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Data Cleansing Terms Clarification

Folks,

Another question and thanks again to all those that have been helpful so far.

In a data flow that I am building I have both customer information and address information. I plan on running my data both through an English base data cleanse and a Canada address cleanse.

I notice that there are many options for the same output field. The difference being the generated field class. I am confused as to what is the difference between Parsed and Standardized in regards to the base data cleanse.

Also I am confused that there are extra types such as alternate or none. Also in dealing with address cleansing there are other items such as generated field category and generated field addrclass which also seem to have an impact on the data that is output from these transforms.

I would like my transforms to correct error data and also if it is possible add items such as city or province when they are missing based on the postal code which is there for example. I have gone through both the designer guide and reference guide in regards to these terms, it has left me more confused than anything.

Which way of implementing this would be the best.

Thanks in advance,

Bill

Edited by: William Grdovich on Oct 5, 2010 4:13 PM

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    Posted on Oct 06, 2010 at 05:53 PM

    Bill,

    I notice that there are many options for the same output field. The difference being the generated field class. I am confused as to what is the difference between Parsed and Standardized in regards to the base data cleanse.

    Parsed means that the address has been separated into its components (house numnber, street name, city, etc). Standardized means that the address has been parsed, and each component value has been corrected, updated or enhanced.

    Also I am confused that there are extra types such as alternate or none.

    An altenate type means that an alternate value is available. For example, in New York City, 6th Ave (the official name) is also known as Avenue of the Americas (the alternate name). If a field has type 'None', it means that there is only one type associated with this field.

    Also in dealing with address cleansing there are other items such as generated field category and generated field addrclass which also seem to have an impact on the data that is output from these transforms.

    A description of the field category columns is provided in the SAP Business Objects Data Services Reference Guide, Data Quality Fields, Global Address Cleanse fields.

    I would like my transforms to correct error data and also if it is possible add items such as city or province when they are missing based on the postal code which is there for example.

    Use Generated Field Class 'Best', Generated Field Category 'Component, Generated Field Addrclass 'Official'. If your selected output field has Generated Field Class 'None' then use Generated Field Category 'Standardized'.

    Paul

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    • Bill,

      The generated field class 'Correct' is used in the US Regulatory Addres Cleanse (URAC) transform but not the GLobal Address Cleanse (GAC) transform, which is what Canada Address Cleanse is built on.

      Regarding the input field errors, address cleanse expects certain input fields to be mapped. For example, if you map an input address field the you should also map a locatity and region or a postcode or all three components.

      regarding best practice, you are correct. I meant to say use Addrclass Delivery for best practice. You would use Official if you want to always use the offical address component value from the postal address lookup tables.

      Paul

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