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Fuzzy Matching 101: Cleaning and Linking Messy Data

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...

Data Cleansing Techniques for Redundancies

Dealing with duplicate data requires a strategy to deal with inconsistent data. The first step would be to standardize addresses with data matching software.  Secondly,

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