As data becomes crucial to all organizations’ functions, the need for accurate analysis is also rising in lockstep. That’s why data analysts are more valuable than ever—but how does that translate into the actual data analyst salary? And if you’re applying for this role, what can you focus on to maximize your earning potential?

Before we move forward, let’s take a moment to distinguish between data analysts and data scientists. Data analysts generally focus on smaller, more tactical data problems. Data scientists, on the other hand, take a more holistic approach to the company’s data, and often provide a more strategic analysis. The terms aren’t interchangeable. 

What’s clear, though, is that both data analyst and data scientists are in intense demand. A Harvey Nash Report, the result of a collaboration with the Massachusetts Institute of Technology CISR and CIONET and published in late 2021, stated that the acute data-analytics skills shortage can drastically increase your hiring potential.

The World Economic Forum’s Jobs of Tomorrow report, published in 2020, listed data specialists as one of seven high-growth emerging professions, with data analysts coming in fifth place. This is clearly a profession with a lot of upsides.

What is the average data analyst salary?

According to Burning Glass, which collects and analyzes millions of job postings from across the country, the median salary for a data analyst is $73,067, but that can rise significantly with the right combination of experience and skills.

Burning Glass also estimates that data analyst jobs will grow 12.3 percent over the next 10 years. At the moment, there have been 100,393 data analyst job postings over the past 12 months, and the average open job takes 39 days to fill—indicating a healthy level of demand. 

According to Glassdoor, the estimated total pay for a data analyst is $86,563 per year in the United States, with an estimated base pay of $76,262 per year. A senior data analyst can expect to earn $93,000 per year. 

What are the most valuable skills for a data analyst?

Analyzing those job postings, it’s clear that the specialized data-analyst skills most in-demand among employers include:

• Data analysis
• SQL
• Python
• Tableau
• Microsoft Power BI
• Data science 
• Data quality

In addition, employers frequently want data analysts to possess “soft skills” such as communication, problem-solving, research, writing, and teamwork/collaboration. Depending on the specialization they pursue, data analysts may need to master analytics and software tools specific to healthcare, manufacturing, and other industries. 

Shounak Simlai, vice president of data strategy and business intelligence at ActiveCampaign, thinks that, among the top skill sets for data analysts, data modeling skills in Excel and SQL are the bare minimum. “Over and above that, I would recommend data analysts be proficient in statistical modeling programs like R,” he said. “It is also important to have experience in coding and an understanding data infrastructure, in order to interface with data engineering.”

He said a successful data analyst must be capable of collecting data, then finding patterns in that data and generating reports to make sense of it all, telling simple, digestible data stories that provide key stakeholders with clear and actionable insights.

What skills do you NEED as a data analyst?

On the most fundamental level, data analysts need to be proficient in data visualization skills (such as Tableau) and analytics/B.I. (via tools such as Looker). In other words, you absolutely need the ability to process data into a form that all stakeholders can understand. 

“Even though everybody has probably heard by now that data is the ‘new oil,’ not all of us grasp the true meaning of this catchphrase,” Jakub Kubrynski, CEO and co-founder of DevSkiller, said. “Sure, it’s obvious that oil is a valuable resource and you’ve got to extract it and process it somehow. But to get the best out of it, you need to be also able to refine it and deliver the final product to the gas stations. The same applies to data.”

Kubrynski said it’s not enough to extract numbers and information from the organization’s systems and organize them into slick reports and dashboards: “You’ve got to be able to translate your insights into actionable recommendations and communicate them to the stakeholders… Hence, the single most important soft skill you should focus on as a data professional is the ability to communicate in a clear and concise manner. Great data analysts have to also be great storytellers.”

Added the ability to deal with ambiguity, and communicate nuances to those stakeholders, is also key. Data analysts regularly communicate results via spoken presentations, PowerPoint decks, and more. 

What programming languages do data analysts learn?

Kubrynski said data analysts, like other data professionals, should possess knowledge of various programming languages and frameworks—especially Python, Perl, R, Scala, and of course SQL. “But acquiring or developing coding skills in one or more of those languages is only the beginning,” he said. “What really matters when it comes to staying competitive on the job market is the ability to apply those skills to solving practical business problems.”

Do I need certifications to become a data analyst?

As in the case of many IT skills, there are plenty of certifications on the market you can consider to boost your value as a data professional.

On top of the well-known Stanford’s Machine Learning Certification offered by Coursera, the top three Kubrynski would recommend are: 

• Microsoft Azure Data Scientist Associate
• IBM Data Science Professional Certificate
• HarvardX’s Data Science Professional Certificate

“Nevertheless, every certification, even the most prestigious one, can only serve as an indication of theoretical knowledge,” he added. “In most, if not all, recruitment processes for tech-related positions, adding a certification to your resume can only get you through the CV sifting process.” (No matter what your certifications, you’ll need to prove your practical skills during the job-interview process.)

Simlai pointed to a broad array of certifications data analysts should be looking at to enhance their value proposition, including:

• Cloudera Data Analyst Certification
• General Assembly Data Analytics Course
• MIT Sloan School of Management Applied Business Analytics Certificate

He also believes it’s worth investigating the CareerFoundry Data Analytics Program and the Springboard Data Analytics Career Track.

How can I negotiate a better data analyst salary? 

Kubrynski believes salary negotiating tips and tricks for analysts and other data professionals are generally the same as for other job positions. “Become familiar with the salary benchmarks in your industry and geographical location, focus on the practical dimension of your knowledge, and show actual value you can deliver to the organization from solving problems to saving money and increasing revenue,” he said.

Most importantly, don’t be afraid to turn down an offer that doesn’t satisfy you. “The market demand for data science-related skills is rapidly increasing,” Kubrynski said. “You can definitely afford to be selective.” 

For Simlai, the top salary negotiating tactic he can think of consists of three words: Research, research, research! “Understand what the market is currently paying for comparable roles,” he said. “Negotiating should be a win-win for both parties. Focus on framing your argument on what you will be able to help them achieve within six months of starting."