Python users probably know data matching by the name “string matching”.
Excel users probably use the “v lookup” and the “fuzzy lookup” functions.
Business people will just tell you that there are too many duplicates and that they can’t find the same data in other business systems.
Almost every system has their own version of something like this but here are a few reasons you’ll probably want to use a purpose-built “industrial strength” data matching and entity resolution solution:
- Data matching and entity resolution are data sciences. It’s either a well-developed model or it may be an iterative approach until you get the right outputs for your specific use case; one that requires matching on multiple fields, allowing for mismatching data, and should have many more advanced configurations available for different challenges. You often need to set up some rules to massage the data before matching, and specifically to get better match results. Users normally review the results and tweak the ruleset, and the workflow, as needed.
- Data matching is where the rubber hits the road. This is the biggest unsolved problem for most data sets and use cases. This is one of the most common complaints from business users. This is one of the reasons why new systems are purchased. This is why reports are wrong. This is why companies implement master data management. This is one of those things that often has real-world consequences.
- Missing 15-30% of your matching records on 500 records is a relatively small number of missed matches. It might be tolerable depending on the use case. Plus you could also do it manually. But missing 15-30% of your matches on hundreds of thousands or millions of records, is a much bigger number. Marketers might not care. But wouldn’t this be a deal breaker for customer or patient data? What about fraud prevention? Higher value use cases usually require better solutions.
- Purpose built data matching solutions are much more effective and they’re also much easier to use. Especially the newer technologies designed for business users. These are no-code, point-and-click solutions that require very little training if any. That means anyone can do the work. The majority of the training is usually more solution-focused. We’ve dealt with all of the different use cases and we built the technology so we’ll show you the best approach to get the best outputs.
Match Data Pro multiuser solutions are also super flexible to work on-premise or in your own private cloud, or as a SaaS service, running jobs on-demand, scheduled, or by REST API. Our solutions are accessible wherever you need them from your browser, over WAN or LAN, on your desktop or mobile devices, through your own private network or using public internet. It’s your call.
And it’s not just data matching. These are data management solutions, ETL solutions, data cleansing solutions, and they’re affordable for just about every business, and they’re flexible enough for just about any data type. Plus, the Senzing Entity Resolution is built-in, allowing everyone access to world-class entity resolution, on-demand. Shoot us an email with any questions.
Author: Ben Cutler
Inquiries: bcutler@matchdatapro.com