I want to dive deeper and show you the ways of implementing some sensitivity analysis examples in your Power BI model. Sensitivity analysis is a very important financial model. It helps businesses in predicting the outcome of a certain scenario, like customer and cost changes, to the overall gains of company. In a previous tutorial
What I want to cover with this tutorial are some great examples of profit prediction in the future using Power BI. To achieve this in Power BI you need a number of different modelling and formula techniques, but you must be able to use them correctly and simultaneously. When it comes to the output that
Power BI is an incredible tool to run scenario analysis and what-if analysis examples. I’ve actually never seen or come across an analytical tool that is as effective and intuitive to implement this type of complex analytics. The key is that you’ve got to think more analytically about the underlying elements in your datasets than
We’re getting specific today and really showcasing the analytical power of Power BI. Sensitivity analysis, or even running some ‘what ifs’ around this, allows you to almost predict what may happen in the future with your results. In this example, I want to see what will happen to my profitability if I am able to
