Data quality involves ensuring the accuracy, timeliness, completeness, and consistency of the data used by an organization so that the data is fit for use. We support the data quality initiatives by providing the capabilities to prepare matching and consolidation rules to fix data anomalies and add more context in your enterprise data assets. Matching is the process of identifying records related to each other in some way that is significant for your purposes. For example, if you are trying to eliminate redundant information from your customer data, you may want to identify duplicate records for the same customer; or, if you are trying to eliminate duplicate marketing pieces going to the same address, you may want to identify records of customers that live in the same household.
A match rule defines the criteria that are used to determine if one record matches another. Match rules specify the fields to compare, how to compare the fields and a hierarchy of comparisons for complex matching rules. A consolidation rule is a Best of Breed rule which consolidates duplicate records by selecting the best data in a duplicate record collection and creating a new consolidated record using the best data. You define the rules that select records to consolidate.
How Spectrum Discovery helps you prepare rules
The Prepare module on the Discovery page allows you to create, modify, delete, and publish the rules and match keys. It lists all the rules and match keys built for the sources in a dashboard view, a one-stop-shop for all your rules management. You can create the rules manually or by machine learning based solutions where the matching algorithms and thresholds are learned automatically based on the user's matching scenario. Spectrum Discovery helps you to build these rules and allows you to associate them with the Business Glossary entities.