UK Zip Code List - Nearest Five Zip List - database

Does anyone know of a free postcode CSV for UK? I have one for the USA but can't fined a UK equivalent.
I want to implement nearest Five kind of logic based on long, Lat.
Kindly let me know if any one is aware.
Regards,
Jigar

It looks like you need to explore the Ordnance Survey OpenData dataset.
The UK doesn't have zip codes; rather, it has postcodes, which are much more precise. For example the building where I work has a postcode to itself, BS1 2PH.
Commercial organisations that validate postcodes use the Postcode Address File, which is commercially licensed (and expensive!), mostly as maintaining a per-premise address format is very time-consuming.
In practice most Web sites. etc. use Web services such as Postcode Anywhere which aggregate and resell the data.

Related

How do I structure multiple Identity Data in a database

Am designing a database for a credit bureau and am seeking some guidance.
The data they receive from Banks, MFIs, Saccos, Utility companies etc comes with various types of IDs. E.g. It is perfectly legal to open a bank account with a National ID and also a Passport. Scenario One that has my head banging is that Customer1 will take a credit facility (call it loan for now) in bank1 with the passport and then go to bank2 and take another loan with their NationalID and Bank3 with their MilitaryID. Eventually when this data comes from the banks to the bureau, it would be seen as 3 different people while we know that its actually 1 person. At this point, there is nothing we can do as a bureau.
However, one way out (for now) is using the Govt registry which provides a repository which holds both passports and IDS. So once we query for this information and get a response, how do I show in the DB that Passport_X is related to NationalID_Y and MilitaryNumber_Z?
Again, a person's name could be captured in various orders states. Bank1 could do FName, LName, OName while Bank3 can do LName, FName only. How do I store this names?
Even against one ID type e.g. NationalID, you will often find misspellt names or missing names. So one NationalID in our database could end up with about 6 different names because the person's name was captured different by the various banks where he has transacted.
And that is just the tip of the iceberg. We have issues with addresses, telephone numbers, etc etc.
Could you have any insight as to how I'd structure my database to ensure we capture all data from all banks and provide the most accurate information possible regarding an individual? Better yet, do you have experience with this type of setup?
Thanks.
how do I show in the DB that Passport_X is related to NationalID_Y and MilitaryNumber_Z?
Trivial.
You ahve an identity table, that has an AlternateId field if the Identity is linked to another one. Use the first IDentity you created as master. Any alternative will have AlternateId pointing to it.
You need to separate the identity from the data in it, so you can have alterante versions of it, possibly with an origin and timestampt. You need oto likely fully support versioning and tying different identities to each other as alternative, including generating a "master identity" possibly by algorithm with the "official" version of your data (i.e. consolidated).
The details are complex - mostly you ahve to make a LOT of compromises without killing performance, so at the end HIRE A SPECIALIST. There is a reason there are people out as sensior database designers or architects that have 20+ years experience finding the optimal solution given the constrints you may not even be aware of (application wise).
Better yet, do you have experience with this type of setup?
Yes. Try financial information. Stock symbols / feeds / definitions are not necessariyl compatible and vary by whom you get it. Any non-trivial setup has different data feeds that may show the same item slightly different, sometimes in error. DIfferent name, sometimes different price (example: ES, CME group, is 50 USD per point, but on TT Fix it is 5 - to make up, the price is multiplied by 10, so instad of 1000.25 you get 10002.5). THis is the same line of consolidation, and it STINKS.
Tons of code, tons of proper database design, redoing it half a dozen time to get the proper performance. THis is tricky, sadly.

