How to handle multi time series data for 10K + items

There are 50 shops and each shop have 30000 items. Goal is to forecast the sale of item based on shop.

Forecase the item_cnt_day, for this i dont see this as multi variate time series. Only shop and item ID is needed to forecast the next month data.

The question is do we need to take this as Multi time series problem and build 30000 ARMA, ARIMA, SARIMA etc models for each of the shop and items. So for 50 shops and 30000 items, there will be 50*30000 models.

What do you guys suggest to handle this problem as time series problem

Topic arima time-series python

Category Data Science

1
answered at

The approach you suggested works, but with the sheer amount of time-series you have, plus having data dating back to 2013; I think it would be a good idea to try to create a single model trained on multiple time-series. This is easily done using the Darts Module.

Darts has examples you can follow for multiple time-series here.

About

Geeks Mental is a community that publishes articles and tutorials about Web, Android, Data Science, new techniques and Linux security.