Time series data has historically been associated with applications in finance. However, as developers and businesses move to instrument more of their servers, applications, network infrastructure and the physical world, time series is becoming the de facto standard for how to think about storing, retrieving and mining this data for real-time and historical insight.
Time series are simply measurements or events that are tracked, monitored, downsampled and aggregated over time. This could be server metrics, application performance monitoring, network data, sensor data, events, clicks, trades in a market and many other types of analytical data. The key difference that separates time series data from regular data is that you’re always asking questions about it over time. A simple way to determine if the dataset you are working with is time series or not, is to look and see if one of your axes is time.
