Automated metadata capture and active monitoring of data assets underpins the capabilities of Metonomy software in the support of enterprise analytics governance.

Complex data architectures require a range of controls to monitor and regulate data as it flows through an organisation to the point of use or consumption. Metadata management is a cornerstone to making data fabric or mesh viable.

Improved control is achieved through the identification of anomalies across disparate applications, tracking usage over time and determining the degree of similarity and potential duplication between elements.

The use of software in conjunction with processes, policies and people with specific skills provides a foundation for improved data governance.

Manual analysis of analytics applications is often time-consuming, frequently repetitive and always inefficient. Automation enables data teams to be more effective in optimising existing applications and more productive when migrating to new.

Enriching asset metadata with annotations relating to purpose, ownership or other categories and types provides context to output. Context is necessary for people to be able to understand the nature of the information they are accessing and to use it appropriately.