Database Design, Google Maps, and Address Fields

I want to collect the addresses of my users so that I can plot them on a Google Map. I know I need to store the lat/long values of their address, which I can get from Google Map API.
I'm looking for recommendations on how to divide the various address parts and save them to the database. I commonly see things like this:
Address Line 1
Address Line 2
City
State/Region/Province
ZIP/Postal Code
Country
Google breaks down these address components differently, though. See, for example: http://maps.googleapis.com/maps/api/geocode/json?address=1600+Amphitheatre+Parkway,+Mountain+View,+CA&sensor=false
I'm not sure what parts of Google address components equate to what is commonly seen in web forms (e.g. is administrative_area_level_1 always the state/region/province?). I'd like to store the various address components as atomically as possible so that I have the greatest control when displaying the address information later on.
NOTE: I also plan to store the formatted_address as I think that could be useful in some cases.
So, what should I store in my database?
This section of the Geocoding documentation provides a pretty good description of the types of data you get back from the reverse geocoder. These data types were developed by Google to describe any address in the world, so are probably a good starting point.
Based on the following quote the administrative_area_level_1 describes subnational jurisdictions, states in the US/Australia, prefectures in Japan, provinces in france etc:
administrative_area_level_1 indicates a first-order civil entity
below the country level. Within the
United States, these administrative
levels are states. Not all nations
exhibit these administrative levels.
You will probably need to be careful about the assumptions you make about these datatypes for other countries. For instance, the administrative_area_level_1 for addresses in London is England. But with a good understanding of this schema, you should be able to render locale friendly addresses anywhere in the world.

Is there a public geolocation system that I can query for names of local cities?

I'm looking to attempt to simplify address entry into a system where the city textbox has autosuggest initially populated by the user's geolocation. In the past it has seemed that autosuggesting the city name is prohibitively costly without knowing the province/state/country first but it doesn't make sense to require the user to enter the address backwards as we don't think about address information this way. On the other hand, not autosuggesting the city name means we end up with all sorts of weird and wonderful entries for mis-spelled cities from around the world.
I was wondering if there's a service that I can query that would automatically respond with the most appropriate city names according to not only what the user enters in the textbox, but the location of that user based on the country and political boundary they fall within?
For instance, if I am in Canada [as I am] and I enter 'Mi' then I'd be presented with all cities within Canada starting with 'Mi' until it was determined that the information I was entering wasn't Canadian at which point, it would use the next most likely configured country based on our usage pattern - i.e. it would check the U.S. next, followed by Mexico and then other less likely destinations. I can write all this myself if I had the database but I don't know where I can find one and my suspicion is that it would be less scalable than querying a pre-existing service on the web.
Looks as though MaxMind offers a free database that you could download in CSV:
There's an online demo to test it a bit if you'd like, but no way to query it through a web service.
IPInfoDB also has their database available for download - they have an XML API, but it only supports looking up the city/country for a particular IP. You're trying to do something a little more wide than that, looking for every city in a particular country, with country selected based on IP. I wouldn't expect that there's a web service for that, it's a pretty specific requirement.
Edited to add: You could use the IPInfoDB API to look up the country though, and then generate the autocomplete suggestions from a local country/city database. That way all the IP-geolocation wouldn't need to be done locally. There are various places that you can get a list of cities in a particular country. For example, here's some comprehensive lists maintained by the National Geospatial-Intelligence Agency

Best practices for storing postal addresses in a database (RDBMS)?

