Address standardization within a database - sql

Question

Working in MS Access 2013. Have a ton of locations/addresses which need to be standardized.
Examples include addresses like:
500 W Main St
500 West Main St
500 West Main Street
You get the point.
I've considered running a query that pulls all records where the left(7) or something characters exist more than once in the database, but there are obvious flaws in that logic.
Is there a function or query or anything else that would help me generate a list of records whose addresses may exist multiple times, in slightly different fashions?

Answer 1

This is a tricky business ... equal parts Black Magic and Science. You will be amazed at the variations of Boulevard alone.
This is why I use the Google API. It can be time consuming, for the initial data-set, but only new adds would need to be resolved.
For example
https://maps.googleapis.com/maps/api/geocode/json?address=500 S Main St,Providence RI 02903
returns, in part
"formatted_address" : "500 S Main St, Providence, RI 02903, USA"
and the GOOD News is
https://maps.googleapis.com/maps/api/geocode/json?address=500 South Main Steet,Providence RI 02903
returns the same formatted address as the previous query
"formatted_address" : "500 S Main St, Providence, RI 02903, USA"
VBA Example:
Upon executing the following code ...
' VBA project Reference required:
' Microsoft XML, v3.0
Dim httpReq As New MSXML2.ServerXMLHTTP
httpReq.Open "GET", "https://maps.googleapis.com/maps/api/geocode/json?address=500 South Main Steet,Providence RI 02903", False
httpReq.send
Dim response As String
response = httpReq.responseText
... the string variable response contains the following JSON data:
{
"results" : [
{
"address_components" : [
{
"long_name" : "500",
"short_name" : "500",
"types" : [ "street_number" ]
},
{
"long_name" : "South Main Street",
"short_name" : "S Main St",
"types" : [ "route" ]
},
{
"long_name" : "Fox Point",
"short_name" : "Fox Point",
"types" : [ "neighborhood", "political" ]
},
{
"long_name" : "Providence",
"short_name" : "Providence",
"types" : [ "locality", "political" ]
},
{
"long_name" : "Providence County",
"short_name" : "Providence County",
"types" : [ "administrative_area_level_2", "political" ]
},
{
"long_name" : "Rhode Island",
"short_name" : "RI",
"types" : [ "administrative_area_level_1", "political" ]
},
{
"long_name" : "United States",
"short_name" : "US",
"types" : [ "country", "political" ]
},
{
"long_name" : "02903",
"short_name" : "02903",
"types" : [ "postal_code" ]
},
{
"long_name" : "2915",
"short_name" : "2915",
"types" : [ "postal_code_suffix" ]
}
],
"formatted_address" : "500 S Main St, Providence, RI 02903, USA",
"geometry" : {
"bounds" : {
"northeast" : {
"lat" : 41.82055829999999,
"lng" : -71.4028137
},
"southwest" : {
"lat" : 41.8204014,
"lng" : -71.40319219999999
}
},
"location" : {
"lat" : 41.8204799,
"lng" : -71.40300289999999
},
"location_type" : "ROOFTOP",
"viewport" : {
"northeast" : {
"lat" : 41.8218288302915,
"lng" : -71.40165396970851
},
"southwest" : {
"lat" : 41.8191308697085,
"lng" : -71.40435193029151
}
}
},
"partial_match" : true,
"place_id" : "ChIJicPQAT9F5IkRfq2njkYqZtE",
"types" : [ "premise" ]
}
],
"status" : "OK"
}

Answer 2

John's answer is completely valid, I wanted to add also that you can achieve the same goal with HERE API. You can do this for free with HERE Maps and you won't need a credit card to get started.
https://geocode.search.hereapi.com/v1/geocode?q=500 West Main Street&apiKey=YOUR_API_KEY
Returns:
{
"items": [
{
"title": "500 W Main St, Alhambra, CA 91801-3308, United States",
"id": "here:af:streetsection:-2rEzgpCkFyX.gMQjWtV1A:CgcIBCCl6q07EAEaAzUwMChk",
"resultType": "houseNumber",
"houseNumberType": "PA",
"address": {
"label": "500 W Main St, Alhambra, CA 91801-3308, United States",
"countryCode": "USA",
"countryName": "United States",
"state": "California",
"county": "Los Angeles",
"city": "Alhambra",
"street": "W Main St",
"postalCode": "91801-3308",
"houseNumber": "500"
},
"position": {
"lat": 34.09193,
"lng": -118.13238
},
"access": [
{
"lat": 34.09241,
"lng": -118.13272
}
],
"mapView": {
"west": -118.13347,
"south": 34.09103,
"east": -118.13129,
"north": 34.09283
},
"scoring": {
"queryScore": 1.0,
"fieldScore": {
"streets": [
1.0
],
"houseNumber": 1.0
}
}
},
additional results...
So you can normalize your data based on the title.