Hello, Is it possible to analyze data with low granularity (i.e. min by min) or they should be summarized before using them for time series forecasting using the notebooks provided in Dataiku.
This is possible using some code along with the visual ML component of Dataiku.
You can use this example: http://gallery.dataiku.com/projects/TIMESERIES/flow/ as a starting point. The code element would mostly deal with slicing windows of the data, since ML models would only forecast one step ahead.
This is a great guide for Univariate Time Series time. However, I need to perform Multivariate Time Seriese Forecasting. Any suggestions on univariate ts forecasting using i.e. Vector Auto Regression (VAR)?