Abstract

A key difference of the Data Vault model, as compared to other modeling techniques, is that it allows bad data into the Data Vault and applies business rules after loading the Data Vault. This chapter demonstrates how to deal with bad data in the Data Vault (for example, de-duplicating records with same-as links) and other examples. Another interesting topic is the application of Data Quality Services (DQS) to the Data Vault. DQS is a component of Microsoft SQL Server used for data cleansing. The authors discuss how to define domains in DQS, document them, and apply them to the data in the Data Vault.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.