I want to build a timeseries forecasting model which uses LSTM layers, I want to know what analysis we have to do prior to fitting the model? My data is recorded every 20 minutes, I performed Dickey fuller test, it proved that my data is stationary. I have 50k records. My task is to take 24 hours of past data, and predict next 12 hours of data. How can I confirm that the data is not suitable for timeseries analysis? How can I choose correct number of past records so that I can predict the next few records accurately? I'm planning to plot auto-correlation graphs, trend graphs etc. How can I know that the data is suitable for timeseries forecasting? Can you give me the list of tests and plots which I have to perform before building the model?