Data discovery is emerging as an essential discipline in the data management space as explained in the post The Role of Data Discovery in Data Management.
In a data hub encompassing master data, reference data, critical application data and more, data discovery can play a significant role in the continuous improvement of data quality and how data is governed, managed and measured along with an ever evolving business model and new data driven services.
Data discovery serves as the weapon used when exploring the as-is data landscape at your organization with the aim of building a data hub that reflects your data model and data portfolio. As the data maturity is continuously improved reflected in step-by-step maturing to-be states, data discovery can be used when increasing the data hub scope by encompassing more data sources, when new data driven services are introduced and the business model is enhanced as part of a digital transformation.
In that way data discovery is an indispensable node in maturing the data supply chain and the continuously data quality improvement cycle that must underpin your digital transformation course.
Learn more about the data discovery capability in a data hub context in the Semarchy whitepaper authored by me and titled Intelligent Data Hub: -Taking MDM to the Next Level.
Liliendahl on Data Quality 