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Hi all, I'm trying to create an aggregated version of a fact table and am running into some issues with the summarization.
My Fact table is in this format:
| query_id | month | source | product | location | indicator | category |
| 123 | 01/01/2024 | Phone | bike | Texas | 0 | Change of Mind |
| 547 | 01/01/2024 | In Person | bike | California | 1 | Faulty |
| 123 | 01/01/2024 | Phone | car | Texas | 0 | Change of Mind |
I am trying to summarize this into a simple aggregated table with the count of distinct ids like so:
| month | source | product | location | indicator | category | total_queries |
| 01/01/2024 | Phone | bike | Texas | 0 | Change of Mind | 4 |
| 01/01/2024 | In Person | bike | California | 1 | Faulty | 9 |
| 01/01/2024 | Phone | car | Texas | 0 | Change of Mind | 45 |
I am using this DAX to generate the table:
SUMMARIZED_QUERIES = SUMMARIZE(FACT_TABLE,FACT_TABLE[category],FACT_TABLE[indicator],FACT_TABLE[location],FACT_TABLE[product],FACT_TABLE[source],FACT_TABLE[month],"total_queries",DISTINCTCOUNT(FACT_TABLE[query_id]))
Solved! Go to Solution.
Hello @purple_SP ,
Please try adding the "All" or "AllSelected" function within your summarized formula so that you can ignore specific filters if there is any..
SUMMARIZECOLUMNS(
FACT_TABLE[month],
FACT_TABLE[source],
FACT_TABLE[product],
FACT_TABLE[location],
FACT_TABLE[category],
FACT_TABLE[indicator],"total_queries", DISTINCTCOUNT(ALL(FACT_TABLE[query_id])))
If you find this helpful , please mark it as solution which will be helpful for others and Your Kudos/Likes are much appreciated!
Thank You
Dharmendar S
Hello @purple_SP ,
Please try adding the "All" or "AllSelected" function within your summarized formula so that you can ignore specific filters if there is any..
SUMMARIZECOLUMNS(
FACT_TABLE[month],
FACT_TABLE[source],
FACT_TABLE[product],
FACT_TABLE[location],
FACT_TABLE[category],
FACT_TABLE[indicator],"total_queries", DISTINCTCOUNT(ALL(FACT_TABLE[query_id])))
If you find this helpful , please mark it as solution which will be helpful for others and Your Kudos/Likes are much appreciated!
Thank You
Dharmendar S
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