Is Data Analyst a Good Career?

The big data analytics market is expected to grow at a breakneck pace in the coming decade, with the sector expected to reach $346.33 billion by 2030. While this growth is a good sign in general, recent layoffs and stiff competition for existing jobs are creating short-term turbulence which has left many prospects wondering whether a career in data analytics is worth it.

With that in mind, the following article discusses the data analytics job market,  whether data analysts are still in demand, the pros and cons of the job, and whether AI will affect jobs in this industry.

Is Data Analyst Still a Good Career?

The job outlook for data analytics remains overwhelmingly promising today. According to the US Bureau of Labor Statistics, jobs in the data science field are going to grow at 35% between 2023 and 2031, which is much higher than the average for the labor market overall. That’s going to translate to 40,500 jobs added to the field over that decade.

The high demand for data analysts across industries has fueled its status change into one of the more lucrative jobs in tech. The current average salary for data analysts is just under $80,000, which is much higher than the job market average. Companies are already coming up with ways to deal with the data analyst talent shortage, and we can expect salaries to continue rising as the squeeze on talent increases. 

Data Analytics Job Market and Demand

Here’s what the demand for data analysts looks like today.

What Is the Scope of Data Analytics?

Data analytics is the process of analyzing large volumes of data to produce meaningful insights. Because digital data has become more universal in business operations, data analyst professionals are hired across almost every industry today.

The finance industry is one of the top use cases for data analytics today, with companies like Bank of America, Goldman Sacha, and PWC hiring large numbers of data analysts for roles in quantitative and financial analysis.

Telecommunications, retail, healthcare, and transportation also see large numbers of data analytic hires, as well as new posts for related positions like business analyst and business intelligence analyst, all of which indicate a wealth of opportunities in the field. 

Are Data Analysts in Demand?

Data analysts are in demand across a wide variety of industries. In fact, demand is so high that companies are facing a talent shortage. The demand for data analysts does, however, tend to vary bystate. New York and California tend to hire data analysts in the highest numbers.

A Career in Data Analytics: Pros and Cons

Let’s find out about some of the advantages and disadvantages of working in this role.

Pros 

Here are some of the best parts of a career in data analytics:

The Data-Fication of Everything

We live in a world where copious amounts of data are available, and it’s hard to overstate the value of that data. Recent reports suggest that we produce over 300 million terabytes of data every single day.

Most of this data would be useless if not for the complex analyses made by the data analytics field. Because of this, businesses can now conduct various forms of numerical and descriptive analysis to generate actionable insights.

Multi-Industry Relevance

Today, you can work as a data analyst in a wide range of industries, from entertainment to healthcare to sports. That also means more data analyst jobs are popping up, so you have more choices at your disposal.

Working on Pioneering Technology

A lot of the most exciting work in computer science research today involves data analysis. This is a field with great commercial value, so businesses contribute to the pioneering work in this field. In addition, academic institutions also invest significantly in data science and contribute to the field’s growth in a big way.

What does this mean for the work that data analysts do? There are always interesting new technologies and tools to try out as part of your job. It also means that your skills are relevant in some cutting-edge fields, such as machine learning and artificial intelligence.

Flexible Work Opportunities

Companies are becoming increasingly open to remote work for data analysts. This may not be true if you work with sensitive data, like contracts for government projects. But for the most part, data analysts have the option to work wherever they please.

That flexibility has caused many data analyst jobs to become location-independent. That means people across the country have access to the same roles, regardless of location. 

Cons

Here are some of the downsides to a career in data analysis:

Increasing Competition

With all those positives, there is going to be an increasing amount of competition for data analyst jobs in the coming years. It has already become easier to gain professional skills in data analysis thanks to bootcamps and free online resources. As demand increases, there is sure to be an influx of talent in this field. That means you will have to work harder to stand out from the crowd in each interview you do.

