Netrics HD

Recently a friend of mine asked exactly how I was planning to blog about both business and technology. He pointed out the well known (but flawed) theory that says business folks are bored with technical details and technical folks are bored with business details.I love both business and technology and am particularly fond of their intersection!

I hope to offer meaningful insight on both subjects and, of course, how they need each other.

Alas, this core matching problem is not limited to people names… it basically applies to anything and everything that is stored in your DBMS. For example, product names, vendor names, claims, applications, and the list goes on and on. No data is immune.

This fundamental data matching limitation then spreads to every application built on top of a DBMS.

So this seemingly small functional limitation – the inability to intelligently compare and match imperfect data – can, at best, render enterprise applications ineffective and wrong, or worse still, result in their failure to perform as required.

Very scary… but fear not, all is not lost! More details on this is on the way… mixed in with other commentary of course.

We often get asked what creates the business-data problems that Netrics solves… Why is database data not perfect? How can databases make mistakes?

These business problems arise because of computers’ well-defined limitations – after all, they’re just fancy calculators. Calculators that can perform billions of operations every second – quite amazing when you think about it. Built into every CPU is the capability to compare data – but these data comparisons are limited to “equals” or “not equals” – that’s all.

These same limitations propagate up to the applications (i.e. databases) that run on these CPUs. So, if you ask any commercially available DBMS (e.g., Oracle, IBM DB2, MS SQLServer, MySQL, Cache, etc) to retrieve a record where the last name is “Damianakis” then that’s exactly what it’s going to do.

But what happens if “Damianakis” is actually in the database as “Damanakos” and also as “Dananakis? Easy, the DBMS will find neither - at least not with built-in database operators. Someone needs to build an abstraction layer that uses the built-in database operators to address this issue.

And thus the can of worms is opened…

Finally! I’m excited about the launch of our new blog. So, what’s this blog all about? Well, here at Netrics we’re passionate about the business and technology of data matching. An esoteric topic you might think, but as we’ll explore over the coming blogs-to-be, a technology that’s mission-critical for virtually every IT solution deployment.

The goal of this blog is to educate and evangelize while offering a “high-definition” view of data matching. This means we won’t sweep details under the rug, or obscure them with marketing-speak – we feel it’s important to see and understand how data matching works and the broad impact is has on IT solutions that businesses depend on.

I’ll certainly get ideas, suggestions and help from everyone here at Netrics… Here is a partial list of topics that I’ll cover in upcoming posts:

• how does inferior matching performance adversely affect a company’s bottom line?
• real-world examples of organizations’ failures to make effective use of structured data due to matching issues, and the impact of these failures on the ability to conduct business
• how ineffective data matching hampers organizational compliance efforts, resulting in increased regulatory issues with government agencies
• why is real-time error-tolerant matching computationally expensive?
• what is deterministic matching? what is probabilistic matching? how are they different?

And of course, I’ll look to you, the readers, for comments, feedback and topics of interest. I’m very excited to have a medium to talk about these mission-critical business problems and the innovative mathematics that Netrics developed to solve them.