InfluxDB allows for storing raw events as irregular time series, which presents unique challenges when performing common operations like calculating the mean of values. To address this, InfluxDB enables converting an irregular time series to a regular one on the fly by aggregating individual values within arbitrary windows of time. This approach requires imposing some kind of regularity on the data, such as breaking up the time range into discreet units using InfluxQL's GROUP BY clause and then aggregating the values within those windows. The choice of window size and interpolation method can significantly impact the final results, highlighting the need for understanding the data well enough to make educated decisions about how to work with it. By utilizing tools like fill() options in GROUP BY clauses, users can effectively handle irregular time series and derive meaningful insights from their data.