Repetitive Work

As a data analyst, you must prepare yourself to do repetitive work, especially early on in your career. The successful data analysts are the ones who are able to deal with some of the boring parts of the job but also find ways to infuse novelty into it by learning how to use new tools or optimizing their process.

The Need for Constant Evolution

As we saw in the previous section, data analysis is a field where there’s a lot of exciting research happening. While that can be invigorating, it also means that data analysts need to work hard to stay abreast of developments in the space.

There are a few ways to make that happen. Data analysis certifications are a great way to upskill and learn from industry experts. You can also take free online data analytics courses. But what’s important is that you remain active in your educational journey and are always prepared to invest time to pickup new analytics skills.

Stressful Work Conditions

Working in data analysis can be stressful at times. Analysts often work under tight deadlines, and workloads can increase drastically during periods such as new product launches.

This situation can be compounded by the fact that data analysts often work independently. You might not always have a team that you can turn to to help you make sound decisions on the job. So you need to be prepared to work autonomously even during periods of stressful work.

Who Should Consider a Career as a Data Analyst?

While data analytics is evidently a good career option, it’s not necessarily for everybody. Here’s how you can figure out whether it’s the right job for you.

Data Analytics Is for You if…

You’re Naturally Curious

Data analytics as a field is driven by a deep curiosity about what data reveals. That curiosity extends to each practitioner and anyone who has a successful career in this field. If you’re someone who is curious about the world and often uses numbers to answer your own questions, then that’s a strong sign that you would be a skilled data analyst.

You Enjoy Working With Numbers

You do need to have strong math skills if you want to work as a data analyst. More to the point, a basic understanding of concepts in linear algebra, calculus, and probability is essential in order to work with data. You also need to have a strong understanding of statistics since statistical analysis is a common task in data analysis.

You Can Simplify Complex Concepts

Communication skills are important if you’re a data analyst. Your job will often involve explaining your work to non-technical team members and managers, so you need to have the ability to break down complex concepts and communicate your findings using visualization tools.

Data Analytics Is Not for You if…

You Can’t Work Autonomously

Data analysts are often required to work independently. This doesn’t mean that you will be completely isolated from your team, but you will have to come up with ways to produce analytics insights independently. If you’re unable to do those things on your own, you won’t go too far as a data analyst.

You’re Uninterested in Business Strategy

Data analytics is a technical field, but that doesn’t mean that you can get by with just coding skills. All of the work that you do will be closely linked to the business goals of your organization. You need to have a basic understanding of the business context of the work that you do so that you can generate the requisite business insights.

You’re Easily Discouraged

Data analysis is the kind of job where you quite often won’t know exactly what you’re looking for. The exploratory nature of this job means that there will be many instances where you have to be persistent, even in the face of uncertainty. People who are easily put off by such a working environment might not enjoy working as data analysts.

Becoming a Data Analyst: General Prerequisites

Let’s say that you’ve figured out that data analysis is the right career for you. What do you do next? Here are a few bases that you should cover so that you can land a job in the industry.

Foundational Knowledge

Math is a good place to begin your training as a data analyst. It’s essential that you have a strong base in areas like probability and statistics. Also, try to cover basic problems in linear algebra and calculus.

You can then move on to learning a programming language. Python is a good option if you’re just starting out. It’s a language with simple syntax and intuitive structures. You can then move on to a language like R if you’re interested in doing math-heavy analytical work like building statistical models. 

You can then move on to combining those two things and working on basic data analysis. Working on projects is a good way to transfer theoretical skills into the real world. You must also have exceptionally strong verbal skills, and an affinity for explaining your math to non-math people in words and infographics. 

Education

There are a few educational options at your disposal as an aspiring data analyst. If you want to go the conventional route, then you can get an undergraduate degree in computer science or IT. If you’re someone who’s self-taught as a data analyst, then you might also consider a business degree.

Nowadays, it’s also possible to pick up key skills by completing a data analysis bootcamp. These are less time-intensive and more affordable than a college degree. Some even come with a job guarantee.

