RecordLinker

Analytics for Data Marts and Warehouses

We were tired of hearing the same tam-dam-dam soundtrack on each SaaS video we click. So here is the silent one for you – no sound, just great content about how our Machine Learning saves you time. Enjoy.

Building a data mart or warehouse is about much more than just moving all your information into a single database. Your data is likely coming from different systems, and in most cases there are inconsistencies in the way product codes, company names, or loss causes etc. are named across each of those source systems.

What happens when records that reference “General Liability” enter your database but can’t harmonize with entries that reference “GL”?

A data mart or warehouse should help you work more efficiently and draw deeper, more accurate insights. Messy, fragmented records undermine all of that. In other words, you’ll find yourself still dealing with apples and oranges – even if they’re all finally sitting in the same fruit bowl!

The best way forward is to link all your reference data to a canonical record set. RecordLinker helps you do just that, using a system that’s quick, user-friendly, and doesn’t derail your data management workflow. Once we’ve sorted out your linkages, you can easily feed them into your existing ETL tool or data mart.

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