Bringing data together
Enterprise data management enables companies to “know what they know.” But it doesn’t reveal insights outside the scope of an initial query. Bottom line? Up to now, as every organization knows, it’s been hard to find and access relevant contextual data.
Companies compete on data. And today more than ever they need a common way to govern and manage this core asset. That requires an integrated view combining critical metadata right across the data supply chain.
Accenture’s Universal Metadata Repository (UMR) changes all that. Using the same technology that underpins the
internet it provides a single logical view of the data supply chain to support:
- A single federated system: incorporating the views of many tools and allowing them to interoperate and exchange metadata across business and technical domains.
- A living system: machine learning augments and accelerates manual data management processes, automatically discovering data rules and metadata and dynamically updating them.
- Data rules enforcement: through dynamic queries that automatically detect discrepancies and generate implementation updates.
Because data is often held in separate tools, systems and locations and managed by separate groups, companies have experienced a disconnect between what they want from their data and their ability to deliver. That’s changed forever. The UMR makes connections in all the right places, making it easy to understand, trace and access data throughout the data supply chain and across multiple systems.
The UMR in action: Anti-money laundering
In a unique anti-money laundering (AML) deployment, the UMR is enabling banks to get the most value from their data and analytics investments in this key space. Implemented for an AML multi-tenant utility, the UMR helps consortium members track their data across multiple systems and transactions in a programmatic and transparent way. The UMR:
- automatically stores technical metadata on data linked to customers, accounts, transaction, transfers and alerts generated when transactions/transfers could be money-laundering activities
- provides a data catalog with discovery capabilities to search for specific entities.
- maps technical data to business metadata to provide business context to all physical data entities
- shows end-to-end lineage, from business terms to scenarios/models and underlying data tables, all the way back to the original source files.