As a data lover, you’re at a professional crossroads. Do you stay in your current—and familiar—role, or do you shift and move in an entirely new direction? More specifically, how do you choose between becoming a business analyst vs. data analyst?

Both roles would allow you to capitalize on your love of “all things data,” and both would appeal to your affinity for problem solving. Both positions would also pair well with an in-depth knowledge of data science. However, the roles of business analyst vs. data analyst require different skillsets and focuses, making it necessary to choose your path carefully.

What Is a Business Analyst?

A business analyst identifies technology solutions to solve oftentimes amorphous business problems. They work in a variety of industries including healthcare, transportation, manufacturing, finance, banking, software services, and telecommunications. The International Institute of Business Analysis defines a business analyst as an “agent of change,” who identifies and executes new opportunities for businesses to capitalize on technology. Business analysts often specialize in one of the following roles: business systems analyst, systems analyst, functional analyst, service request analyst, or agile analyst, depending on one’s area of interest. For example, a functional analyst helps organizations use and integrate their technology with other systems. A service request analyst handles user inquiries and system enhancements.

Successful business analysts possess strong foundational data science skills as well as an ability to develop strategic business and project plans, identify key performance indicators, create use-case scenarios, and engage and communicate with stakeholders at all levels of the organization. They must be able to take a holistic view of a business problem or challenge and work with various individuals to get the information necessary to drive IT changes. Those transitioning into a business analyst role may have previously worked as software developers or project managers.

A business analyst’s daily responsibilities may include reviewing data about current work habits, interviewing users to identify technology challenges, preparing documents that outline detailed functional requirements needed to address those challenges, creating flowcharts for programmers to follow, designing and executing test scripts or scenarios, and managing change requests related to the project.   

What Is a Data Analyst?

Data analysts, on the other hand, use specialized analysis techniques and tools to determine how businesses can use data to make more informed decisions. This may sound very similar to the role of business analyst; however, data analysts work more directly with the data itself. They’re responsible for identifying important business questions, applying the appropriate statistical techniques to harness structured and unstructured data, and performing complex data analysis to extract useful information and develop conclusions. Data analysts are also responsible for protecting an organization’s data and ensuring that all data repositories produce consistent and reusable data. Data analysts and business analysts work in many of the same industries and particularly those that rely on technology. Data analysts and data scientists are also increasingly employed in other industries such as agriculture, travel, food, oil, and auto insurance—each of which has only begun to tap into the power of big data.

Successful data analysts are those who can extract and analyze big data as well as present results to executive management or departmental managers. This requires a unique balance of technical data knowledge and business acumen—a skillset professionals can gain or hone in a data science degree program. Those transitioning to a data analyst role may have previously worked in fields such as accounting, healthcare information management, database administration, computer science, or business.

A data analyst’s daily responsibilities may include culling data using advanced computerized models, removing erroneous data, performing analyses to assess data quality, extrapolating data patterns, and preparing reports (including graphs, charts, and dashboards) to present to management.

Business Analyst vs. Data Analyst: 4 Main Differences

Although business analysts and data analysts have much in common, they differ in four main ways:

1. Overall responsibilities. Business analysts provide the functional specifications that inform IT system design. Data analysts extract meaning from the data those systems produce and collect. Data scientists can often automate the business analyst’s tasks and may be able to provide some of the business insights as well.
2. Salary. Data analysts earn an average salary of $72,691, according to Indeed. Business analysts earn a higher average annual salary of $86,206. Although business analysts tend to make more, professionals in both positions are poised to transition to the role of “data scientist” and earn a data science salary—$100,910 on average. 
3. Skillsets. Business analysts require data science knowledge as well as skills related to communication, analytical thinking, negotiation, and management. Data analysts require similar skills with a more in-depth focus on technical data manipulation.
4. User interaction. As project facilitators and managers, business analysts often have more direct interaction with systems users, customers, system developers, and others than data analysts do. That’s because business analysts may frequently interview people to learn more about how technology can be improved to help business processes. They work collaboratively with others throughout the duration of a single project. Although data analysts may consult initially with internal subject matter experts to identify important data sets, the bulk of their work is done independently.   

How to Prepare for a Business Analyst or Data Analyst Role

If you’re thinking about transitioning to a business analyst or data analyst position, consider earning a Master of Science in Data Science online from the University of Wisconsin. The 12-course curriculum focuses on building both technical data science skills and “power” skills such as leadership, communication, and project management—skills that are beneficial in either position. Plus, a data science master’s will help you advance to a high-paying, in-demand data science role. To learn more, see our page “What Do Data Scientists Do?”

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