Are there any good references for best practices for storing postal addresses in an RDBMS? It seems there are lots of tradeoffs that can be made and lots of pros and cons to each to be evaluated -- surely this has been done time and time again? Maybe someone has at least written done some lessons learned somewhere?
Examples of the tradeoffs I am talking about are storing the zipcode as an integer vs a char field, should house number be stored as a separate field or part of address line 1, should suite/apartment/etc numbers be normalized or just stored as a chunk of text in address line 2, how do you handle zip +4 (separate fields or one big field, integer vs text)? etc.
I'm primarily concerned with U.S. addresses at this point but I imagine there are some best practices in regards to preparing yourself for the eventuality of going global as well (e.g. naming fields appropriately like region instead of state or postal code instead of zip code, etc.
For more international use, one schema to consider is the one used by Drupal Address Field. It's based on the xNAL standard, and seems to cover most international cases. A bit of digging into that module will reveal some nice pearls for interpreting and validating addresses internationally. It also has a nice set of administrative areas ( province, state, oblast, etc ) with ISO codes.
Here's the gist of the schema, copied from the module page:
country => Country (always required, 2 character ISO code)
name_line => Full name (default name entry)
first_name => First name
last_name => Last name
organisation_name => Company
administrative_area => State / Province / Region (ISO code when available)
sub_administrative_area => County / District (unused)
locality => City / Town
dependent_locality => Dependent locality (unused)
postal_code => Postal code / ZIP Code
thoroughfare => Street address
premise => Apartment, Suite, Box number, etc.
sub_premise => Sub premise (unused)
A lessons I've learned:
Don't store anything numerically.
Store country and administrative area as ISO codes where possible.
When you don't know, be lax about requiring fields. Some country may not use fields you take for granted, even basic things like locality & thoroughfare.
As an 'international' user, there is nothing more frustrating than dealing with a website that is oriented around only US-format addresses. It's a little rude at first, but becomes a serious problem when the validation is also over-zealous.
If you are concerned with going global, the only advice I have is to keep things free-form. Different countries have different conventions - in some, the house number comes before the street name, in some it comes after. Some have states, some regions, some counties, some combinations of those. Here in the UK, the zipcode is not a zipcode, it's a postcode containing both letters and numbers.
I'd advise simply ~10 lines of variable-length strings, together with a separate field for a postcode (and be careful how you describe that to cope with national sensibilities). Let the user/customer decide how to write their addresses.
If you need comprehensive information about how other countries use postal addresses, here's a very good reference link (Columbia University):
Frank's Compulsive Guide to Postal Addresses
Effective Addressing for International Mail
You should definitely consider storing house number as a character field rather than a number, because of special cases such as "half-numbers", or my current address, which is something like "129A" — but the A is not considered as an apartment number for delivery services.
I've done this (rigorously model address structures in a database), and I would never do it again. You can't imagine how crazy the exceptions are that you'll have to take into account as a rule.
I vaguely recall some issue with Norwegian postal codes (I think), which were all 4 positions, except Oslo, which had 18 or so.
I'm positively sure that from the moment we started using the geographically correct ZIP codes for all of our own national addresses, quite a few people started complaining that their mail arrived too late. Turned out those people were living near a borderline between postal areas, and despite the fact that someone really lived in postal area, say, 1600, in reality his mail should be addressed to postal area 1610, because in reality it was that neighbouring postal area that actually served him, so sending his mail to his correct postal area would take that mail a couple of days longer to arrive, because of the unwanted intervention that was required in the correct postal office to forward it to the incorrect postal area ...
(We ended up registering those people with an address abroad in the country with ISO-code 'ZZ'.)
Unless you are going to do maths on the street numbers or zip / postal codes, you are just inviting future pain by storing them as numerics.
You might save a few bytes here and there, and maybe get a faster index, but what do you when US postal, or whatever other country you are dealing with, decides the introduce alphas into the codes?
The cost of disk space is going to be a lot cheaper than the cost of fixing it later on... y2k anybody?
Adding to what #Jonathan Leffler and #Paul Fisher have said
If you ever anticipate having postal addresses for Canada or Mexico added to your requirements, storing postal-code as a string is a must. Canada has alpha-numeric postal codes and I don't remember what Mexico's look like off the top of my head.
You should certainly consult "Is this a good way to model address information in a relational database", but your question is not a direct duplicate of that.
There are surely a lot of pre-existing answers (check out the example data models at DatabaseAnswers, for example). Many of the pre-existing answers are defective under some circumstances (not picking on DB Answers at all).
One major issue to consider is the scope of the addresses. If your database must deal with international addresses, you have to be more flexible than if you only have to deal with addresses in one country.
In my view, it is often (which does not mean always) sensible to both record the 'address label image' of the address and separately analyze the content. This allows you to deal with differences between the placement of postal codes, for example, between different countries. Sure, you can write an analyzer and a formatter that handle the eccentricities of different countries (for instance, US addresses have 2 or 3 lines; by contrast, British addresses can have considerably more; one address I write to periodically has 9 lines). But it can be easier to have the humans do the analysis and formatting and let the DBMS just store the data.
Ive found that listing all possible fields from smallest discrete unit to largest is the easiest way. Users will fill in the fields they see fit. My address table looks like this:
*********************************
Field Type
*********************************
address_id (PK) int
unit string
building string
street string
city string
region string
country string
address_code string
*********************************
Where's the "trade off" in storing the ZIP as a NUMBER or VARCHAR? That's just a choice -- it's not a trade off unless there are benefits to both and you have to give up some benefits to get others.
Unless the sum of zips has any meaning at all, Zips as number is not useful.
This might be an overkill, but if you need a solution that would work with multiple countries and you need to programmatically process parts of the address:
you could have country specific address handling using two tables: One generic table with 10 VARCHAR2 columns, 10 Number columns, another table which maps these fields to prompts and has a country column tying an address structure to a country.
If you ever have to verify an address or use it to process credit card payments, you'll at least need a little structure. A free-form block of text does not work very well for that.
Zip code is a common optional field for validating payment card transactions without using the whole address. So have a separate and generously sized field for that (at least 10 chars).
Inspired by Database Answers
Line1
Line2
Line3
City
Country_Province
PostalCode
CountryId
OtherDetails
At the moment, I'm developing an international ecommerce website.
It should cover almost all addresses in this world as shown below:
*****************************************************************
Type Field name Displayed name in your form
*****************************************************************
INT id (PK)
VARCHAR(100) building Apt, office, suite, etc. (Optional)
VARCHAR(100) street Street address
VARCHAR(100) city City
VARCHAR(100) state State, province or prefecture
VARCHAR(100) zip_code Zip code
VARCHAR(100) country Country
*****************************************************************
I would just put all the fields together in a large NVARCHAR(1000) field, with a textarea element for the user to enter the value for (unless you want to perform analysis on eg. zip codes). All those address line 1, address line 2, etc. inputs are just so annoying if you have an address that doesn't fit well with that format (and, you know, there are other countries than the US).

