Mapping is the process of annotating the fields in a data source with a set of common terms Senzing understands and uses when performing Entity Resolution.
For instance, the column that contains a person's first name may be named fname in one data source and firstName in another. The corresponding term for a first name in Senzing is NAME_FIRST. Reducing the different column names to common terms allows entity resolution to work.
In the attribute pull down list for each column, you will find a list of terms to select from. It’s a good idea to familiarize yourself with this list as it will inform you as to what to look for in the columns of your data sources.
The attribute pull down list is grouped by category. There are common terms for names, addresses, phones, identifiers like drivers license, passport and email addresses, and other attributes like date of birth and gender. An ideal mapping would include:
- A name
- An address, phone, and/or email
- A date of birth and/or identifier
Unfortunately, not every data source has all of these. But they should have something besides just a name; name alone is not enough to perform Entity Resolution. However, you can use the search function on a full name once your data is loaded.
You will also find that the app automatically maps many data source columns automatically. Your task is to accept or correct the ones it mapped automatically and manually assign the ones not auto mapped.
One final thought, not every column in every data source is useful to the entity resolution process! That is you don't need to map every column, but it will still be ingested for your subsequent reference. This is useful for displaying in reports, for example.
To include or exclude a data source column tick/untick the include check box at the top of the column. In this example the CONFIRM_IP column will be ingested and available for reference, but it will not be used for Entity Resolution as it is not mapped to a valid Senzing attribute term.
Ideally you wouldn't include every un-mapped column from a source, especially columns with a large amount of text in them as they will make your reports harder to read. Remember, you can always go back to the source system and view the full details of all fields that are not relevant and used by Entity Resolution.
That’s all there is to mapping! We suggest you add your data sources one by one and review the matches Senzing determined each time. See the troubleshooting article if you didn’t get the results you were expecting.