Skills

Here are a few skills that you will need to work on if you want to break into entry-level positions in data analysis.

• Data Mining: This is the process by which data is obtained from different sources and provides the raw material for the rest of the data analysis process.  

• Data Preparation and Cleaning: These steps turn unorganized data into data that is amenable to the analysis process. It achieves things like correcting faulty values, eliminating duplicates, and so on. 

• Data Visualizations: Visualization takes raw numbers and transforms them into visuals that can be easily comprehended. Doing so helps data analysts themselves spot trends in data and produce reports for a lay audience. 

• SQL: This is a commonly used language to manipulate data in databases. You need to be able to write queries to retrieve and input data into databases. 

Tools

Here are a few tools that you should consider learning as a data analyst. 

Data Mining

• RapidMiner
• KNIME
• Heap

Analysis

• Apache Spark
• Microsoft Excel

Data Visualization

• Microsoft Power BI
• Tableau 
• Looker

Other Requirements

While it’s common to work on technical skills, it’s also important to work on your soft skills as a data analyst. Communication skills are prime among these. You should be able to collaborate with different team members efficiently. Your communication skills will also come into play when you have to present reports to different stakeholders in a project.

What Does the Career Path for a Data Analyst Look Like?

Data analysts usually begin their careers as junior analysts. This is a stage at which you’re given specific datasets and told exactly what kind of insights you need to generate from them. Most of your work will involve basic programming in languages like Python and SQL.

Junior analysts who accrue two years of experience can move on to the senior analyst role. Senior analysts are given business problems that they need to work to solve. A lot of the analysis at this stage is exploratory in nature. You will often be required to learn how to use tools like Apache Spark to streamline the work that you do as a senior analyst.

There are a few paths that your career can take at this point. Senior analysts with five or more years of experience are considered for the data engineer position. This is a role in which you will be required to engineer data systems and oversee data handling at different stages of the analysis process.

You could also take the managerial path at this stage. The project manager role is one where you have to straddle the technical and people management side of things. Project managers oversee entire projects by managing resources, creating roadmaps, and ensuring timely delivery at different stages of the project.

How Will AI Impact Data Analysis?

AI has always been in the picture in the field of data analysis, as artificial intelligence algorithms have always been used to automate some aspects of the analytical process and to enhance exploratory data analysis.

At this juncture, it’s not really possible for AI to automate the entire data analysis process, given everything that’s involved in gaining actionable insights from large amounts of data. If anything, AI will continue to make the job of data analysts easier and serve as an assistant in the analytics process.

What Does the Average Salary for a Data Analyst Look Like?

Here’s what you can expect to make at different stages of your career as a data analyst.

Entry-Level

Entry-level data analysts have an average salary of $51,980.

Mid-Level

The average salary of a mid-level data analyst is $94,717.

Senior Level

Senior data analysts make a salary of $101,301 annually.

Pursuing a Career in Data Analytics: Real-Life Examples To Inspire You

It always helps to have people whose experiences you can learn from as you try to build a career in the field of data analysis. Here are a few examples.

Andrew Hershy

Andrew Hershy comes from a background in healthcare consulting and accounting. He decided to give learning data analytics a try since he used to work in Excel a lot as part of his earlier job. In the linked post, Andrew goes over the different stages of his learning journey, including specific projects and courses he took to learn data analytics.

Wale Gbads

Many people wonder if it’s possible to self-learn data analysis. In the linked video, Wale Gbads goes over some easily accessible resources that you can use to pick up key skills as a beginner in data analysis. He categorizes these under querying, cleaning, statistical and non-statistical methods, and visualization, so you can easily pick resources based on the areas where you need help.

FAQs About Careers in Data Analytics

We’ve got the answers to your most frequently asked questions.

Since you’re here…
Interested in a career in data analytics? You will be after scanning this data analytics salary guide. When you’re serious about getting a job, look into our 40-hour Intro to Data Analytics Course for total beginners, or our mentor-led Data Analytics Bootcamp.