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Latest updates for Amazon Sagemaker Lakehouse

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aws.amazon.com /2 days ago

Multi-cloud lakehouse architecture on AWS for Agentic AI, Part 1: Architecture and best practices

This post focuses on explaining the architecture approach to build the open lakehouse architecture on AWS, unifying the metadata catalog across providers for the AI agents to acces...

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aws.amazon.com /1 month ago

Access Amazon S3 data files directly using AWS Lake Formation permissions

In this post, we demonstrate reading from and writing to Lake Formation-managed S3 locations using Apache Spark jobs from EMR. Lake Formation credential vending for S3 location acc...

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aws.amazon.com /1 week ago

Streaming benchmark and recommendation results to MLflow with Amazon SageMaker AI

In this post, you learn how to use the new MLflow integration with Amazon SageMaker AI optimized inference recommendation jobs and Amazon SageMaker AI benchmark jobs to automatical...

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aws.amazon.com /1 week ago

How BigBasket uses the Iceberg based lakehouse architecture on AWS to power lightning-fast grocery delivery across India

In this post, we demonstrate how BigBasket implemented the lakehouse architecture on AWS, including their architecture decisions, implementation approach, and the measurable busine...

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aws.amazon.com /1 month ago

How Amazon is moving to integrate catalogs to improve data discovery with Amazon SageMaker

Enterprises face challenges when teams create data assets outside of central data catalogs. It adds overhead for discovery, and limits collaboration. Amazon’s Business Data Technol...

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aws.amazon.com /3 weeks ago

Detecting fraud patterns across Snowflake and AWS using SageMaker Data Agent

Amazon SageMaker Data Agent launches three new capabilities in Amazon SageMaker Unified Studio notebooks: SQL analytics on Snowflake data sources, materialized view management, and...

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aws.amazon.com /1 week ago

Accelerating log analytics at scale with AWS Glue and Apache Iceberg materialized views

In this post, you learn how to build an application log pipeline for production use with Amazon CloudWatch Logs, AWS Lambda, Amazon Data Firehose, AWS Glue, and Apache Iceberg mate...

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aws.amazon.com /1 month ago

Capture data lineage of Amazon EMR spark jobs into Amazon SageMaker Unified Studio

In this post, you’ll walk through a practical, step-by-step example that shows how to capture and track data lineage from Spark jobs running on Amazon EMR directly into Amazon Sage...

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aws.amazon.com /1 month ago

Accelerate SQL development with SageMaker Data Agent in Query Editor

In this post, you learn how to use Data Agent in Query Editor to explore data, build multi-step analyses, recover from errors, and summarize results using a public education datase...

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databricks.com /1 day ago

Foundational context: Cross-industry & function-specific accelerators for Lakebase

Databricks Lakebase is a fully managed, serverless Postgres database built for the...

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aws.amazon.com /3 weeks ago

Monitor and debug generative AI inference with SageMaker detailed metrics and Insights dashboard on CloudWatch

Amazon SageMaker AI provides fully managed real-time inference hosting for machine learning models. You deploy a model to a SageMaker endpoint backed by one or more compute instanc...

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snowflake.com /1 month ago

The Interoperable Lakehouse: Agency Over Your Data

Achieve true agency over your data with the Snowflake Interoperable Lakehouse. Unify storage, governance, and semantics with managed Apache Iceberg.

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aws.amazon.com /1 week ago

Monitoring discriminative ML models using Amazon SageMaker AI with MLflow

Implementing a data and model monitoring solution is necessary to maintain prediction accuracy and help achieve the best outcome for your machine learning use case. This post shows...

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dataengineeringcentral.substack.com /4 weeks ago

The Future of the Lakehouse: Delta Lake, Rust, and Data Platforms at Scale

with Ethan Urbanski

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aws.amazon.com /1 month ago

Real-time CDC from Aurora PostgreSQL to Amazon S3 Tables using Debezium and Firehose

In this post, we show you how to build a CDC pipeline that delivers query-ready Iceberg tables directly. The pipeline captures inserts, updates, and deletes from Aurora PostgreSQL...

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aws.amazon.com /1 month ago

Fundamental’s Large Tabular Model NEXUS is now available on Amazon SageMaker JumpStart

In this post, we show you how to get started with NEXUS on Amazon SageMaker JumpStart, walk through the deployment process, and demonstrate how to run predictions against your ente...

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aws.amazon.com /1 month ago

Comprehensive observability for Amazon SageMaker AI LLM inference: From GPU utilization to LLM quality

This post demonstrates a comprehensive observability solution using Amazon Managed Grafana dashboards that provides a holistic view of both quality and quantity for LLMs served on...

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aws.amazon.com /3 weeks ago

AI-powered BI with Snowflake and Amazon Quick

In this post, you will learn how to build an end-to-end integration between Snowflake semantic views and Amazon Quick. The sample data is user review data for a media company. You...

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aws.amazon.com /6 days ago

Enhancing enterprise inference on Amazon SageMaker HyperPod with data capture, Hugging Face, NVMe, and Route 53 integrat...

In this post, we walk through five capabilities now available in SageMaker HyperPod inference: multi-tier data capture for auditing and model improvement, direct deployment from Hu...

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aws.amazon.com /1 month ago

Build stateful streaming applications with Apache Spark 4.0 on Amazon EMR Serverless

In this post, we demonstrate how to build a production-ready IoT device monitoring system using Spark 4.0’s transformWithState API on Amazon EMR Serverless. This example showcases...

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aws.amazon.com /2 weeks ago

Simplify model selection in Amazon Bedrock with the open source Model Profiler

The Amazon Bedrock Model Profiler is an open source tool that aggregates model metadata from multiple AWS APIs and external sources into a single, searchable interface. In this pos...

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aws.amazon.com /1 month ago

Accelerate ML feature pipelines with new capabilities in Amazon SageMaker Feature Store

Today, we’re announcing three new capabilities available in SageMaker Python SDK v3.8.0. In this post, we walk through each capability with code examples you can use to get started...

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databricks.com /1 month ago

Announcing Lakebase Change Data Feed (CDF)

Moving data from your operational database has traditionally meant setting up and...

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aws.amazon.com /1 month ago

Build governance dashboards for Amazon SageMaker Catalog with Amazon Quick

In a previous post, we showed you how to query Amazon SageMaker Catalog metadata using SQL by using the metadata export feature. This post builds on that foundation by demonstratin...

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