Remove Data Architecture Remove Metadata Remove Risk
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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

Fragmented systems, inconsistent definitions, legacy infrastructure and manual workarounds introduce critical risks. Data quality is no longer a back-office concern. We also examine how centralized, hybrid and decentralized data architectures support scalable, trustworthy ecosystems.

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How to Manage Risk with Modern Data Architectures

Cloudera

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

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Very Meta … Unlocking Data’s Potential with Metadata Management Solutions

erwin

Untapped data, if mined, represents tremendous potential for your organization. While there has been a lot of talk about big data over the years, the real hero in unlocking the value of enterprise data is metadata , or the data about the data. Metadata Is the Heart of Data Intelligence.

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How Metadata Makes Data Meaningful

erwin

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

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5 Ways Data Modeling Is Critical to Data Governance

erwin

For decades, data modeling has been the optimal way to design and deploy new relational databases with high-quality data sources and support application development. Today’s data modeling is not your father’s data modeling software. So here’s why data modeling is so critical to data governance.

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Using Strategic Data Governance to Manage GDPR/CCPA Complexity

erwin

Modern, strategic data governance , which involves both IT and the business, enables organizations to plan and document how they will discover and understand their data within context, track its physical existence and lineage, and maximize its security, quality and value. Strengthen data security. How erwin Can Help.

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Making OT-IT integration a reality with new data architectures and generative AI

CIO Business Intelligence

In this way, manufacturers would be able to reduce risk, increase resilience and agility, boost productivity, and minimise their environmental footprint. Industrial knowledge graphs employ industry-standard metadata to contextualize and structure data so it can be used in large language models.