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These most definitely are different things although some skills are transferable. It’s really a difference in the “so what” of your analysis. Depending on your industry, the shift in need could be dramatic. However, in order for the BA type roles to be phased out, you need to to have high quality data, static questions that aren’t subject to nuances and whims of the PO, excellent measurement and dashboarding systems, etc. In theory, data is business currency. It’s what drives the innovation flywheel. Any non-digitally native business likely will struggle until they get their inputs and outputs under control AND until business-minded people know what to do with the data that they receive. So - don’t be the person who just passed a PO some 6-digit # without any context or direction. Help them know what that number means and how to use it. Don’t be a straight order-taker, but ask the goal and offer suggestions about how to get a better, cleaner answer and get yourself a seat at the table. It won’t matter as much that you are / were the “data person,” you become a strategic thinker with a way to get at the answer.
Descriptive analytics are foundational to moving beyond that. The challenge with AI or ML is that the data HAS to be clean, there have to be clear processes and definitions . Most companies aren't there and it's going to take a human, or multiple humans, to get things aligned.