Today, more and more companies are hiring data analysts to derive actionable insights from huge volumes of raw data. These insights are crucial if companies want to make informed decisions and drive better outcomes.
In fact, according to an EY study, 93 percent of companies indicated they plan to continue increasing investments in data and analytics in order to reach a higher level of maturity. As a result, the U.S. Bureau of Labor Statistics (BLS) expects the employment of operations and research analysts (including data analysts) to grow 23 percent from 2021 to 2031, much faster than the average for all occupations. According to the most recent Dice Tech Salary Report, the average salary for a data analyst stands at $83,779, up 11.5 percent between 2021 and 2022.
While a college degree may be a great foundation for a career in data analytics, choosing the right major can be challenging. Data from Zippia shows that data analytics professionals possess a wide variety of backgrounds and degrees.
Confused? Here’s how to decide what degree and skills you actually need to start a career in data analytics.
Pursue (Almost) Any Degree
While data analysts exist at the intersection of information technology, statistics and business, you can break into the field with almost any degree or curriculum, provided you’re exposed to data modeling, visualization, and related techniques, noted Rassul Fazelat, president and CEO of recruiting firm Data Talent Advisors. “Soft skills” such as empathy, communication, and securing buy-in from other stakeholders are also essential to budding data analysts.
Because communication, problem-solving, logic and analytical skills are so invaluable, some of the most desirable candidates major in philosophy or history, paired with additional courses to learn data analytics fundamentals and math or statistics.
Brad Lindemann, an early career coach who specializes in helping data analysts land their next job, agrees that aspiring data analysts can pursue (almost) any degree. “I've had clients with very specific analytics degrees and some without,” he noted, “I haven’t seen see any material difference in how often they get called back by prospective employers.”
The most successful data analysts know how to simplify things and help users understand the results of the analysis so that they can take action, he added.
Today, most degrees in economics, statistics, math, finance or business provide those skills as well as exposure to the tools data analysts need in their first jobs. They are also the most versatile degrees because they offer a variety of career paths and flexibility. While focused data analytics degrees obviously sound attractive because they appear to be an exact match for the role, they can limit some of your options later.
Align Your Major and Career
Before you commit to a major, start cultivating your analytical skillset by identifying roles where you’re likely to excel. Consider the industries that are doing the most hiring, the types of problems or questions they are trying to solve using data analytics, and the level of skills you would need to solve those problems.
For instance, you may want to major or minor in computer science if you’d like to engage in trade analytics in financial markets, perform analytics using .NET languages, or collect and analyze the data stored in mainframes to engage in risk analysis in large banking organizations.
On the other hand, unless you want to move into a data engineering, MLOps engineering or data scientist role down the road, a computer science or information science degree might be overkill for most analytics jobs.
Skills You Need to Get Hired
One of the most common mistakes aspiring data analysts make is thinking they need to become proficient at everything when selecting a degree program.
In reality, you only need to master one aspect of the data analysis process to land your first job, especially if you target positions at large companies where data analysts often specialize.
Rather than spreading out your studies, lean heavily into one aspect of data wrangling and visualization, Lindemann advised. That way, you can help out in one area from day one and become proficient with other processes on the job.
Research shows that data cleaning and preparation comprises 80 percent of the work for most data professionals. With that in mind, focusing on data wrangling with SQL and becoming acquainted with the overall process of data analysis by participating in internships and competitions will help you become more attractive to prospective employers.
You can land almost any entry-level data analytics job in any industry as long as you know how to use SQL to query and transform data stored in a database and either Microsoft Power BI or Tableau for data visualization.
To pursue jobs that require higher-level data manipulation, it’s helpful to have experience with Python and possibly R. Having exposure to SAS (which stands for Statistical Analysis System) and insight engines may help boost your marketability (depending on the organization’s aims and objectives).
There’s an arms race for data analytics talent. However, a college degree merely opens the door. Employers prize the attainment of critical soft skills over academic qualifications alone when they look to hire entry-level data analysts. Professionals who seem committed to continually upgrading their skills also have an advantage.
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