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When receiving bulk updates from vendors, what is the the best update
Automated updates can save you effort, but sometimes can cause good data to be overwritten.
It also depends on the size of your data update, the quality of your existing data and how many staff you have to perform the operation, balanced against the risks of adding incorrect information.
Automated updates generally work better for tasks like formatting addresses to meet address standards or other tasks of a formatting nature. Automated update routines, no matter how sophisticated, still can't match the ability of skilled staff members in doing the analysis on a record by record basis to determine which data has greater validity.
Automated updates also work better when the time from when the data was sent to the vendor, to when it was received back is short. You should also have automated load and checking programs written in advance, so again the delay between receiving the data and updating is reduced to a minimum.
It's always useful to set up a fairly extensive review first to determine the accuracy of the information received from the vendor and check this against your database. You should also contact the sample set directly to verify information.
It's also useful to take a snapshot of each of the tables that will be changed before the actual update is done so you can easily create a before and after analysis report.
You can put certain criteria on the updates, for instance, select the date you send the information to the company, any updates in the system after this date are not written over with the information you have received from the vendor.
You should also become familiar with how the logic of the program your vendor uses works as you may want to apply some similar strategies as part of your in-house pre-checking.
Keep statistics of the number of pieces of data updated so you can also track the effectiveness of your vendor. Keep statistics of the time it took your staff to update/correct the information so you can improve your internal business processes.
The exercise of mass updating data usually ends up being a combination of automated updating and a lot of manual checking and verification both at the front and back end of the process.
If you have a small database and the staff resources, you may wish only do manual updates and corrections.