This is the most simpliest and typical address search. In this example a user will be searching for an address (with only the street name and state) in USA data. The final address to be returned is:
290 Bridge St
VAIL CO 81657-4590
Fuzzy matching is the process of intelligently searching for an address, approximately matching the address information provided by the user to addresses in the authoritative reference dataset (i.e. from Royal Mail, USPS, Australia Post), and returning all likely possibilities for the user to select from. This is useful when the user provides too little or too much information, inputs the address in the wrong format or includes a typo.
Our real-time Data Validation app for SAP S/4HANA leverages advanced fuzzy matching logic to deliver the most approximate search results for the user to select from, based on a degree of confidence, rather than an exact match. The solution intelligently recognizes and works around the errors below, reformats the address if needed and includes missing elements to deliver a correct, complete, and formatted address.
Abbreviations – users enter abbreviations for certain address components. For example, Av for Avenue, Blvd for Boulevard, Rd for Road as well as Ch for Chemin (French) or Str for Straße (German).
Typos – users make errors in data entry, especially when on mobile devices or spelling addresses phonetically. For example, entering an 'n' instead of an 'm' or entering 'streeet' instead of 'street'.
Incorrect ordering or format – users don't always enter the address in the way it appears on an envelope. For example, enter the town or city first, followed by the street and building number.
Missing or additional spaces – users add or miss spaces between words or even within words without realizing.
Missing or additional information – users provide too little or too many address elements when searching for an address. For example, leave out the property/building number.
If the address input cannot be matched to any likely address, a "No matches" message will be shown to the user.
When you search with our real-time Data Validation app for SAP S/4HANA you can use wildcards to replace one or more missing letters in your address information. There are two wildcards available. You can use a combination of wildcards in your search.
Question mark wildcard (?)
This wildcard replaces a single character in an address or postal code. For example:
Lov?tt St, Manly Vale (AUS data)
or
Hawthorn Ave, ?N21 ?HA (GBR data)
Asterisk wildcard (*)
This wildcard replaces any number of characters at the end of an address element, except postal code. For example:
Bridge , Vail (USA data) or rue de la Creuse, Vendin (FRA data)
Multiple wildcards
The example below shows how to search for an address in GBR data where part of the street name and a character from the postal code are unclear. You know that the street
name begins with “Aldis”, but not the street descriptor (“Drive”, “Road”, etc).
A user can also use the asterisk to look for certain keywords. To do this, precede the first address element with the asterisk wildcard. For example, the search “*park, perth” returns all addresses in the city of Perth (in AUS data) with a first address element of “park”.
In a keyword search, the asterisk can be anywhere in the address element. This type of search is especially useful if you are looking for a particular type of organisation or institution (banks, colleges, hospitals etc.). For example, the search “*university,melbourne” looks for any university in Melbourne.
When you enter property information, you can return an unrecognized address by entering the premise number, followed by !. For example: