Remove Government Remove Healthcare Remove Metadata Remove Security
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Metadata Management, Data Governance and Automation

erwin

erwin released its State of Data Governance Report in February 2018, just a few months before the General Data Protection Regulation (GDPR) took effect. Download Free GDPR Guide | Step By Step Guide to Data Governance for GDPR?. Data governance maturity includes the ability to rely on automated and repeatable processes.

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Mastering healthcare data governance with data lineage

IBM Big Data Hub

The healthcare industry faces arguably the highest stakes when it comes to data governance. The impact of healthcare data usage on people’s lives lies at the heart of why data governance in healthcare is so crucial.In healthcare, managing the accuracy, quality and integrity of data is the focus of data governance.

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Data Intelligence and Its Role in Combating Covid-19

erwin

Managing and Governing Data From Lots of Disparate Sources. This data will be collected from organizations such as, the World Health Organization (WHO), the Centers for Disease Control (CDC), and state and local governments across the globe. Unraveling Data Complexities with Metadata Management.

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Delivering responsible AI in the healthcare and life sciences industry

IBM Big Data Hub

With today’s new generative AI products, trust, security and regulatory issues remain top concerns for government healthcare officials and C-suite leaders representing biopharmaceutical companies, health systems, medical device manufacturers and other organizations.

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FAIR Data Principles in Life Sciences: A case for Data Intelligence Cloud

Collibra

At its core, FAIR aims to break down data silos by providing guidelines to make data: Findable – metadata and data should be searchable and should be easily located. Accessible – metadata and data should be accessible to users. Additionally, metadata should include qualified references to other metadata.

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