Moving Average

A Moving Average is a statistical calculation used to analyze data points by creating a series of averages of different subsets of the full data set. In the context of business intelligence and data analytics, it is a common tool used to smooth out short-term fluctuations and highlight longer-term trends or cycles. Imagine you’re tracking the daily sales of lemonade over the summer; one day it’s hot and you sell a lot, the next day it rains and sales drop. A moving average helps you understand the overall trend of your sales over time, whether they’re increasing or decreasing, without getting thrown off by those wildly changing daily numbers.

To calculate a moving average, you take a set number of points, add them up, and then divide by the number of points. So if you’re looking at a 7-day moving average, you’d add up the sales from the past 7 days, divide by 7, and plot this average on your graph. The next day, you drop the oldest sales figure, add the new day’s sales, and calculate a new average. As this process continues over time, the line on the graph will start to “move.” It smooths out random variation and makes it easier to spot a trend.

Businesses use moving averages in a variety of ways, such as to forecast sales, analyze stock prices, or measure economic trends. By understanding the direction and patterns in data, companies can make more informed decisions about everything from marketing budgets to inventory levels. It also helps them prepare for the future, rather than just react to the past.