timeseries is usually specific to use cases when you data represents some signal over time, like temperature reading, stock price, etc.
so you need 2 components: timestamp and signal reading, in this case all specific timeseries analytics apply: sliding/tumbling window, avg per window, smoothing, autocorrelation and all other techniques from Digital Signal Processing/timeseries analytics.
Your regular monthly Sales data of ACME Corp by product category and storeId - this is not timeseries, just general BI
so you need 2 components: timestamp and signal reading, in this case all specific timeseries analytics apply: sliding/tumbling window, avg per window, smoothing, autocorrelation and all other techniques from Digital Signal Processing/timeseries analytics.
Your regular monthly Sales data of ACME Corp by product category and storeId - this is not timeseries, just general BI