Once you have edited your inventory information, whether it is adjusting stock counts, or prices, etc. You will need to re-import that data back into System Five. The first thing that you should always do prior to a data load is do a backup. Just in case you either encounter an error or the items are imported into a wrong location. 

*your spreadsheet needs to be saved as Comma Separated Values (*.csv) 

* if you are including a long description or notes column please ensure it does not contain multiple lines (includes a carriage return character that will cause the load not to work).


From the Navigator menu, select Inventory and Purchases, Data Load, then Part Load.

Then click From File

You will then need to browse to the file you created in the previous section, and make sure that the drop down menu shows Comma Separated Values (*.csv). Select your file and click on open.

Click Next to continue.

You will need to match all the columns with the appropriate column field from the drop down box (or right click on the column you wish to map). If you do not want to import a column, then you still must select the column, but select the column field named none. We recommend setting the columns you do not wish to load to 'none' so it is ignored.

The most important column is the Category Column. This one absolutely must be selected, or all items will be placed in one category. Once all the columns have been named, click next.

Select Load into Regular Parts, and Skip header row, and click next. If you are missing information/columns the Next button will not activate and a message will show in the bottom green area to indicate what is missing.

Since we have already modified our data from within Excel, we can click next and completely bypass this page.

Click load to begin our data load.

When the data load is complete, Click OK, then you can View the Log, which is a more complete listing of what was done during the data load, than what appears in this summary.


Or you can click on Close.

Your data load is now complete