How can GCCs help organizations unlock the power of data?

Today’s business enterprises are operating in a dynamic environment, driven by data. Big data has transformed how businesses operate and compete by providing a wealth of information for decision making. While the primary focus of organizations has been on data science and business intelligence, the quality of the data being analyzed could, in fact, be the most crucial factor. The rather subtle maxim “garbage in, garbage out” is applicable to any data analysis exercise. As data science becomes more important in business operations, leaders would need to prioritize data governance. 

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.

Data quality improvement is a comprehensive task which requires support from multiple stakeholders across regions as well as a detailed understanding of the underlying data. This is where GCCs are playing a key role, acting as pivots for data quality improvement. A GCC can, for example, perform regular data audits to assess the overall data quality across data types and co-ordinate with different business data owners to resolve issues and improve data quality. On the other hand, GCCs can also take up independent data enrichment and cleansing exercises, leveraging their specialized domain knowledge to plug holes in historical datasets.