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prabuj
Contributor III
Contributor III

How can you solve this scenario in Talend ?

Dear Team, @richard Hall @Shicong Hong @Fred Trebuchet

I have data coming like this. Could you give a solution to solve it. ?

AT DAY-1, I load the data into target. IT's a delta process

0695b00000hsMtmAAE.png

0695b00000hsMtrAAE.png

BOTH ARE SAME CUSTOMER, BUT HAVE NO IDENTITY TO FIND THEY ARE SAME.

AT DAY N, THE CUSTOMER IS SAYING - DAY-2 RECORD IS GOOD ONE. HOW CAN I KEEP A FLAG "AS THE DAY 1 DATA AS OLD CUSTOMER ID", AND "DAY-2 DATA AS NEW CUSTOMER ID".

THANKS IN ADVANCE.

Labels (3)
1 Solution

Accepted Solutions
LLopeza1682662066
Contributor II
Contributor II

Hello, try this steps.

  1. Compare the data from DAY-1 and DAY-2 to identify matching customer attributes such as name, address, or any other relevant identifiers.
  2. Use a suitable algorithm or logic to determine the degree of similarity between the DAY-1 and DAY-2 records. This could involve comparing fields for exact matches or utilizing fuzzy matching techniques to account for slight variations in the data.
  3. Based on the comparison results, if a match is found, assign a flag or a unique identifier (e.g., "OLD_CUSTOMER_ID" for DAY-1 data and "NEW_CUSTOMER_ID" for DAY-2 data) to differentiate between the old and new records.
  4. Ensure that the assigned flag or identifier is included in the target data during the delta process and stored accordingly.

By implementing this approach, you can distinguish between the DAY-1 and DAY-2 data and assign appropriate flags or identifiers to indicate whether the customer is considered old or new. Home Bargains Portal

 

 

View solution in original post

2 Replies
Anonymous
Not applicable

Hi

If you can't modify the table, create a new table to store the customer id and add a new flag field? Then, whenever you load the data into target in ETL job, synchronize the related data in this identity table.

Regards

Shong

LLopeza1682662066
Contributor II
Contributor II

Hello, try this steps.

  1. Compare the data from DAY-1 and DAY-2 to identify matching customer attributes such as name, address, or any other relevant identifiers.
  2. Use a suitable algorithm or logic to determine the degree of similarity between the DAY-1 and DAY-2 records. This could involve comparing fields for exact matches or utilizing fuzzy matching techniques to account for slight variations in the data.
  3. Based on the comparison results, if a match is found, assign a flag or a unique identifier (e.g., "OLD_CUSTOMER_ID" for DAY-1 data and "NEW_CUSTOMER_ID" for DAY-2 data) to differentiate between the old and new records.
  4. Ensure that the assigned flag or identifier is included in the target data during the delta process and stored accordingly.

By implementing this approach, you can distinguish between the DAY-1 and DAY-2 data and assign appropriate flags or identifiers to indicate whether the customer is considered old or new. Home Bargains Portal