What is the role of a BI Developer in a Machine Learning-driven company?

All answers to this question.

Learning SQL is still more important than Python for 90% of BI work. ML models are useless if the data feeding them is garbage.

   Answered 2024-03-23 by Linda Garcia

• I agree with Linda. The "Garbage In, Garbage Out" rule is even more dangerous with ML. The BI dev’s role in ensuring data integrity is the foundation of the whole AI stack.

     Commented 2024-03-24 by James Wilson

Do you find that business stakeholders actually trust "Black Box" AI predictions on their BI dashboards?

   Answered 2024-03-25 by Steven Harris

• Steven, trust is the biggest hurdle. As a BI pro, you need to include "Explainability" metrics. Don't just show a prediction; show the "Top 3 factors" that led to that score. When a manager sees why the AI flagged a customer, they are much more likely to take action on that data.

     Commented 2024-03-27 by Richard Scott

Your role is shifting from "descriptive" (what happened) to "prescriptive" (what will happen). You don't need to be a Data Scientist, but you must become the "translator." In 2024, many BI tools allow you to call Azure ML or SageMaker models directly via an API. I recommend learning basic Python to handle data cleaning and to understand how to interpret model "confidence scores." In my last role, the Data Scientists built the models, but I was the one who designed the "Executive Alert" dashboard that flagged predicted churn before it happened.

   Answered 2024-08-15 by Heather Collins