multiple seasonality-using Tbat() function ,-forecasting

Question

I started using tableau with its integration with R, and I'm using the predicted graphs.

I have 6 years of data (hourly) with multiple seasonalities, as hourly, weekly and yearly.

library(forecast); data <- msts(.arg1, seasonal.periods=c(24, 7 * 24, 365 * 24)

I've applied the above in tableau. It is taking 8 hours to complete but not getting good results. Previously I used the ts() function that was showing good results when I applied f=365,{days wise data}, but on hourly data this is not showing good results.

There may be some seasons that are getting missed. I know tbat() can do the job but I need to improve it over tableau.

Answer 1

Dates are notoriously difficult. The biggest issue is that you're not accounting for leap years, which will happen in any six year window. Holidays make life even more complicated, since some holidays fall in different days of the week depending on the year, which can change observations.

Take a step back. What kind of data do you have? What do you want to learn about it? That will inform the best approach.