Understand the Meaning & Flow of Enterprise Data
Data Governance Driven by Data
Human beings craft policies and high-level definitions, but the truth of what needs governing lies in the data. The Global IDs Enterprise Data Automation platform automates data governance by building comprehensive knowledge of where data is, what it is, and how it flows, gaining control of the data from the bottom up.
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Ensuring Data Privacy
Without comprehensive knowledge of the data landscape, there is no way to know all sensitive data has been secured. The Global IDs Enterprise Data Automation platform creates the privacy foundation that ensures compliance and strengthens stakeholder confidence.
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Enabling Digital Transformation
Cloud migration, modernization, mergers, enabling analytics and business intelligence...Every enterprise faces one or more of these journeys of digital transformation. The Global IDs Enterprise Data Automation platform delivers the ecosystem transparency needed for objective decision making as your digital environment undergoes enterprise-wide change.
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Metadata Management is the Fulcrum
The sheer growth of enterprise data, increasing regulatory pressures, and the need to extract more value from data have all caused metadata to emerge as the fulcrum of data management, compliance, and business intelligence.
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Understanding the Difference Between Data Governance and Data Quality
Data governance and data quality are closely related, but with an important difference in perspective. Understanding this difference brings to light a crucial prerequisite for both: a greater transparency of the ecosystem.
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The Intelligence at the Heart of Data Lineage
Data lineage helps address business problems and regulatory demands that are posed in logical business terms. In order to make sense of the physical flow of data in logical terms, automated classification is a must.
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Integrating Data from Outside the Enterprise
In business to business relationships, partner data becomes your data. Integrating and leveraging external data sources is being done today as a painful manual process, but is ripe for automation as an ideal use case for data classification.
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