On sales forecasting by combining multiple factors

[kishcolor]

For example, suppose you have sales data with the following data.

• Date (Quarter, month, day, weekday)
• Weather (atmospheric temperature)

I could use the "Forecast" function of Power BI to generate a sales forecast on a line graph.

However, it seems that only dates, etc. can be achieved, and multiple elements cannot be used.

Is it possible to combine two or more factors (date+weekday+temperature) to calculate a sales forecast?

If you know of any good methods or ways to achieve this, please let me know.

* By the way, about the factors to be used...
Since we have already calculated the correlation coefficient, we assume that only elements with a correlation coefficient of 0.8 or higher will be used.

Red text: Temperature obtained from weather forecast
Yellow cell: Sales value to be predicted

Best regards

[AlexisOlson]

You'd need to write your own forecast formula. Multilinear regression is possible in DAX (I've done it myself) but a lot of work since DAX doesn't have built-in matrix algebra functions. DAX isn't great for complex predictive analytics since you need to essentially build everything from scratch, even determinants and matrix inversion.

As a side note, I'd be surprised if those independent variables have a >0.8 correlation coefficient all combined, much less individually.