Data integrity relates to the accuracy and consistency of data in software systems. For CRM in particular, a big part of data integrity analysis looks at whether the data is required, whether the data is consistent with the values it should contain, and whether the data type matches the values that are stored in the field. For example, a "date" value should not be stored in a text field.

Data augmentation tools allow businesses to fill in the gaps on missing information to create richer customer profiles. Information like recent social posts, phone numbers, and company-related new releases are just a few of the data points collected by data augmentation solutions. Many CRMs offer these capabilities built-in to their systems or have add-on capabilities to enable data enhancement.

Data deduplication is the act of eliminating multiple copies of repeating data. Removing duplicate data improves storage capacity and lays the groundwork for more accurate reporting and analytics. Deduplication is a key aspect of data cleaning.

A data dictionary catalogues which pieces of information you have, where that information is stored, when the data was created, how it's being used, and when it's no longer valid. Simply put, a data dictionary acts as a glossary of basic insights about your data.

The US Postal Service wants you to always send and ship to the correct address, so they provide a service that lets you identify change of address requests. Change of address management uses that service to continually keep your addresses in sync with the postal service. This is true for many countries across the world.

Master Data Management defines a set of rules for organizing, creating, and using your data. These governance guidelines are far more in-depth than a data dictionary as they define rules for how data can be used, when users are allowed to create data, when users can start using certain pieces of data, and when data must be disposed of.