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Data platform trinity: Competitive or complementary?

IBM Journey to AI blog

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.

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

Marktechpost

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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Generate user-personalized communication with Amazon Personalize and Amazon Bedrock

Flipboard

The workflow consists of the following steps: Import your user, item, and interaction data into Amazon Personalize. The user and item datasets are not required for Amazon Personalize to generate recommendations, but providing good item and user metadata provides the best results in your trained models.

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Ken Claffey, CEO of VDURA – Interview Series

Unite.AI

Can you share the story behind the creation of the VDURA Data Platform and the key challenges you aimed to address in the AI and HPC landscape? The VDURA Data Platform was developed to address a critical and growing gap in data infrastructure for AI and HPC workloads: balancing high performance with enterprise-grade durability.

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Manage access controls in generative AI-powered search applications using Amazon OpenSearch Service and Amazon Cognito

Flipboard

Solution overview By combining the powerful vector search capabilities of OpenSearch Service with the access control features provided by Amazon Cognito , this solution enables organizations to manage access controls based on custom user attributes and document metadata. If you don’t already have an AWS account, you can create one.

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Achieve your AI goals with an open data lakehouse approach

IBM Journey to AI blog

A lakehouse should make it easy to combine new data from a variety of different sources, with mission critical data about customers and transactions that reside in existing repositories. Also, a lakehouse can introduce definitional metadata to ensure clarity and consistency, which enables more trustworthy, governed data.

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How to modernize data lakes with a data lakehouse architecture

IBM Journey to AI blog

But what has been clear is that there is an urgent need to modernize these deployments and protect the investment in infrastructure, skills and data held in those systems. In a search for answers, the industry looked at existing data platform technologies and their strengths. Comprehensive data security and data governance (i.e.

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