The term ‘data fabric’ was first coined by Forrester analyst Noel Yuhanna in a 2016 report. It has been widely adopted by vendors and other analyst firms in the interim. But while the name might be new, the objective behind it isn’t: an architecture that includes all forms of analytical data for any type of analysis that can be accessed and shared seamlessly across the entire enterprise.
A data fabric provides a better way to handle enterprise data, giving controlled access to data and separating it from the applications that create it. This is designed to give data owners greater control and make it easier to share data with collaborators.
According to Gartner, there are four key pillars in a data fabric architecture:
- The data fabric must collect and analyze all forms of metadata.
- It must convert passive metadata to active metadata.
- It must create and curate knowledge graphs.
- It must have a robust data integration backbone that supports all types of data users.