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Ashi
Helper I
Helper I

calculated columns vs replace values vs a separate connection table

I have few flags as (1/2/3)  in my data sets which have specific meanings.

for eg,

if 1 then active

if 2 then partial active

if 3 then completely active.

so considering the performance which of the following method do you suggest???

1>in edit query, change data type and replace values

2>create a calculated column.

3>create a separate table in power bi and then connect the two.

 

1 ACCEPTED SOLUTION
GilbertQ
Super User
Super User

Hi @Ashi

 

What I would suggest or what I would do, is to create a new column in the Query Editor.

 

By doing it in the Query Editor it is very easy to create the Conditional Column. As well as if there ever were any changes it would be easy to update.

 

It would also give you better performance because the column is created before the data is compressed using the Vertipaq compression algorithm. And then you could use this new column in a slicer or filter (Soon to be released Drill Through) if required.





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3 REPLIES 3
v-jiascu-msft
Employee
Employee

Hi @Ashi,

 

Could you please mark the proper answer as solution or share the solution if it's convenient for you? That will be a big help to the others.

Best Regards!
Dale

Community Support Team _ Dale
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
GilbertQ
Super User
Super User

Hi @Ashi

 

What I would suggest or what I would do, is to create a new column in the Query Editor.

 

By doing it in the Query Editor it is very easy to create the Conditional Column. As well as if there ever were any changes it would be easy to update.

 

It would also give you better performance because the column is created before the data is compressed using the Vertipaq compression algorithm. And then you could use this new column in a slicer or filter (Soon to be released Drill Through) if required.





Did I answer your question? Mark my post as a solution!

Proud to be a Super User!







Power BI Blog

hi @GilbertQ,

Thanks for the suggestion.

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