Data Platform Explainability Metadata 
IBM Journey to AI blog
JANUARY 18, 2023
Data platform architecture has an interesting history. A read-optimized platform that can integrate data from multiple applications emerged. In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution.
Marktechpost
MARCH 12, 2024
Database metadata can be expressed in various formats, including schema.org and DCAT. Unfortunately, these formats weren’t made with machine learning data in mind. Google has recently introduced Croissant, a new format for metadata in ML-ready datasets. Users can then publish their datasets.
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IBM Journey to AI blog
APRIL 10, 2023
That is, it should support both sound data governance —such as allowing access only by authorized processes and stakeholders—and provide oversight into the use and trustworthiness of AI through transparency and explainability.
IBM Journey to AI blog
AUGUST 17, 2023
Year after year, IBM Consulting works with the United States Tennis Association (USTA) to transform massive amounts of data into meaningful insight for tennis fans. This year, the USTA is using watsonx , IBM’s new AI and data platform for business.
AWS Machine Learning Blog
DECEMBER 5, 2024
For use cases where accuracy is critical, customers need the use of mathematically sound techniques and explainable reasoning to help generate accurate FM responses. This includes watermarking, content moderation, and C2PA support (available in Amazon Nova Canvas) to add metadata by default to generated images.
AWS Machine Learning Blog
OCTOBER 20, 2023
Data lake foundations This module helps data lake admins set up a data lake to ingest data, curate datasets, and use the AWS Lake Formation governance model for managing fine-grained data access across accounts and users using a centralized data catalog, data access policies, and tag-based access controls.
Heartbeat
DECEMBER 7, 2023
This data source may be related to the sales sector, the manufacturing industry, finance, health, and R&D… Briefly, I am talking about a field-specific data source. The domain of the data. Regardless, the data fabric must be consistent for all its components. Data fabric needs metadata management maturity.
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