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DeepikaMalakalapalli
Contributor
Contributor

Question on Filter Restrictions in Qlik Sense with Joined Tables

Hi everyone,

I’m currently working on a Qlik Sense project and have encountered an issue related to filter restrictions when joining two tables. I’d appreciate any insights or solutions you might have.

Scenario:

I have two tables:

  1. Table 1: Contains normal data with multiple columns, including a common identifier column (ID).
  2. Table 2: Contains aggregated data, grouped by the same ID, with fewer columns.

From these tables, I need to extract:

  • 3 specific columns from Table 1
  • 2 specific columns from Table 2

However, when I attempt to join these tables using the ID column, I’m facing a data mismatch issue. The results seem inconsistent, and I suspect it might be related to the way filters are being applied in Qlik Sense.

Has anyone experienced a similar issue or have suggestions on how to properly join these tables while avoiding data mismatch? Any help with understanding filter restrictions in this context would be greatly appreciated!

Thanks in advance for your assistance!

Best,
Deepika M

 

Labels (1)
3 Replies
Anil_Babu_Samineni

Since you have common field (ID), It will do auto association, What if in case if you are leaving as it is with load of 2 different Tables? Is this still issue?

Is this same scenario in the source side as well?

Best Anil, When applicable please mark the correct/appropriate replies as "solution" (you can mark up to 3 "solutions". Please LIKE threads if the provided solution is helpful
marcus_sommer

Don't join or associate the tables else just concatenate them - within the most scenarios it should work well, see also: Fact Table with Mixed Granularity - Qlik Community - 1468238

AnsweringTuring
Contributor III
Contributor III


To properly join two tables in Qlik Sense while avoiding data mismatch issues, you need to ensure that the filters are applied correctly. Here are some steps you can take:

1. Verify that the ID column in both tables has the same data type and format. Any discrepancies in data types or formats can cause issues during the join operation.

2. Use the "Keep" prefix when loading the tables to preserve the original data structure and avoid automatic concatenation. This will allow you to control the join operation explicitly.

3. Perform an inner join between the two tables using the ID column as the join key. This will ensure that only records with matching ID values from both tables are included in the result.

4. Apply filters after the join operation to avoid any unintended data loss or mismatch. Filters applied before the join can potentially exclude records that should be included in the join result.

5. If you need to apply filters before the join, use the "Qualify" prefix to create a temporary table with the desired filters, and then join this temporary table with the other table.

6. Verify the join result by checking the number of records and the data distribution. You can use the "Peek" function or create a visualization to inspect the joined data.

By following these steps, you should be able to join the two tables correctly while maintaining data integrity and avoiding any data mismatch issues caused by improper filter application.