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The DQ Dictionary

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Socrates said, “The beginning of wisdom is the definition of terms.” There are many terms that fall under Data Quality, and it can get confusing. Was that validating or authenticating my data? Are you Migrating or Integrating data?  

We decided in this article to explain the terms we commonly use at DQ Global as well as looking at the difference between some words that we’ve often heard mixed up. To help you all achieve Data Quality Wisdom.  


Validate, Verify or Authenticate 

Validate, Verify and Authenticate, whilst these are very similar there are some fundamental differences in their meanings. To make it simple to understand we will break it down into each word. 

Validate – Validating data means syntactically validating values as being of the correct format. This means ensuring they look correct, for example someone’s address following the correct format of having a house number and a postcode. 

Verify – Verifying data is checking to see if the values or record match the proxy of the real world entity they are supposed to represent. Carrying on with the address example, this would be reading the yellow pages to check the address matches the name given. 

Authenticate – Authentication checks to see if the value is present at the time of checking. If we look at the address scenario again this would essentially be going to the address we are told and knocking on the door to see if the person actually lives there. 


Single customer view 

The single customer view can also be called things such as “single source of truth” or the “golden record.” In simple terms a single customer view means storing all the data about a customer in one record which can be accessed from a centralised location. This is beneficial for your team as it avoids duplicate contact information and ensure the richest data of your customer/client. 

Data Migration and Integration 

Data Integration and Migration follow common processes and have similar features however in practice they are actually rather different. 

Data migration – involves moving data from one system to another, in one direction. Migration is a one-time process. Once data has been migrated, it is not moved back, and the migration is not repeated. 

Data integration – is the meshing of two systems that do not already talk to each other. Integration is repeatable, too. Often, it means creating a two-way link so that users see a more complete picture of a record or contact. Integration is commonly used in cloud applications: for example, your Customer Relationship Management (CRM) system and your accounting tool may be linked so that you can see invoices, contact details and payment history in both 


Automation describes the process of converting a manual sequence of steps into a sequence that is triggered automatically by a computer. 

Why bother with automation? Businesses often struggle with repeated manual tasks: they tend to be dull for employees, and they drain teams of enthusiasm and resources. Repetitive tasks are a prime source of data quality problems: data is often submitted in an incomplete state, with errors, with inaccurate or invalid data in place. 

Often, manual processes have been adopted because the software in use is too old to be compatible with anything else, yet business automation can help old software ‘talk’ to new applications. 

By using process automation, many data quality challenges are overcome. It makes processing much faster. The automation can also be run unattended at a time or event of your choice. 


Written by Conor Doyle

Conor has been at DQ Global for the past 3 years. He now leads the sales team to maintain and build client and business partner relationships. Throughout, he has gained extensive knowledge and experience surrounding Data Quality and established himself as an industry expert.