LocationMaster provides an online API with high performance web services for address parsing and validation, geocoding and reverse geocoding similar to the many commercial and home grown services available. These are designed to be integrated into web pages, applicatons, automated processes and work flows as well as being used to standardise and validate bulk data in database matching exercises.
Unlike other such services, LocationMaster also provides access and tools to manage the underlying address data. This includes integrating the large scale updates, retires and additions available in the public domain every quarter as well as the day to day address and location knowledge acquired in the normal course of your business activity. All changes to the underlying data are recorded and auditable. Which all means that address data issues are able to be quickly tracked down and fixed in real time whilst maintaining a high quality standard of address data.
Not only can the address data be managed, so can relationships between addresses. At the heart of LocationMaster, is a location based data model that enables even complex relationships between addresses to be modeled and used in automated decision processes.
Relationships such as alias addresses and primary/secondary addresses, to an extent, already available in the public address data for Australia but rarely, if ever, used in the current commercial address validation offerings. In LocationMaster they play an integral role. For example, if a location has two addresses (e.g. a corner block), it doesn't matter which of the two addresses you are given, LocationMaster would respond with the same location - enabling data matching with all associated addresses for that location.
LocationMaster takes these concepts even further by enabling seemingly unrelated addresses to be grouped together hierarchically as well as geographically. This opens up the possibility of modeling complex sites such as hospitals, university campuses, schools, shopping centres, airport precincts, business parks and multi street facing groups of apartment blocks. All examples that are either missing or badly represented in the current address data offerings. This give much more flexibility as to what is treated as an entity in order to achieve a particular business outcome.
The ability to use these relationships opens up a wide range of possibilities, especially with automated decision processes. No longer are you limited to simply matching addresses in your existing internal or external data, but you can relate an address to data about a location.
