Many datasets are affected by seasonality, making it challenging to extract accurate insights. Fortunately, these seasonal fluctuations can be easily removed using the right data processing techniques. Let’s start with the basics of seasonally adjusting data to enhance your business intelligence strategy.
Understanding Seasonality in Data
Seasonality refers to recurring patterns in data based on known periodicities. These periodicities often align with pay cycles, production schedules, or consumer behavior. For example, government payroll tax receipts follow specific pay periods—weekly, bi-weekly, semi-monthly, and monthly. Identifying these cycles is the first step toward accurate data analysis.
Using Moving Averages for Seasonal Adjustment
If you know the periodicity of your dataset, you can remove its effect using a moving average. This common data processing technique involves calculating the average of a specific number of data points within a rolling window. Here’s how it works:
- Monthly Pay Period: Use a 21-period moving average for daily data.
- Bi-Weekly or Semi-Monthly: Apply a 10-period moving average.
By smoothing out fluctuations, moving averages reveal underlying trends, improving business intelligence reporting. However, they come with a drawback: lag.
The Drawback of Moving Averages
A moving average provides the most accurate representation at the midpoint of the window. For instance, a 21-period moving average best fits the data lagged by 10 days. Each periodicity you adjust increases the lag, resulting in smoother data that no longer reflects current conditions.
Moving Trends: A Smarter Alternative
To achieve the smoothness of a moving average without the lag, consider moving trends, also known as moving linear regression. This method provides real-time insights by fitting a linear trend to a rolling window of data points, making it an essential tool for predictive analytics and business intelligence platforms like Excelerate®.
Excelerate® Simplifies Seasonal Adjustment
With Excelerate’s advanced data processing tools, you can automate seasonal adjustments, generate real-time reports, and eliminate periodic noise without complex formulas. Whether you’re tracking KPIs, managing cloud analytics, or refining your ETL process, Excelerate® streamlines the task.