Remove Contextual Data Remove Data Lake Remove Data-driven Remove Optimization
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4 ways generative AI addresses manufacturing challenges

IBM Big Data Hub

The industry must continually optimize process, improve efficiency, and improve overall equipment effectiveness. Or we create a data lake, which quickly degenerates to a data swamp. Contextual data understanding Data systems often cause major problems in manufacturing firms.

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Achieving Trusted AI in Manufacturing

Cloudera

As we navigate the fourth and fifth industrial revolution, AI technologies are catalyzing a paradigm shift in how products are designed, produced, and optimized. But with this data — along with some context about the business and process — manufacturers can leverage AI as a key building block to develop and enhance operations.

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Five benefits of a data catalog

IBM Big Data Hub

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. Why: Data Makes It Different. Not only is data larger, but models—deep learning models in particular—are much larger than before.

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