Data Matching Guide Vol. 1

Understanding Why Traditional Matching Processes Fail

Whitepaper – “The Definitive Guide to Customer Data Matching Volume 1” – Understanding why traditional matching processes fail

This eBook by Rob Heidenreich – 360Science CEO, is the first in a two-part series exploring customer data matching processes, algorithms, their purpose, use, and more importantly – their limitations. Ultimately we uncover the pitfalls and challenges of working with conventional matching algorithms in customer data applications, and why ‘traditional matching’ processes fail.

It was written to help both data practitioners and executive stakeholders have a conversation on customer data unification by providing them with a common language understanding of the complex technical challenges of data matching. It’s not a doctoral thesis. It simply provides an easy to read understanding of the complex data science behind customer data matching.

Warning! Contains information that may leave even the most experienced Data Scientists and Data Analysts #mindblown!

To better understand what ‘an advanced customer data matching engine looks like’ – I would encourage you to read Volume 2 of the Definitive Guide to Customer Data Matching, as it more thoroughly details the unique capabilities of the 360Science AI Matching Engine.

 

Read Whitepaper