Data Quality Tool for Data Warehousing
Data Warehousing and Its Major Data Quality Challenge
The problem is – 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”?
Most likely your data warehousing needs involve a data quality tool able to perform consistent entity resolution. Preferably something you can integrate into your data architecture without a huge headache.
A data mart or warehouse should help you work more efficiently and draw deeper, more accurate insights. Messy, fragmented records undermine all of that.
The best way forward is to map 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 relationships between records, you can easily feed them into your existing ETL tool or data mart.
Discover Our Data Management Capabilities
Visit these pages to understand what we do, how we do it, and whether it matches your current needs.
Problems We Solve
What can be achieved thanks to RecordLinker, general use cases.
Feature List
Our full list of capabilities, quality-of-life and collaboration features.
