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Breaches are resumé generating events.”. Dan Kirsch, Analyst, Hurwitz Associates, agrees that CISOs must take responsibility, when he says that “data protection is absolutely part of the CISO’s job. Do we know the business outcomes tied to data risk management? These questions drive classification. What do we know?
It involves the creation of rules for collecting, storing, processing, and sharing data to ensure its accuracy, completeness, consistency, and security. Some key concepts related to data governance include: Dataquality: Ensuring that data is accurate, complete, and consistent.
It involves the creation of rules for collecting, storing, processing, and sharing data to ensure its accuracy, completeness, consistency, and security. Some key concepts related to data governance include: Dataquality: Ensuring that data is accurate, complete, and consistent.
To make good on this potential, healthcare organizations need to understand their data and how they can use it. These systems should collectively maintain dataquality, integrity, and security, so the organization can use data effectively and efficiently. Why Is Data Governance in Healthcare Important?
So how does data intelligence support governance? Examples of governance features that leverage data intelligence include: A business glossary, with automated dataclassification, to align teams on key terms. Data lineage tracking and impact analysis reports to show transformation over time. Dataquality.
Global policies such as data dictionaries ( business glossaries ), dataclassification tags, and additional information with metadata forms can be created by the governance team to ensure standardization and consistency within the organization. Unmanaged assets : For unmanaged assets, permissions are handled externally.
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