[WEBINAR] How to Seamlessly Cleanse and Enrich Your Customer Data

Blog Administrator | Address Quality, Address Validation, Address Verification, Analyzing Data, Analyzing Data Quality, Data Enrichment, Data Management, Data Migration, Data Quality | , , , , ,

Your contact data is perhaps your organization’s most valuable asset. But how good is your data?

At least 25 percent of most companies’ data is probably inaccurate, according to industry analyst Gartner. Bad data is likely caused by the fact that contact data is always in flux – as people move, get married, retire or pass away.… Read More

Melissa Data Adds Real-Time Global Address Verification and Auto-Completion to CRM and Ecommerce Data Quality Tool

Blog Administrator | Address Correction, Address Quality, Address Validation, Address Verification, Analyzing Data, Analyzing Data Quality, CRM, Data Quality, Global Data Quality, International Address Verification, Press Release | , , , , , , ,

Express Entry® Web Service Enables Fast, Accurate Data with Reduced Keystrokes; Now Verifies Address Information for More Than 240 Countries/Territories

 

Rancho Santa Margarita, CALIF – May 14, 2014 – Melissa Data, a leading provider of contact data quality and integration solutions, today announced global address verification in Express Entry, the company’s address auto-completion tool designed to eliminate bad data at its source.… Read More

Big Data May Turn Data Quality on Its Head

Blog Administrator | Address Quality, Analyzing Data, Analyzing Data Quality, Big Data, Data Quality | , , ,

By Elliot King

Big data has emerged as a big issue for organizations both large and small. The idea of being able to capture and assess huge amounts of data, as well as use a vast new array of data types including unstructured and semi-structured data, has led to a kind of religious fervor.
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Data Quality Management Mistakes to Avoid

Blog Administrator | Address Quality, Analyzing Data, Analyzing Data Quality, Data Cleansing, Data Management, Data Quality | , , , , ,

By Elliot King

Everyone wants high quality data and it seems that goal should not be so hard to achieve. The need seems obvious and there are plenty of good tools that can be put to work in the effort. Unfortunately, it is just not that easy to set up a successful, ongoing data quality program.
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