hi help!!! I have done a write to table. All Columns are the same but I have had to define which row is first name, last name etc... Anyway done that but it has caused the existing first and last names to dissappear. See screen shot 3 questions. 1. what have I done wrong? 2. can i go back? 3. how should I handle this data going forward. I don't want to create new columns and then merge with a formula... Thanks.
When using write to table, existing data can disappear if column mapping overwrites the original data. To fix this issue: 1. Delete the affected column 2. Create a fresh column 3. Re-map your data to the write to table (ensure auto-dedup is activated) For future data handling, consider column dependencies when restructuring. Columns won't re-run automatically, which helps preserve existing data unless you trigger them. If adding new rows, filter for those rows first, then run enrichments on that filtered view to avoid overwriting existing data. Unfortunately, there's no direct undo feature mentioned in our documentation for this specific scenario.
Hi Ross, using write to other table, you should always create net new destination columns and merge the final outputs into one column to prevent overwriting your data. If you overwrote that data or accidentally deleted it, the only way to reproduce the previous table view is to set up a new Clay table, and rerun the enrichments. I understand that this is not ideal, and I want to assure you that our team is actively working on this issue for future product releases. Using the "send table data" action, should prevent this issue from occurring, we suggest that you test this action out:
Thanks for letting me know. makes sense!
Sorry it was actually "send data to table" that caused the original info to disappear. Can you explain how to do this without data disappearing?
Hi Ross, thank you for reaching out! Instead of mapping data to existing an column, create a new column and then use 'Merge Column' to create a column that combines data from the old column and the new column into one single column.