Magical matching predefined magical data matching rule types empower you to easily match customers, suppliers, products, places etc based on similar values within a field or set of fields.


Organisations create data about Customers, Products, Places etc in many different systems of record. They need a single place to be able to count their unique customers, suppliers, products, places etc. To enable this similar records in each of the disparate systems need to be matched to identify if they are the same.

Magical Matching allows Data Magicians to easily match this data when they create their Change Rules.


The challenge is there is often no single common field across these systems of record, making it difficult to determine if customer A in system 1 is the same as customer A in system 2.

  • Exact matching on a field, for example Customer name, does not take into consideration names that are misspelt or are abbreviated, for example Robert and Bob.

  • Matching on multiple fields, for example name, address and date of birth, are needed to increase the accuracy of matches and reduce the number of over matches.

Solution uses augmented analytics, to recommend when things you care about are the same, so you can easily match them to create a single view of your core business data.

Quote from ADI

Matching your customer data from multiple source systems to create a golden record shouldn’t be difficult, so we created rule types in which automate the matching for our customers using our augmented analytics capabilities, while still leaving them the ability to tweak the matching rules to meet their specific use cases.

No longer do they have to buy a third party Master Data Management solution so create their golden customer records and single view of customers.

Lets go

To get started you simply create a new rule, select the matching rule type from the drop down list, select the detail fields for the concept that you are wanting to create a golden record for, and then automagically does the rest.

Customer Quote

We have multiple systems where we create customer records, including our online store and our POS system. We could never get a accurate count of how many customers we had and we were being quoted hundreds of thousands of dollars to buy and implement a master data management solution to enable us to do this.

With a simple click on the matching rule type in we get our customers automatically matched for us, and we are amazed at the accuracy of the matching that it delivers.

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