Your Deduplication Processes May be Leaving You at Risk for GDPR Fines

Melissa Team | Article, Data Audit, Data Matching, Data Quality, Duplicate Elimination, Fuzzy Matching, GDPR, Global Business, Global Data Quality, Identity Resolution | , , , , , , , , ,

Once-trusted fuzzy matching algorithms may be leaving your organization vulnerable to hefty GDPR fines. The balancing act of false-positives and false-negatives in single customer view (SCV) systems used to favor the false-negative side, with near negligible error results. However, the standard of that balancing act has now been redefined by the GDPR regulations. Find out how GDPR has moved the “match” goalposts, how to test your SCV platform, and what you need to do to keep your organization GDPR compliant.… 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

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

How to Get Complete Control Over Your Data Stewardship Processes

Blog Administrator | Data Matching, Matching | , ,

Matchbook is a SaaS solution that provides accurate and
complete control over your data stewardship processes.

With a fully functional user dashboard, Matchbook
enables data stewards to:


View queue statistics to see how much data has been processed
and the status of their matches.


See at-a-glance how many of the processed company
records were low confidence or had no matches at all and then compare
that to low confidence match patterns. 
Read More

Record Matching Made Easy with MatchUp Web Service

Blog Administrator | Data Governance, Data Integration, Data Management, Data Matching, Data Quality, Data Quality Components for SSIS, Data Steward, Data Warehouse, Duplicate Elimination, Fuzzy Matching, Golden Record, Householding, Identity Resolution, Record Linkage, SQL Server Integration Services, SSIS, Survivorship | , , , , , , ,

MatchUp®,
Melissa’s solution to identify and eliminate duplicate records, is now
available as a web service for batch processes, fulfilling one of most frequent
requests from our customers – accurate database matching without maintaining
and linking to libraries, or shelling out to the necessary locally-hosted data
files.

 

Now
you can integrate MatchUp into any aspect of your network that can communicate
with our secure servers using common protocols like XML, JSON, REST or SOAP.
Read More