Question

What are the different types of Cleanser or Data Quality ( DQ ) Functions available Out-of-box in Reltio?

Answer

Reltio provides standardization functions out-of-the-box for common attributes and operates in real-time on the field when data is modified either through a data load or data entry via the UI.

Different Out-of-box Cleanser supported currently -

1) Full Name Cleanser
The full name cleanser generates full names as defined and adds an attribute to the ReltioCleanser crosswalk.

2) Pattern Based Cleanser
The pattern based cleanser generates the output text as defined and adds an attribute to the ReltioCleanser crosswalk.

3) Initials Cleanser
The initials cleanser generates initials by extracting the first letter of each word from the Name attribute and adds an attribute to the ReltioCleanser crosswalk.

4) Address Cleanser
Address cleansing is the collective process of standardizing, correcting, and then validating an address.

5) Phone Cleanser
This cleanser takes the phone number, country code, and type and produces many attributes with the ReltioCleanser crosswalk, as per the output mapping.

6) Email Cleanser
This cleanser takes the email, its type, rank, and activeness, and produces many attributes with the ReltioCleanser crosswalk, as per the output mapping.

7) String Cleanser

This cleanser alters the given text based on the specified options. It also adds an attribute with the ReltioCleanser crosswalk, based on the output mapping. 

8) HTTP Cleanse Function
The HTTP cleanse function is based on REST API.

The REST API request returns results as a JSON with a single object. All properties of the object are treated as a result of cleanse.

9) S3 File Cleanser

The S3 file cleanse function is based on the properties file stored in the S3 file storage.

This cleanser works as a string replacement function on words and regular expressions. 

References

https://docs.reltio.com/datacleanse/cleanselibrary.html