[WEBINAR] Integrating Matching in SQL Server with MatchUp

Cassidy Littleton | Data Matching, Deduping, Matching, SQL Server Integration Services | , ,

Does this sound familiar? You just removed the duplicate data from your database. You’re ready to add real-time or scheduled inserts but you don’t want to go through the hassle of re-processing every record. Now, you don’t have to. Melissa’s MatchUp Object gives you the ability to perform the same advanced matching as batch processing through a set of CLR functions called directly from SQL Server and flag records already in your database.… Read More

Google Gets Nailed for GDPR

Author | Data Cleansing, Duplicate Elimination, GDPR | , , , , , ,

Today is Data Privacy Day! A good day to remind our readers about GDPR data privacy regulations and those pesky goalposts.

If you haven’t been keeping up, the GDPR hammer is coming down hard and fast on tech giants like Google, who was recently hit with a fine totaling 50 million Euros (about $57,192,500) by France’s data protection regulator CNIL. Anyone familiar with Google’s omnipresence in the digital arena and $111 billion in earnings will immediately notice that the fine, while large, is a softball in comparison with the data protection’s capacity to impose mind boggling fines – up to 4% of global annual revenue.… Read More

Tips & Tricks for Global MatchUp Matching Strategies

Blog Administrator | Address Verification, Matching, Tips & Solutions | , , , , ,

 

by Tim Sidor, Data Quality Analyst

In
the past we’ve discussed implementing different matching strategies based on how
you would like your records grouped. For example. By “Address”? or by “Name and
Address”. The former would match ‘John’ and ‘Mary Smith’ at the same household,
whereas the latter would identify them as unique
entities.

 

For
Global processing, even after determining and selecting a general strategy,
‘Address’ for example, it might still require knowing the expected address
formats of the source data that needs to be compared and thus reevaluate the
logic.
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Matchcode Caveats – How to Solve Them

Blog Administrator | Matching | , , , , ,

By Tim Sidor, Data Quality Analyst

“The more advanced I make my matchcode, the more duplicates I’ll
identify.”

This is an
assumption – true or false – that many of our new users to MatchUp make, but
often leads to false dupes, no dupes, or a process that seems to run forever.

“Why?”

Adding more
columns of conditions, can be looked at as ‘just adding more ways to return
more duplicates.’
Read More