Forum Discussion
Anonymous
3 years agoNot applicable
Create list based on multiple customer IDs
Hi all! I have a list of over 50k customers, but I am only concerned with aprox 1k of them - group A and Group B. I don't have access to the data in Excel format - I've linked Power BI directly ...
lbendlin
3 years agoSuper User
Please provide sanitized sample data that fully covers your issue.
Please show the expected outcome based on the sample data you provided.
Anonymous
3 years agoNot applicable
OK, let's try this! Here is the data (or at least how it would look in Excel. I know the customer ID's of all customers in Group A, and Group B. I need a way to filter just to show these two groups of customers. My data is being pulled from the cloud so I can't (or at least I don't think) I can create a column to calculate this.
| Customer ID | City | Type | Month | Revenue | |||||
| 1234567 | London | Retail | January | £ 22,536 | |||||
| 6549872 | London | Retail | January | £ 23,770 | |||||
| 1232209 | Leeds | Leisure | January | £ 25,004 | |||||
| 6547514 | London | Leisure | January | £ 26,238 | |||||
| 1229851 | New York | Leisure | January | £ 27,472 | |||||
| 6545156 | London | Retail | January | £ 28,706 | |||||
| 1227493 | Leeds | Retail | January | £ 29,940 | |||||
| 6542798 | London | Finance | January | £ 31,174 | |||||
| 1225135 | New York | Retail | January | £ 32,408 | |||||
| 6540440 | Leeds | Finance | January | £ 33,642 | |||||
| 1222777 | New York | Finance | January | £ 34,876 | |||||
| 6538082 | New York | Retail | January | £ 36,110 | |||||
| 1220419 | Leeds | Retail | January | £ 37,344 | |||||
| 6535724 | New York | Finance | January | £ 38,578 | |||||
| 1218061 | New York | Finance | January | £ 39,812 | |||||
| 6533366 | London | Finance | January | £ 41,046 | |||||
| 1215703 | London | Retail | January | £ 42,280 | |||||
| 6531008 | Leeds | Retail | January | £ 43,514 |
Simply put, I don't want any of the customers marked NA below to appear in my dataset.
| Customer ID | City | Type | Month | Revenue | |
| 1234567 | London | Retail | January | £ 22,536 | Group B |
| 6549872 | London | Retail | January | £ 23,770 | NA |
| 1232209 | Leeds | Leisure | January | £ 25,004 | NA |
| 6547514 | London | Leisure | January | £ 26,238 | NA |
| 1229851 | New York | Leisure | January | £ 27,472 | Group A |
| 6545156 | London | Retail | January | £ 28,706 | Group B |
| 1227493 | Leeds | Retail | January | £ 29,940 | NA |
| 6542798 | London | Finance | January | £ 31,174 | NA |
| 1225135 | New York | Retail | January | £ 32,408 | NA |
| 6540440 | Leeds | Finance | January | £ 33,642 | Group A |
| 1222777 | New York | Finance | January | £ 34,876 | Group A |
| 6538082 | New York | Retail | January | £ 36,110 | Group A |
| 1220419 | Leeds | Retail | January | £ 37,344 | NA |
| 6535724 | New York | Finance | January | £ 38,578 | NA |
| 1218061 | New York | Finance | January | £ 39,812 | NA |
| 6533366 | London | Finance | January | £ 41,046 | NA |
| 1215703 | London | Retail | January | £ 42,280 | NA |
| 6531008 | Leeds | Retail | January | £ 43,514 | Group B |
- lbendlin3 years agoSuper User
Here is an example. Feel free to modify/adjust. It will also work when the "NA" customers are missing from the dimension table. Understanding blank row and limited relationships - SQLBI