What is the "best" way to store international addresses in a database?

What is the "best" way to store international addresses in a database? Answer in the form of a schema and an explanation of the reasons why you chose to normalize (or not) the way you did. Also explain why you chose the type and length of each field.
Note: You decide what fields you think are necessary.
Plain freeform text.
Validating all the world's post/zip codes is too hard; a fixed list of countries is too politically sensitive; mandatory state/region/other administrative subdivision is just plain inappropriate (all too often I'm asked which county I live in--when I don't, because Greater London is not a county at all).
More to the point, it's simply unnecessary. Your application is highly unlikely to be modelling addresses in any serious way. If you want a postal address, ask for the postal address. Most people aren't so stupid as to put in something other than a postal address, and if they do, they can kiss their newly purchased item bye-bye.
The exception to this is if you're doing something that's naturally constrained to one country anyway. In this situation, you should ask for, say, the { postcode, house number } pair, which is enough to identify a postal address. I imagine you could achieve similar things with the extended zip code in the US.
In the past I've modeled forms that needed to be international after the ups/fedex shipping address forms on their websites (I figured if they don't know how to handle an international order we are all hosed). The fields they use can be used as reference for setting up your schema.
In general, you need to understand why you want an address. Is it for shipping/mailing? Then there is really only one requirement, have the country separate. The other lines are freeform, to be filled in by the user. The reason for this is the common forwarding strategy for mail : any incoming mail for a foreign country is forwarded without looking at the other address lines. Hence, the detailed information is parsed only by the mail sorter located in the country itself. Like the receiver, they'll be familiar with national conventions.
(UPS may bunch together some small European countries, e.. all the Low Countries are probably served from Belgium - the idea still holds.)
I think adding country/city and address text will be fine. country and city should be separate for reporting. Managers always ask for these kind of reports which you do not expect and I dont prefer running a LIKE query through a large database.
Not to give Facebook undue respect. However, the overall structure of the database seems to be overlooked in many web applications launching every day. Obviously I don't think there is a perfect solution that covers all the potential variables with address structure without some hard work. That said, combined with autocomplete Facebook manages to take location input data and eliminate a majority of their redundant entries. They do this by organizing their database well enough to provide autocomplete information in a low cost, low error way to the client in real time allowing them to more or less choose the correct location from an existing list.
I think the best solution is to access a third party database which contains your desired geographic scope and use it to initially seed your user location information. This will allow you to avoid doing the groudwork of creating your own. With any luck you can reduce the load on your server by allowing your new users to receive the correct autocomplete information directly off your third party supplier. Eventually you will be able to fill most autocomplete for location information such as city, country, etc. from information contained in your own database from user input data.
You need to provide a bit more details about how you are planning to use the data. For example, fields like City, State, Country can either be text in the single table, or be codes which are linked to a separate table with a Foreign Key.
Simplest would be
Address_Line_01 (Required, Non blank)
Address_Line_02
Address_Line_03
Landmark
City (Required)
Pin (Required)
Province_District
State (Required)
Country (Required)
All the above can be Text/Unicode with appropriate field lengths.
Phone Numbers as applicable.

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