There might be days where we get a surge of spam traffic or a huge wholesale order or several test purchases from our beloved dev team.
That skew our metrics: causing data quality issues like bloated totals, skewed averages, and unusual spikes in trend lines.
If you're lucky, you can find a way to isolate and filter out these records within the original dataset and clean your data.
But what if you can't?
One solution, if the outliers happen to be on specific dates, is to exclude those days from your charts.
You will also learn how to deal with missing data points on a time series chart!