Data Analyst vs. Business Analyst: Education, Skills, and Prospects

Skills That Differentiate Data Scientists and Data Analysts

For data analysts to fulfill their duties, they must have a strong set of skills. Although that does include a blend of technical and soft skills, the former are more apparent, considering their responsibilities.

The primary focus of data analysts is on managing, interpreting, and extracting actionable insights from raw data. Therefore, mastery of Structured Query Language (SQL) is crucial for working with databases, enabling these analysts to retrieve, manipulate, and organize vast datasets efficiently. In addition to that, proficiency in programming languages like Python and R is needed for conducting advanced statistical analyses and developing predictive models.

Microsoft Excel also remains a staple for organizing data and performing preliminary analyses, while data visualization skills allow analysts to create intuitive charts and graphs that communicate complex findings to stakeholders. Expertise in data cleaning, deduplication, and normalization is also needed to ensure that data is clean, consistent, and free of inaccuracies before it is analyzed.

Business analysts, on the other hand, focus on a skill set that emphasizes soft skills and strategic thinking as they work to align business objectives with actionable improvements. While they also possess technical skills related to analytics and business, the soft ones are more directly tied to their day-to-day work.

Critical thinking and problem-solving abilities are core to their role, enabling them to evaluate business processes and propose solutions. Communication skills are equally as important since business analysts stand in the middle of technical teams and organizational leadership—they need to be able to articulate their findings and recommendations to different audiences.

Expertise in process improvement helps them design and implement changes that boost efficiency and effectiveness across business operations. While technical skills such as a working knowledge of analytics tools are necessary, business analysts rely more heavily on their understanding of organizational objectives and collaboration.

Difference Between Data Analysts and Business Analysts

Data analysts and business analysts are complementary but, ultimately, distinct roles. Data analysts are primarily focused on the data itself. As mentioned, they work with complex datasets in order to find patterns, trends, and insights.

Think of it this way: in a retail company, a data analyst might analyze sales data from various stores to determine which products perform best during specific seasons. By identifying that a particular product consistently sells more during December or that urban customers favor specific items, the data analyst provides the “what”–a clear understanding of what the data reveals about customer behavior and trends.

On the other hand, business analysts use those insights to aid strategic business decisions. Using the retail example, these analysts would take the data analyst’s findings and recommend actionable strategies, such as increasing inventory for high-demand products during peak seasons or launching targeted marketing campaigns to urban audiences.

So, the main distinction between the two lies in their focus. Data analysts provide the foundation by extracting and interpreting raw data and answering the “what” questions, such as what patterns exist or what behaviors are evident. Business analysts, in contrast, focus on the “so what,” and they use the insights provided by data analysts to determine what actions should be taken.

Salaries and Job Outlook for Data Analysts and Business Analysts

The difference between business analyst and data analyst roles naturally extends to their earning potential and job outlook as well.

Business analysts generally command higher salaries, with median total pay reaching $98,662 per year and a range between $37,000 and $149,000. Data analysts, while earning slightly less, still enjoy competitive compensation, with median pay at $82,640 and a salary range of $34,000 to $136,000 annually.

In terms of job outlook, data analysts have the advantage, as they are part of the broader data science field, projected to grow an extraordinary 36% from 2023 to 2033. Business analysts, on the other hand, are part of the management analyst category, which is also in demand, with a steady growth rate of 11% during the same period.

Both roles offer opportunities across many industries thanks to the versatility of their skills. For instance, data analysts are essential in fields such as healthcare, technology, finance, and even entertainment.

Mikayla Voorn, a student at the School of Information Studies, is using her data analytics skills to support Syracuse University’s student-run radio station WERW.

“I have a huge passion for the world of entertainment, and I’m excited to learn even more about how analytics can be applied to the music industry through this project,” said Voorn.

Similarly, business analysts can explore career paths in industries ranging from government and consulting to manufacturing and retail. Their ability to evaluate business processes and recommend actionable strategies makes them indispensable in organizations aiming to enhance efficiency and profitability.

How to Choose Between a Career as a Data Analyst or Business Analyst

As both options offer excellent opportunities, identifying which one better aligns with your strengths and long-term goals will provide you with an answer.

So, to narrow down your choice, ask yourself these questions:

• Do I enjoy working with datasets directly, or do I find greater fulfillment in strategizing solutions?

• Do I see myself working more behind the scenes with technical tools or collaborating with teams to implement changes within an organization?

• Am I more interested in building predictive models and analyzing patterns or evaluating business processes and optimizing efficiency?

• Do I prefer working with coding languages like Python or R, or do I enjoy conducting interviews and creating strategic plans?

Even if you choose one now and want to switch later on, it’s entirely possible to transition with the right skill development. For data analysts looking to pivot to business analysis, acquiring knowledge of business operations, project management, and communication strategies can be a strong foundation. On the other hand, business analysts can move into data-focused roles by building technical skills, such as SQL, Python, or data visualization tools.