Practice For Best Mac Address
Are there any best practices (or even standards) to store addresses in a consistent and comprehensive way in a database? To be more specific, I believe at this stage that there are two cases for address storage: • you just need to associate an address to a person, a building or any item (the most common case).
Then a flat table with text columns (address1, address2, zip, city) is probably enough. This is not the case I'm interested in. • you want to run statistics on your addresses: how many items in a specific street, or city. Then you want to avoid misspellings of any sorts, and ensure consistency.
My question is about best practices in this specific case: what are the best ways to model a consistent address database? A country specific design/solution would be an excellent start. ANSWER: There does not seem to exist a perfect answer to this question yet, but: •, as, is the closest thing to a global standard that popped up. It seems to be quite an overkill though, and I am not sure many people would want to implement it in their database. • To start one's own design (for a specific country), to the (UPU) site is a very good starting point.
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• As for France, there is a norm (non official, but de facto standard) for addresses, which bears the lovely name of (french only), and has to be paid for. The description for France is based on this norm. • I happened to find the equivalent norm for Sweden:.
• At European level, some effort has been made, resulting in the norm EN 14142-1. It is obtainable via. I basically see 2 choices if you want consistency: • Data cleansing • Basic data table look ups Ad 1. I work with the SAS System, and SAS Institute offers a tool for data cleansing - this basically performs some checks and validations on your data, and suggests that 'Abram Lincoln Road' and 'Abraham Lincoln Road' be merged into the same street. I also think it draws on national data bases containing city-postal code matches and so on. You build up a multiple choice list (ie basic data), and people adding new entries pick from existing entries in your basic data.
In your fact table, you store keys to street names instead of the street names themselves. If you detect a spelling error, you just correct it in your basic data, and all instances are corrected with it, through the key relation. Note that these options don't rule out each other, you can use both approaches at the same time.