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Featured Resources

Fuzzy Matching 101: Cleaning and Linking Messy Data
fuzzy matching

In this blog, we will take an in-depth look at fuzzy matching, the go-to approach for data deduplication and record linkage. We will cover: What is Fuzzy Matching? Why Do Businesses Need Fuzzy Matching?...

In this blog, we will take an in-depth look at fuzzy matching, the go-to approach for data deduplication and record linkage. We will cover: What is Fuzzy Matching? Why Do Businesses Need Fuzzy Matching?...

In this blog, we will take an in-depth look at fuzzy matching, the go-to approach for data deduplication and record linkage. We will cover: What is Fuzzy Matching? Why Do Businesses Need Fuzzy Matching?...

Data Quality Testing – A Quick Checklist to Measure and Improve Data Quality

Don't wait for a data migration event to test your data quality. Perform data quality tests now before it gets too late. Here's everything you need to know!...

Don't wait for a data migration event to test your data quality. Perform data quality tests now before it gets too late. Here's everything you need to know!...

Don't wait for a data migration event to test your data quality. Perform data quality tests now before it gets too late. Here's everything you need to know!...

What is Data Accuracy, Why it Matters and How Companies Can Ensure They Have Accurate Data.

Inaccurate data has real-world implications across industries. In law enforcement, inaccurate data could mean booking the wrong person for a crime. In healthcare, it could mean making a fatal mistake in...

Inaccurate data has real-world implications across industries. In law enforcement, inaccurate data could mean booking the wrong person for a crime. In healthcare, it could mean making a fatal mistake in...

Inaccurate data has real-world implications across industries. In law enforcement, inaccurate data could mean booking the wrong person for a crime. In healthcare, it could mean making a fatal mistake in...

Merge and survivorship with DME

Merge Purge DME process of combining multiple sources of data while simultaneously removing duplicates and bad records from the data source.

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