analyst earns can help you decide if this career is for you. If you intend to focus solely on this career to pay your bills and achieve other goals, it makes sense to get an idea of the typical salary. The national average salary for a big data analyst is $62,468 per year.

This amount varies depending on your experience, employer, and geographical location. You can use a few strategies to become more competitive, including:

working for industries with a higher demand for big data analysts
upgrading your knowledge
choosing a city with favourable compensation regulations

The job outlook for big data analysts

With data increasingly becoming one of the most valuable assets globally, the future of big data analysis continues to be promising. The projected labour force shortage up to the year 2028 due to expansion demand and replacement demand is another indicator this career path is worth considering.

Salary figures reflect data listed on Indeed Salaries at time of writing. Salaries‌ ‌may‌ ‌‌vary‌‌ ‌depending‌ ‌on‌ ‌the‌ ‌hiring‌ ‌organization‌ ‌and‌ ‌a‌ ‌candidate's‌ ‌experience,‌ ‌academic‌ background‌, ‌and‌ ‌location.‌