•1 min read•from Towards Data Science
Avoiding Entity Key Drift in a Data Lake: Step 2, When Fuzzy Matching Stops Working
I built a matcher meant to finish the cleanup that normalization left behind. Testing it against real data showed that no version of it could be made safe. What follows is the architecture that was left once the matcher was set aside.
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Tagged with
#Entity Key Drift
#Data Lake
#Fuzzy Matching
#Normalization
#Matcher
#Data Cleanup
#Architecture
#Real Data
#Data Science
#Towards Data Science
#Data Quality
#Data Integration
#Data Governance
#Version Control
#Testing
#Safety
#Cleanup
#Data Management
#Data Transformation
#Data Integrity