Business analysts focus on data base design (database modeling, at a high level, including defining metrics, dashboard design, retrieving and producing executive reports and designing alarm systems), ROI assessment on various business projects and expenditures, and budget issues. Some work on marketing or finance planning and optimization, and risk management. Many work on high-level project management, reporting directly to executives.
Some of these tasks are sometimes performed by data scientists as well, particularly in smaller companies: metric creation and definition, high-level data base design (which data should be collected, and how), or computational marketing, even growth hacking (a word recently coined to describe the art of growing Internet traffic exponentially fast, which can involve engineering and analytic skills).
There is also room for data scientists to help the business analyst’s job, for instance by helping automate the production of reports, and make data extraction much faster. You can teach a business analyst FTP and fundamental UNIX commands: ls -l, rm -i, head, tail, cat, cp, mv, sort, grep, uniq -c, and the pipe and redirect operators (|, >). Then you write and install a piece of code on the database server (the server accessed by the business analyst traditionally via a browser or via tools such as Toad or Brio), to retrieve data. Then, all the business analyst will have to do is
Such collaboration is win-win for the business analyst and the data scientist. In practice it has helped business analysts extract data 100 times bigger than what they are used to, and 10 times faster than they are.
Conclusion: Data scientists are not business analysts, but they can greatly help them, including automating the business analyst’s tasks. Also, data scientists might find easier get a job, especially in a company where there is a budget for one position only, and the employer is unsure whether hiring a business analyst (carrying over all analytic and data tasks) or a data scientist (who is business savvy and can perform some of the tasks traditionally assigned to business analysts) if he/she can bring the extra value and experience described here. In general, business analysts are hired first, and if data and algorithms become too complex, a data scientist is brought in. If you create your own startup, you need to wear both hats: data scientist and business analyst.