Hi everyone,
I found a couple similar posts but couldn't find one that had a solution for my specific scenario. I am also fairly new to creating workflows from scratch, so I apologize in advance.
I'm trying to identify IDs that have multiple company names and addresses linked to them from a large data set of thousands of records. I was able to group by ID and Company name, however the data could use some cleansing as some of the company names are being counted more than once due to the different naming conventions (see sample attached). How can I clean the data to group by similar company name under the same ID?
I hope my question makes sense.
| State | ID | Company |
| WA | 123456789 | BIG POPPA |
| AZ | 123456789 | BIG POPPA INC |
| AZ | 123456789 | BIG POPPA INCORPORATED |
| NY | 123456987 | AYE AND BEE INC |
| TX | 123456987 | AYE & BEE INC |
| FL | 254170270 | BEYONCE |
| FL | 254170270 | SOLANGE |
| CA | 313076766 | PARKWOOD WAY |
| WA | 313076766 | PARKWOOD WY |
| AZ | 678912345 | STONEBRICK PL |
| AZ | 678912345 | STONERICK PL |
| TX | 876543219 | NICKI MONET |
| AZ | 876543219 | NICKY MONET |
| CA | 987654321 | MACY GRAY |
| AZ | 987654321 | MACY GREY |
| CA | 987654321 | RIH STUDIOS |