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Google AI Introduces Croissant: A Metadata Format for Machine Learning-Ready Datasets

Marktechpost

Even among datasets that include the same subject matter, there is no standard layout of files or data formats. This obstacle lowers productivity through machine learning development—from data discovery to model training. Database metadata can be expressed in various formats, including schema.org and DCAT.

Metadata 102
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Five benefits of a data catalog

IBM Journey to AI blog

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.

Metadata 130
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Datasets at your fingertips in Google Search

Google Research AI blog

Dataset Search shows users essential metadata about datasets and previews of the data where available. Users can then follow the links to the data repositories that host the datasets. Dataset Search primarily indexes dataset pages on the Web that contain schema.org structured data.

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Build trust in banking with data lineage

IBM Journey to AI blog

This trust depends on an understanding of the data that inform risk models: where does it come from, where is it being used, and what are the ripple effects of a change? Moreover, banks must stay in compliance with industry regulations like BCBS 239, which focus on improving banks’ risk data aggregation and risk reporting capabilities.

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Data architecture strategy for data quality

IBM Journey to AI blog

Monitor and identify data quality issues closer to the source to mitigate the potential impact on downstream processes or workloads. Efficiently adopt data platforms and new technologies for effective data management. Apply metadata to contextualize existing and new data to make it searchable and discoverable.

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CMU Researchers Introduce Zeno: A Framework for Behavioral Evaluation of Machine Learning (ML) Models

Marktechpost

Model outputs, metrics, metadata, and altered instances are only some of the fundamental components of behavioral assessment that can be implemented as Python API functions. The participant in Case 2 used the API’s extensibility to create model-analysis metadata. Zeno is made available to the public via a Python script.

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Unfolding the Details of Hive in Hadoop

Pickl AI

These work together to enable efficient data processing and analysis: · Hive Metastore It is a central repository that stores metadata about Hive’s tables, partitions, and schemas. Processing of Data Once the data is stored, Hive provides a metadata layer allowing users to define the schema and create tables.