Remove Metadata Remove Risk Remove Unstructured Data
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Generative AI is pushing unstructured data to center stage

CIO Business Intelligence

When I think about unstructured data, I see my colleague Rob Gerbrandt (an information governance genius) walking into a customer’s conference room where tubes of core samples line three walls. While most of us would see dirt and rock, Rob sees unstructured data. have encouraged the creation of unstructured data.

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Comprehensive data management for AI: The next-gen data management engine that will drive AI to new heights

CIO Business Intelligence

However, as model training becomes more advanced and the need increases for ever more data to train, these problems will be magnified. As the next generation of AI training and fine-tuning workloads takes shape, limits to existing infrastructure will risk slowing innovation. What does the next generation of AI workloads need?

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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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Monitoring Apache Iceberg metadata layer using AWS Lambda, AWS Glue, and AWS CloudWatch

AWS Big Data

In the era of big data, data lakes have emerged as a cornerstone for storing vast amounts of raw data in its native format. They support structured, semi-structured, and unstructured data, offering a flexible and scalable environment for data ingestion from multiple sources.

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5 Ways Data Modeling Is Critical to Data Governance

erwin

They also face increasing regulatory pressure because of global data regulations , such as the European Union’s General Data Protection Regulation (GDPR) and the new California Consumer Privacy Act (CCPA), that went into effect last week on Jan. Today’s data modeling is not your father’s data modeling software.

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Do I Need a Data Catalog?

erwin

The data catalog is a searchable asset that enables all data – including even formerly siloed tribal knowledge – to be cataloged and more quickly exposed to users for analysis. Three Types of Metadata in a Data Catalog. Technical Metadata. Operational Metadata. for analysis and integration purposes).

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5 Benefits intelligent document processing brings to content management

CIO Business Intelligence

Add context to unstructured content With the help of IDP, modern ECM tools can extract contextual information from unstructured data and use it to generate new metadata and metadata fields.

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