“measure twice, cut once”

Ok, so we are logged in and ready to rock.

Let’s start with a small Test file with only a few records.

This is ideal to make sure everything is configured properly and makes it easier to spot errors before a big upload.

After you pick the right object where the Data Loader will insert data, you can select the data file. Once the file to import is initialized, the count of records is returned. If the number of records matches, this ensures there’s no problem so far.

Next, we’ll map field names. By using auto-match, Data Loader will try to match standard fields between Salesforce and your data file. If this is not enough or not accurate, you can manually drag and drop the correct fields from the SF list to the Column Header list.

At the end of the process, Data Loader will create a success or error file. You can decide where it will be saved. Remember they will always be called Success or Error. You may want to rename them in such a way that they’ll be easier to identify. The final screen shows total successes and failures.

By checking the success file, you’ll see that the record now includes a Salesforce ID field, with its own unique value. This ID can be useful later on if we need to import or change the information in the same record. Also, if an Error file is generated, you can see what went wrong. We can now fix the problem and reimport.

Finally, here are a few points to remember:

Data Loader on1y recognizes 1 field for the street address. If you have more than one field, they have to be combined into a single one. Data Loader only matches Salesforce ID, while updating, therefore will not catch duplicates names or emails.

Lastly, all currently active workflows will trigger on any record that meets the criteria. It is best to temporarily suspend their execution while uploading/updating data via Data Loader.