Forum Discussion

Ambi's avatar
Ambi
New Member
6 years ago
Solved

Power BI Forecast

Hi Community,
Please guide me to forecast monthly Sales(Not as each day, it is as month) for next three months keeping the previous previous four years monthly Sales History. I want the forecast to be displayed in Table visual and find the difference between actual sales and forecast Sales, its accuracy.

I tried Forecasting using Linear Regression in DAX. Dax Forecasted value was same as in  Excel Prediction function. Also, tried prediction using custom visual "Forecasting with ARIMA". The level of accuracy varied at a greater level between Custom Visual and Linear Regression prediction. I found "Forecasting with ARIMA" is great at prediction and closely match the actual sales.

But my problem here is, i am not able to display it in  table visual. I want the algorithm used in "Forecasting with ARIMA" Custom Visual to be displayed in Table Visual. Only on showing in Table visual, it is able to easily and clearly show the Forecast and Actual Sale Difference. The Forecast must change dynamically with Filter Selection.

For reference, i am attaching you the pbix. In this i have tried using Line Chart, Forecast using ARIMA and R-Script. 
https://drive.google.com/file/d/1K5cHVSXGQDsFhl7F9GPEcDWZorUJQ2Wd/view?usp=sharing

Appreciate any answer and guidance.
Thanks in advance,
Ambhika

  • Hi Ambi ,

    Is this what you want?

    library(gridExtra)
    library(quantmod)
    library(forecast)
    library(tseries)
    ARIMA_Sales<-ts(dataset$Sales,start=c(1))
    Sales_Forecast<-auto.arima(ARIMA_Sales,seasonal=TRUE)
    Predicted_Sales<- forecast(Sales_Forecast, h=10)
    Predicted_Sales<-data.frame(coredata(Predicted_Sales))
    grid.table(Predicted_Sales)

     

    Best Regards,

    Icey

     

    If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

1 Reply

  • Icey's avatar
    Icey
    Community Support

    Hi Ambi ,

    Is this what you want?

    library(gridExtra)
    library(quantmod)
    library(forecast)
    library(tseries)
    ARIMA_Sales<-ts(dataset$Sales,start=c(1))
    Sales_Forecast<-auto.arima(ARIMA_Sales,seasonal=TRUE)
    Predicted_Sales<- forecast(Sales_Forecast, h=10)
    Predicted_Sales<-data.frame(coredata(Predicted_Sales))
    grid.table(Predicted_Sales)

     

    Best Regards,

    Icey

     

    If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.