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Firstly the "What"
Cleaning a database is done to:
Remove duplicate records Ensure your data is consistently formatted Correct data that is obviously wrong e.g. wrong postcode for a known suburb Find other records that are likely to be the same (more on this later)So "Why" would you want to do that?
To explain why Authentic Connor McGovern Jersey , I am going to use the example of a customer database, but the principles apply to other types of data also.
Have you ever received a marketing message catalogue in the mail twice or more times? I receive multiple copies of such communications regularly, and I don't always get around to telling the sender of their mistake. This can:
be interpretted as sloppiness on the part of the organisation undo your efforts to target personalise - any attempt on the organisation's part to "personalise" and "target" the message is wasted, because the recipient knows immediately that it was a mindless distribution of information using a database. waste $$$! Everytime you send a communication twice to the one person or household, you have most likely just wasted some of your hard-earned funds.
In addition Authentic Trysten Hill Jersey , cleaning your data, will help you to analyse your data more accurately. For instance, you will know the real number of contacts and perhaps how they are geographically distributed, rather than the distorted figures that can be derived from analysing a corrupted database.
It's not a crime! In fact it is very easy for your data to get in a state that requires cleaning. For example, when a client changes their address Authentic Taco Charlton Jersey , your staff might update the suburb but forget to put in the new postcode. Or, an existing client returns to your organisation several years later, without informing new staff that they are an existing client, and if you don't have the appropriate keys on your database preventing duplicates, the client could be set up again as another customer with the same or similar details.
Having documented processes that your staff can use as a checklist Authentic Michael Gallup Jersey , and appropriate unique keys on your database fields, will go some way to ensuring that your data is kept clean, but incorrect data will never be prevented.
"How" then, do you efficiently clean your database?
Fixing incorrect information such as the postcode matching the suburb is usually done by comparing each record to the correct values in another table. For example, to correct all the postcodes in your data Authentic Leighton Vander Esch Jersey , assuming that the suburb entered is correct, you would write SQL code that would compare the postcode of your record against a table of postcode + suburb + state that you may have obtained from Australia Post. Such a process would likely generate a list of records where the suburb was not found, requiring you to manually investigate and correct the data.
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