DataVerse

Governing Data Quality
as the Data Moves

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Global IDs DataVerse

Data Quality professionals often struggle to ensure that their data quality policies are consistently applied firmwide.

What if companies had the ability to enforce these policies throughout the data lifecycle?

The Global IDs next generation DataVerse solution allows business users to enforce data policies throughout the enterprise using a pioneering user interface which:

DataVerse changes the game, providing seamless navigation across complex data structures without losing context, and dramatically improving user productivity.

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DataVerse Transforming How Data is Visualized

Data Lineage flows can be large, complex and difficult to visualize given the limited real estate available on a desktop, laptop or tablet. DataVerse resolves the limited real estate constraint by giving data professionals a holistic view of the entire lineage flow. Application teams can use the high-level view to identify areas of interest and then zoom in to trace the record details without switching screens and losing context.

DataVerse allows users to search for and select individual records to see how the record flows across the data landscape. This is useful, for example, to verify the source of critical data elements and when troubleshooting dropped records.

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Consistent Data Policy Enforcement across the Enterprise

Master Data and Reference Data teams can use DataVerse to understand all dependent applications that are consuming the master and reference data. Additionally, DataVerse detects and alerts users when data policy violations are introduced as the data moves downstream. DataVerse allows the same Data Quality policies used in master data and reference data systems of record to be consistently enforced in each downstream table.

Visualize Data Transformations

Violations to data policies may appear when the data is transformed. DataVerse is unique in the way it alerts users when transformations exist between source and target tables. Not only can a user pinpoint where a data transformation occurs, the software also allows users to drill in to visualize:

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Reconcile Record Movement

DataVerse illustrates each hop the data makes as it moves from table to table through its lifecycle. Each hop introduces opportunities for data policy violations to appear. These violations may be caused by faulty ETL logic, misunderstood data transformations or human interference.

Faulty ETL logic can introduce data policy violations in a variety of ways. For example, did all records move successfully from source to target? DataVerse provides data teams with assurance that all records moved as planned, and alerts when the reconciliation is incomplete.

This video shows an example where five records were dropped when the data moved, causing all downstream applications to be missing the data.

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Detect and Resolve Data Quality Policy Noncompliance

Erroneous ETL logic may also create data policy violations as the data moves. DataVerse summarizes the quantity of compliant records in green and the noncompliant records in red. Data teams can click the noncompliant record summary to view the violating records, and drill-in to see which rules were violated.

Teams can take action to remediate policy violations by logging the issue for resolution. And since the Global IDs software integrates with industry standard issue management platforms like ServiceNow and Jira, your issue resolution processes do not change.

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With DataVerse, companies can visualize and understand their data lineage, and have assurance that data policies are consistently enforced as the data moves across the enterprise.

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