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I have a dataset of projects, details, and total costs from which I want to extrapolate the cost of each component of each project. Does anyone have any suggestions on how to approach this? While my actual data set is more complex with more variables, I've created a sample data set that I think is sufficient in working out a methodology.
I've uploaded a pbix file with the sample data here:
https://drive.google.com/file/d/1HWl8WO7ZfexQTuZPhpBat0lp6PB3XwuI/view?usp=sharing
My ultimate goal is to have the user build a new "order" that will produce an estimate and perhaps a range (minimum and maximum). You can see a concept of the final result in the Report View of the pbix file above.
This data will be "live" in a sense - more data will be added over time. The idea is that as more data is added, it would improve the algorithm to estimate costs.
I should note that when I created the attached data set, I used consistent costs for the components when coming up with the total costs. But in the actual data, costs are variable (hence the need for a cost estimating tool).
Hi @Domenick ,
Based on the information you provided, consider using what-if parameters in Power BI. This feature allows you to create dynamic reports that can simulate different scenarios.
You can set a parameter for each component that affects the cost and then use DAX to calculate the estimated total cost based on user input. You can refer to the following link for more details:
Use parameters to visualize variables - Power BI | Microsoft Learn
Best Regards,
Ada Wang
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