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But, as you can easily imagine, we cannot always divide it by 12.In fact, at the beginning of the period there are not 12 months to aggregate, but a lower number.This fact is not very evident and it is worth a few words more.Time intelligence functions do not perform math on dates.AJAX is a collection of related web technologies that help to make interactive web applications.The term actually stands for Asynchronous Java Script and XML and is aimed at increasing responsiveness and interactivity of web material. If your server is configured and running, you can test this example with the URL Mathematica/Examples/AJAX/Load In this way, we take 31 of December 2010, move it to 31 December 2009 and take the next day, which is 1st of January 2010: an existing date in the calendar table.

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The Calendar has been marked as a calendar table (it is necessary to work with any time intelligence function) and we built a simple hierarchy year-month-date.(You may have some other URL for accessing your server.) contains two sections, a Java Script section and an HTML section.The Java Script is as follows (in a real usage, this would be better put into a js library file rather than directly into the web page).With this set up, it is very easy to create a first Pivot Table showing sales over time: When doing trend analysis, if sales are subject to seasonality or, more generally, if you want to remove the effect of peaks and drops in sales, a common technique is that of computing the value over a given period, usually 12 months, and average it.The rolling average over 12 months provides a smooth indicator of the trend and it is very useful in charts.

The Calendar has been marked as a calendar table (it is necessary to work with any time intelligence function) and we built a simple hierarchy year-month-date.

(You may have some other URL for accessing your server.) contains two sections, a Java Script section and an HTML section.

The Java Script is as follows (in a real usage, this would be better put into a js library file rather than directly into the web page).

With this set up, it is very easy to create a first Pivot Table showing sales over time: When doing trend analysis, if sales are subject to seasonality or, more generally, if you want to remove the effect of peaks and drops in sales, a common technique is that of computing the value over a given period, usually 12 months, and average it.

The rolling average over 12 months provides a smooth indicator of the trend and it is very useful in charts.

Given a date, we can compute the 12-month rolling average with this formula, which still has some problems that we will solve later: The behavior of the formula is simple: it computes the value of [Sales] after creating a filter on the calendar that shows exactly one full year of data.