Business Analyst vs Data Analyst

"Behind each data point is a living, breathing human" - Shafqat Islam

Big data is transforming and powering decision-making everywhere. In order to make sense of all this data and use it to be more competitive, companies must apply both business analytics and data analytics. There’s often confusion about these two areas, which can seem interchangeable.

Both business analytics and data analytics involve manipulating large amounts of data to extract insights from the data with the goal of enabling effective decision making. The difference is how this manipulation is done.

Business Analyst:

Business Analyst use organized data to ask three different questions. What has happened (descriptive analytics)? What will happen in the future (predictive analytics)? What should we do (prescriptive analytics)? Through the use of manipulation software such as Excel, Power BI, or SQL, analyst retrieve and aggregate data from multiple sources; thus compiling it into a digestible and actionable format. Data dashboards are a key to use to visualize the data and represent it to stakeholders.

Data Analyst:

Data analysts look at unorganized data to find patterns and trends within it. They are looking to find possible problems in businesses or processes that business analyst then try to solve. One common way they do this by using the computer programing languages R or Python. Another growing trend is to use Machine Learning to apply statistical statistical probabilities and forecasts.