Utilizing the NARY_MAX Function in Looker Studio: A Comprehensive Guide to Enhancing Data Analysis Efficiency

 Utilizing the NARY_MAX Function in Looker Studio: A Comprehensive Guide to Enhancing Data Analysis Efficiency

Utilizing the NARY_MAX Function in Google Data Studio

Introduction to the NARY_MAX function

Operating within the Google Data Studio, the NARY_MAX function offers a remarkable methodology to determine the highest value among multiple inputs. The function stands as an adaptive variant of the standard MAX function, accommodating a more extensive range of comparisons involving an array of values.


NARY_MAX(X, Y, [,Z]*)
The limitation resides in the function's requirements, as it mandates a minimum of two arguments for execution. Moreover, at least one of these arguments must represent a field or an expression imbued with a field. Also, it only accepts arguments of similar types, such as numbers.

Utilizing the NARY_MAX Function

The function usage boils down to a simple yet effective structure wherein you link values through commas, and NARY_MAX deciphers the maximum among them. Remember to retain the argument variety within the same type - all as numbers, for instance.


To best elucidate the utilization of the NARY_MAX function, let's construct a scenario related to a hypothetical sales company. Picture a business with separate product lines, each with its unique sales numbers.

Consider an inventory like this:

|Date|Product 1 Sales|Product 2 Sales|Product 3 Sales| |-|-|-|-| |Jan 01, 2021|5,200|7,500|6,000| |Jan 02, 2021|5,400|8,000|6,400| |Jan 03, 2021|5,750|7,750|6,250|

With the use of the NARY_MAX function, the business can effortlessly identify the most profitable product line per day.

NARY_MAX(Product 1 Sales, Product 2 Sales, Product 3 Sales,)

Rendering results such as:

|Date|NARY_MAX selling product| |-|| |Jan 01, 2021|7,500| |Jan 02, 2021|8,000| |Jan 03, 2021|7,750|

From here, the company may infer that Product 2 is performing the best sales-wise.

Limitations of the Function

As highlighted, NARY_MAX necessitates a minimum of two arguments and field-containing arguments. Moreover, it upholds an unwavering homogeneity concerning argument types. Mixing numbers, texts, and dates, for example, would lead to the execution not processing.

Tips and Tricks

Always ensure that all arguments within a NARY_MAX function call reside within the identical type. And given it returns unaggregated dimensions automatically, bear in mind to set specific aggregation rules when dealing with higher complexity data.

To recap, NARY_MAX stands as a robust tool within the capabilities of Google Data Studio. It enhances the efficiency of discerning maximum values among arrays of data, given they adhere to its functional limitations and guidelines.

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