Remove 2012 Remove Clustering Remove Data Lakes
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Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift

Flipboard

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. Here we use RedshiftDatasetDefinition to retrieve the dataset from the Redshift cluster.

ML 123
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How to Create Iceberg Tables in Snowflake

phData

Snowflake-managed Iceberg table’s performance is at par with Snowflake native tables while storing the data in public cloud storage. They are Ideal for situations where the data is already stored in data lakes and do not intend to load into Snowflake but need to use the features and performance of Snowflake.

SQL 52
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Dive deep into vector data stores using Amazon Bedrock Knowledge Bases

AWS Machine Learning Blog

These models support mapping different data types like text, images, audio, and video into the same vector space to enable multi-modal queries and analysis.

Database 107