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#6 The Importance of Rolling Average as a Data Professional
Data Career Week: Tips, Tools and Remote Data Jobs
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06 Dec
📊 The Importance of Rolling Average as a Data Professional
A rolling average is a statistical measure that is continuously recalculated over a specified period, known as a "window," as new data becomes available. This approach is particularly useful in time series analysis, where it's important to understand trends and patterns over time. The window moves forward with each new data point, ensuring that the metric always reflects the most recent set of data within that window.
For example, a data analyst might use a 7-day rolling average to smooth out daily fluctuations in website traffic. By averaging the number of visitors over the past seven days, the analyst can identify underlying trends in traffic without the noise of daily spikes or drops. Another common example is a 30-day rolling sum, which might be used to track monthly sales figures. This method provides a continuously updated total of sales over the last 30 days, offering a real-time view of performance without the irregularities that might occur from day to day.
This is particularly valuable in environments with volatile or seasonal data, where immediate changes can obscure underlying patterns.
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