biontest.blogg.se - Azure data studio filter tables

In addition, you can use a more complex condition with regular expression matching and logical AND. IF(Actual Sales > Forecast Sales, Bonus * 1.4, Bonus) Then, bonuses will be distributed accordingly. If they do, your new column will the “Bonus” by 1.4, which presumably is going to info you sales team. This simple condition will calculate if “Actual Sales” exceed the “Forecast Sales”.

False_result: This refers to the value that will be returned if the condition is false.

True_result: This refers to the value that will be returned if the condition is true.

It consists of any valid boolean expression. The basic syntax is as follow: IF(condition, true_result, false_result) Parameters Similar to other platforms, you can use the IF function to return a dimension based on a given condition or rule. This has been a highly anticipated function and everyone was ecstatic when Google brought it to life. However, with the simplified CASE statement, you can do the following and save a bit of time! How to create IF statements in Google Data Studio? For example, if you have the same “Campaign” name, but this time, you want to use the year as a matching criteria.įollowing the same logic as our past examples, you would normally write this standard CASE statement. In recent feature updates, Google has made it even easier to write repetitive CASE statements by declaring the field at the beginning. In a little bit more detail: How to write simplified CASE statements by declaring a field to test once? All we are doing with the regular expression is telling Data Studio that every time the capital letters “EN” or “FR” are spotted in the “Complex Campaign” dimension, the text strings should be named “English” and “French”, respectively. “Campaign” is inside brackets, unlike IN where it is outside. We start the WHEN statement the same way, without much difference. Google Data Studio (and most Google products) uses the RE2-style syntax. Quick background: Regular expressions are a notation for describing sets of character in a specific word or any text string. This is why we are going to try out the REGEXP_MATCH function, also referred to as regex.

If we were to use IN, then the list in the CASE function is going to grow substantially and we are more likely to make a mistake while writing it. For example, in the “Complex Campaign” dimension, we have a lot of different and unique campaign iterations. Now, what happens if things get more complicated. How to use REGEXP_MATCH function within CASE? Now if we want to see the campaign simply filtered by the “Language” dimension, we can even exclude “Campaign”. The result is exactly what we were looking for. Finally, I go ahead and choose my campaign name(s) and specify with THEN what I want to name the result of my WHEN condition. Then adding IN, which instructs Data Studio that I will be listing text strings. In the statement below, I am opening the CASE with a WHEN, specifying the first condition. The trick with the CASE function is that you often have to find a unique common denominator to parse the data correctly.

This is where you can use the CASE function to write a specific statement. However, you want to see the table below only per “Language”. In the table below, you have a paid digital marketing campaign that includes “EN” and “FR” in the campaign name. The CASE function returns dimensions and metrics based on conditional expressions it is often used to create new groupings of data and sort them in categories. Enjoy! What is the Data Studio CASE function? *NEW – By popular demand, I have decided to expand the comprehensive guide on CASE and added IF statements, as the Google Data Studio team has had some incredible updates over the past year. In addition, I have added a section on how to compose the new Simplified CASE statements. I personally think that knowing how to write a CASE is not only helpful in Data Studio, but also it allows you to understand how computer logic works. In this post, we are going to explore one of the most useful functions in Google Data Studio, the CASE.