Summary: In this article we will review, the criteria needed to successfully import a .csv in Organizer
How can an import fail?
In the side panel for an import, a user will see "Data could not be imported because it did not meet the minimum import requirements" if and only if 0 records were able to be imported from the source .csv file. This could be due to any of the following reasons:
All records failed validation
All records failed to be geocoded
Some records failed validation and the rest failed to be geocoded.
Records can fail validation for different reasons depending on the import type.
If the type of import chosen was "Upload CSV", records can fail validation for any of the following reasons:
Missing person id
Missing first name and last nameIf the type of import chosen was "Address" which can be used for hotspot, records can fail validation for any of the following reasons:
missing City, Street Name, and Street Number (if no latitude/longitude is provided)
missing City and Street Name (if latitude/longitude is provided)
Records can fail geocoding for any of the following reasons:
Not enough address information was provided to associate it with a latitude/longitude
The address information provided was misspelled or otherwise incorrect and does not actually exist
Google does not have data on the provided address (more common in extremely rural areas)
How can an import failure be handled?
A import failure can be archived by clicking the down arrow at the end of the failed import row.
Here is a useful workflow for dealing with data errors in records:
2. If import fails, click on it to open the right side panel which contains additional information.
3. Under "IMPORT SUMMARY" in the right side panel, expand the line that contains Total Records Failed.
4. Download the link(s) with the text "View Details" next to the invalid records count and/or the geocoding errors count.
5. Open each file in a csv viewer (such as Microsoft Excel or Google Sheets) and correct the errors. (See above in Validation Failures or Geocoding Failures to understand the errors.)
6. Re-import each corrected .csv file.
7. Create a list using the successful imports as sublists.