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Report limitations

As we venture out into the world of customized reports, there are some limitations to keep in mind for the best results.

able limits 

Lightspeed Analytics can display a maximum of 5,000 rows of results:


An incomplete table with a calculated column will not let you sort by calculated results:


Keep in mind that you can continue to sort by dimensions and measures. The most common types of reports that may exceed their row limit will be Dusty Inventory or Customer Lifetime Value

You can sometimes avoid this by applying more filters to your reports, perhaps by creating Dusty Inventory lists for only one vendor or category. You can also limit customers by status, state, or name begins with, etc.

Too much data can slow or break a report

There is a threshold to how much calculation a table can take before it doesn't launch anymore. 

Too many calculations (including rows and columns) can slow down your browser:


This is why we recommend saving different versions of your report as the calculations become progressively more complex.

Value types don't always mix

In some calculations, Analytics does not like mixing types of values. This comes up often when dates are involved. In some spreadsheet values, dates are considered numbers. In Analytics they are not. o compensate for this, you can extract a number from a date and use it instead.

Filters may filter more than you expect

If you are reporting on a dimension, and no data exists with that dimension on it, the value will not appear in your results.

This often occurs in sales reports. If we are looking at Quantity sold by category in the past week, and we also add Quantity on hand, our Quantity on hand will appear low:


This is not because the numbers are reported incorrectly, rather, it is only looking at the products that sold in the past week, and provides us with a total of their Quantity on hand, by Category.

This is why it's good to measure inventory levels from an inventory report (such as Dusty Inventory, with the Dusty filters removed), instead of a sales report:


Data has limited pairings

While Analytics is very robust in the number of data points that can be matched, some data points are purely not compatible with others. 

For example, being that Retail allows multiple payment methods on a sale with multiple items and taxes, it is actually impossible to match Items to Payment Methods, Items to Taxes, or Taxes to Payment Methods. Analytics can run reports on Items, Payments, and Taxes, but the data within them cannot be joined to each other. 

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