EY refers to the global organization, and may refer to one or more, of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity. Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients.
3. Data catalog and metadata management
Data, being a critical business asset that is leveraged for varied purposes, requires effective cataloging. A data catalog serves as a centralized repository that indexes and organizes metadata, providing a comprehensive view of an organization's data assets. Metadata management ensures that data definitions and lineage are accurately documented, fostering data quality and compliance with regulatory standards.
This centralized catalog enables business visibility and facilitates data mobilization for effective decision-making. Global Capability Centers (GCCs) are best placed for managing this data catalog and ensuring that data is accessible throughout the organization.
4. Automation and technology enablement
As organizations handle increasingly large amounts of data and metadata, leveraging automation and digitalization becomes crucial for data governance. GCCs, equipped with Automation CoEs, could play a key role in implementing system rules for data governance.
Several GCCs have been leveraging leading applications, such as Collibra and Atlan, to accelerate governance processes.
A multinational enterprise GCC, for example, has been responsible for the global implementation and management of the Collibra application, while another GCC is responsible for creating derivation rules that auto-predict and populate fields at the time of master data request creation.
GCCs can also leverage their capabilities to enhance the governance process through artificial intelligence. For example, an AI engine can identify invalid data attributes based on defined rules as well as internal inconsistencies. It can then extract information from trusted sources such as emails, purchase orders, invoices, online OEM catalogs, etc., to predict the attribute and enrich the data element. AI can also be used to scan source systems and applications to discover relationships and map the data lineage and data profiling.