Key traits of successful data analysts

Students return to campus in January 2022 after a few weeks of online learning owing to a COVID-19 surge at University of California, Irvine.

Jeff Gritchen—MediaNews Group/Orange County Register/Getty Images

Big data has been a buzzword for several years, but the need to understand what it means is both a reality and a top priority for many industries. This need has been only further emphasized during the COVID-19 pandemic, as many organizations have reduced their investments across many areas of IT but chose to increase spending on data and analytics.

Enhancing data analytics was among the most important data strategy initiatives for 43% of companies by 2023, according to a 2021 survey of 351 senior technology executives conducted by MIT Technology Review and Databricks. Meanwhile, investing in people with analytics expertise can pay off because it has been shown to drive growth. A 2016 study by McKinsey found that 15% of operating-profit increases from big-data analytics were linked to the hiring of data and analytics experts alone, rather than IT investments or a combination of the two factors.

If enhancing data analytics is a priority, and talented analysts can drive profit, what traits or skill sets should a data analyst possess to be successful? Here’s what you need to know.

Data analyst skill sets represent a blend of talents

Throughout his career, Dave Belgard has used his data and business intelligence background in many ways, including building a data analytics center of excellence at one organization and developing a product strategy as part of a merger. “In each of the roles, I’ve been successful because I have the ability to manage and use data that pretty much no one else has,” says Belgard, now a manager of software engineering for support, triage, and training at Comcast.

What skills are required for success? Belgard immediately points to a few traits, including an inquisitive mind and technical flexibility. “You need to be the type of person that is always asking why,” he says. “Many people simply accept how things are done; an inquisitive person wants to know why they are done that way.”

For Joe Ste.Marie, the key traits of a successful data analyst draw on a mixture of skills. Ste.Marie is a director at Bully Pulpit Interactive, a Washington, D.C.-based communications agency, and he leads the product and tech work. In this role, Ste.Marie’s team takes data and analytics and makes it actionable for others in the organization.

“Beyond the actual data you’re using, all analysis is just the combination of a great question, the right breakdowns of that data, and domain knowledge,” Ste.Marie says. “So for an analyst, you need to have the technical skills to interact and analyze that data, enough knowledge of the problem to know what that data means, and, most importantly, curiosity to ask the right questions.” 

Top technical skills for data analysts

The technical skills Belgard and Ste.Marie refer to may vary from role to role, but they tend to fall into certain key domains. According to the International Institute of Business Analysis (IIBA), a nonprofit professional organization for business analysts, the top areas of expertise that can serve analysts include:

  • Business intelligence and reporting software 
  • Data mining 
  • Data visualization 
  • Database design
  • Programming skills, such as Python and R 
  • Statistical analysis software (such as R, SAS, SPSS, or STATA) 
  • SQL databases and database querying languages 
  • Survey/query software

“The technical skills can truly be as simple as knowing how to build a pivot table in Excel or do basic aggregation in SQL, or as complicated as knowing how to run multilevel regressions,” Ste.Marie notes. “If there’s one hard skill that’s just critical, it’s SQL. After all these years, it’s still one of the easiest ways to answer 80% of questions.”

The importance of soft skills in data analysis

Technical expertise alone doesn’t tell the whole story, however. Beyond just having a head for numbers and the ability to problem solve, there are soft skills to consider. A data analyst should be curious, strategy-minded, able to operate in a systematic and scalable manner, and have excellent communication skills.

Curiosity is one of the skills Ste.Marie believes is most critical for data analysts to possess. “The only trait that you can’t teach analysts is curiosity,” he says. “Most of the analysis and technical things you can learn by doing, but they’re all just tools to answer questions. So that natural curiosity is actually the thing that separates out ‘good’ analysts from really great ones.” 

Other soft skills help analysts progress, Ste.Marie believes. “You can run the smartest, most sophisticated modeling that people have ever seen, but if you can’t translate that back to your stakeholders, your analysis isn’t very useful,” he says. “I’ve spent a lot of time learning the hard way that being useful is way more important than being right.”

In its roundup of top business analysis skills, the IIBA cited facilitation skills—the ability to help a group of people make progress—as the top soft skill analysts will need during and post-pandemic. 

A strong outlook for the data analytics field

Now is a time when the best data analysts can shine. From employing complicated technical skill sets to offering persuasive communication styles, the skills they bring to the table are not only valuable to their work, but to their employers. And if analysts don’t learn these skills on the job, they may seek out more education, such as through a master’s degree program in data science or a master’s degree program in business analytics.

The organizational demands may be many and the accompanying skill sets wide-ranging, but the future is bright for those data analysts willing to expand their skill sets to embrace it.

“We’re sitting in a really huge moment of transformation for the data space,” Ste.Marie says. Belgard agrees: “Data drives everything.”

See how the schools you’re considering fared in Fortune’s rankings of the best business analytics programs, data science programs, and part-time, executive, full-time, and online MBA programs.

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