Data Analyst vs Business Analyst | Which role is right for you?

Not sure what the difference is between data analysts and business analysts? Having trouble deciding which career path to pursue? Trying to move from a business analyst to a data analyst role? Or the other way around? If the answer is yes to any of these questions, then this is the right video for you as I'll walk you through the main differences and similarities between data analysts and business analysts. I'll cover the responsibilities, the skills required, the career paths, and the potential salary you could make. Hey, my name is Mo Chan, and I work as a data and analytics analyst within the financial services industry. In both my direct and my wider team, there are lots of data analysts and business analysts, so I'm going to use my own data analyst knowledge and experience combined with my exposure working with other DAs and BAs to highlight the main differences and similarities between the two roles. So let's start with the responsibilities, and more specifically, the data analyst responsibilities. DAs connect data and business teams and work with programming teams to collect and analyze data. Say the client onboarding team wants to build a dashboard with onboarding KPIs. As a data analyst, you would gather the requirements for the dashboard. You'd speak to the business team, the client onboarding team in this case, and find out where they consume the data from, what columns they use, and what filters, if any, need to be applied. You would also discuss the dashboard design and layout as you want to make sure that you build something that satisfies the business ask and solves the business problem. You would work with the data engineering team to connect to the data source, analyze the data, do some data validation, and prepare some mock-up dashboards that you can present back to your stakeholders. Once the business team is happy, you can go ahead and build, test, and productionalize your dashboard. Building actionable insights using past data is great, but what if there was an easy way for you to create smart predictions? With Pcan's predictive analytics platform, you can quickly turn yourself into an AI analyst by turning your data into smart predictions. You can connect to your data by importing your CSV files or by using one of the many connectors available. The easiest way to get started is to select a template from the use case library. Each template has a guiding question, an output preview, the required tables, and a set of predefined queries that you can tailor to your own needs to build your predictive flow. Once you hit train model, Pcan will use the queries to automatically create an AI-ready dataset and train a machine learning model. No data prep required at all. Pretty cool, right? You can use Pcan's interactive dashboards to get insights into your model's performance. The dashboard has various metrics such as precision and recall, threshold configuration, a confusion matrix, and feature importance. So if you're interested, sign up to Pcan for free using the link in the description below. A business analyst also sits between business stakeholders and the internal team and also gathers requirements to solve specific business problems. The biggest difference is that BAs usually prepare the use cases and specs and the requirement documents and leave the actual build with developers. As a business analyst, you would work with clients to understand problem, set up meetings to gather the correct requirements. You would focus on scope, you would outline and communicate the client's needs to your team, prepare and present the requirements and the findings to come up with a detailed plan on how to solve the business problem. You'd do test planning and test cases and prepare business proposals. Now, all of this means that as a business analyst, you need excellent communication and stakeholder management skills. You'd be sending a lot of emails, setting up various meetings and workshops to understand and explain the client's requirements or your own findings. You'd also need to have strong business knowledge to be able to see things from the business side and some kind of technical grasp, as you would also have to be able to see things from the tech side. All of this will make you effective in connecting business and IT teams. You'd need to have some technical skills too, of course. I'm thinking Excel and maybe SQL, nothing crazy, as you'll have to do analysis on your own. Now, as a data analyst, you'll need to have more technical skills, for sure, and probably a bit less communication and people skills, though it always helps if you can explain things clearly and have great stakeholder management skills. You'd need to master Excel and SQL, some kind of visualization tool like Tableau or Power BI, and preferably a programming language as well, say Python, for example. You'd have to be able to poll, wrangle, and analyze data, maybe build some data pipelines, do some data modeling, and tell compelling stories using data. Of course, as a DA, you'd also need business knowledge as well, as you need to come up with insights and build reports and dashboards that tailor to a specific business ask. I'm sure you can see that there's quite a bit of overlap between the responsibilities and skills of DAs and BAs, and at a lot of organizations, the roles can often overlap too. When it comes to data analyst career paths, you tend to start out as an assistant or junior data analyst before you become a full-blown data analyst. Then you move on to senior DA and lead data analyst, after which you can either become a specialist, say a research analyst, or you can also go down the management track and become a data portfolio lead or a data portfolio manager. When it comes to business analyst career paths, you tend to start out as an assistant BA, then you become a BA, then a senior BA, and then a lead BA, after which you can go down the business track by becoming an account owner or taking up an executive level position on the business side. Or you can go down the domain track and become a domain consultant or the head of your domain. As far as the salaries go, just by quickly checking the average US salaries on Indeed, you can see that you can make quite a good living with either of these roles. So to summarize, data analysts and business analysts both connect business and IT teams and gather requirements to solve specific business problems. Both roles require domain knowledge. Data analysts will need to have more technical skills as they need to pull, wrangle, and analyze data to create actionable insights in the form of reports, dashboards, or ad hoc analysis. Business analysts will need to have stronger communication, presentation, and stakeholder management skills as they need to prepare and present requirements, findings, test cases, and business proposals. Both roles offer good career progression and salaries, so whichever you choose, you can't really go wrong. Just make sure you go with the one you'd actually enjoy doing on a daily basis. I hope you liked this video, and if you did, you should check out some of my other videos right here. Thank you so so much for watching, and I will see you in the next one.