Business Analyst vs Data Analyst Explained

Over the years, companies have used data analysts and business analysts inversely. Still, if you take a closer look at their job descriptions and personal experiences, we can highlight their differences. However, people working with data are often clustered in small companies. But, in large organizations, data analysts and business analysts are hired for various critical tasks.

Moving on, let’s take a closer look at these two roles to understand their nuances and what they bring to the table.

business analyst

Ideally, the role of a business analyst is to calculate each part of the business to ensure that it is on the right track. They play a crucial role in maintaining the growth of the business. Business analysts create, develop, and maintain important metrics commonly known as KPIs (key performance indicators). It helps in quantifying the activity and allows the company to quickly complete a sales process or product improvement.

In addition to working with metrics, business analysts investigate internal and external business sections to uncover anomalies. During this process, businesses can plan with the help of business analyst findings to make the business more efficient and successful. However, a successful business analyst needs the right tools to dig deep into the key issues facing a business. They use various tools such as SQL, Tableau (visualization tools), Excel, Salesforce and other CRM tools, KPI analysis, and then present the results to stakeholders. As a Business Analyst you will have a lot of “screen time” as it is largely customer oriented, even if the “customer” is internal.

Data Analyst

While this might be borderline confusing with the business analyst role, again there are key differences in skills, objectives and description. A data analyst should focus on business data and should not be held accountable for the impact of data on the business. Ultimately, they will be asked to perform both functions. Yet, more emphasis is placed on data warehousing, data tables, and SQL code developed to create business metrics and not to present them to stakeholders.

In an organization, data analysts will be required to design and maintain data systems and databases, as well as troubleshoot potential issues that arise from time to time. Another critical role they perform is extracting and cleaning data and preparing it for analysis. To get to grips with data usage, there are a few things data analysts need to know, such as SQL, R, and Python programming, data architecture, and routine reporting. Additionally, data analysts ensure that the data includes no noise, and SQL queries are optimized to deploy the data effectively and efficiently. A data analyst focuses on the technical aspects of data rather than business analysis.

Main differences

Now that we have understood the roles of business analysts and data analysts, let’s see how different they are. For starters, business analysts use data to uncover problems and solutions, but don’t go into their technical details. However, they work at a more conceptual level to set strategy and communicate with stakeholders and are primarily concerned with the business side of data.

On the other hand, data analysts spend most of their time collecting raw data and information from different sources, cleaning and shaping it, and using a range of specialized techniques to extract useful and draw conclusions. Similarly, business analysts have deeper industry knowledge and experience in e-commerce, manufacturing, or healthcare. This is why trade analysts often do not worry about the technical aspect of data and its supply. However, they should have a working knowledge of statistical tools, common programming languages, networks and databases.

The roles of data analysts can be very linear due to their rigorous practices and constant search for data. However, a business analyst should be trained in requirements modeling and gathering; meanwhile, data analysts should have excellent data mining skills and be familiar with machine learning and AI (a must-have for today’s industries). Finally, business analysts with a solid foundation in business administration are an important asset. On the other hand, data analysts should ideally have an information technology background that will help them manage complex algorithms, databases, and statistics.

Whichever path you choose to follow, the rise of Big Data has created many opportunities for business and data analysts. Important trends such as explainable AI, augmented AI, blockchain and data factory have taken over the world, and the importance of key data and what to do with it has finally been realized. This can motivate more people to take up this challenge and launch their business or data analyst career.

Sean N. Ayres