Errata

Analytics Engineering with Microsoft Fabric and Power BI

Errata for Analytics Engineering with Microsoft Fabric and Power BI

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The errata list is a list of errors and their corrections that were found after the product was released. If the error was corrected in a later version or reprint the date of the correction will be displayed in the column titled "Date Corrected".

The following errata were submitted by our customers and approved as valid errors by the author or editor.

Color key: Serious technical mistake Minor technical mistake Language or formatting error Typo Question Note Update

Version Location Description Submitted By Date submitted Date corrected
Printed, PDF, O'Reilly learning platform
Page Page 288 in the section called "SUM versus SUMX when the expression is a single column"
Last section

In this section we said that the simple aggregation functions use an optimized internal path that is faster than the iterators, and that the engine replaces a single-column SUMX with its non-X version. We actually had this backwards.

SUM is shorthand for SUMX, so SUM ( factorders[_Quantity] ) is internally translated into SUMX ( factorders, factorders[_Quantity] ), and there is no separate faster path for SUM.

The closing sentence of the section repeats the same reversed direction, and the first paragraph also has a typo (“expectation” should be “exception”).

To fix this, please replace the first paragraph with:
“Iterator functions can have a performance impact on large tables when the expression they evaluate for each row is complex. A simple aggregation function such as SUM is shorthand for its X version over a single column, so the two have the same performance. We recommend using the simple aggregation functions when you are aggregating a single column, since they are shorter and easier to read.”

Please also replace the closing sentence with:

“They both produce the same value with the same performance, since internally the first one is translated into the second one.”

Shabnam Watson
 
Oct 17, 2026