AWS Big Data Blog

Enhance data governance with enforced metadata rules in Amazon DataZone

We’re excited to announce a new feature in Amazon DataZone that offers enhanced metadata governance for your subscription approval process. Using this update, domain owners can define metadata requirements and enforce them on data consumers when they request subscriptions to data assets. By making it mandatory for data consumers to provide specific metadata, domain owners can achieve compliance, meet organizational standards, and support audit and reporting needs.

Introducing Point in Time queries and SQL/PPL support in Amazon OpenSearch Serverless

Today we announced support for three new features for Amazon OpenSearch Serverless: Point in Time (PIT) search, which enables you to maintain stable sorting for deep pagination in the presence of updates, and PPL and SQL, which give you new ways to query your data. In this post, we discuss the benefits of these new features and how to get started.

Introducing Amazon MWAA micro environments for Apache Airflow

Today, we’re excited to announce mw1.micro, the latest addition to Amazon MWAA environment classes. This offering is designed to provide an even more cost-effective solution for running Airflow environments in the cloud. With mw1.micro, we’re bringing the power of Amazon MWAA to teams who require a lightweight environment without compromising on essential features. In this post, we’ll explore mw1.micro characteristics, key benefits, ideal use cases, and how you can set up an Amazon MWAA environment based on this new environment class.

Integrate custom applications with AWS Lake Formation – Part 1

In this two-part series, we show how to integrate custom applications or data processing engines with Lake Formation using the third-party services integration feature. In this post, we dive deep into the required Lake Formation and AWS Glue APIs. We walk through the steps to enforce Lake Formation policies within custom data applications. As an example, we present a sample Lake Formation integrated application implemented using AWS Lambda.

Integrate custom applications with AWS Lake Formation – Part 2

In this two-part series, we show how to integrate custom applications or data processing engines with Lake Formation using the third-party services integration feature. In this post, we explore how to deploy a fully functional web client application, built with JavaScript/React through AWS Amplify (Gen 1), that uses the same Lambda function as the backend. The provisioned web application provides a user-friendly and intuitive way to view the Lake Formation policies that have been enforced.

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

In this post, we show you how to manage user access to enterprise documents in generative AI-powered tools according to the access you assign to each persona. This post illustrates how to build a document search RAG solution that makes sure only authorized users can access and interact with specific documents based on their roles, departments, and other relevant attributes. It combines OpenSearch Service and Amazon Cognito custom attributes to make a tag-based access control mechanism that makes it straightforward to manage at scale.

Enrich your AWS Glue Data Catalog with generative AI metadata using Amazon Bedrock

By harnessing the capabilities of generative AI, you can automate the generation of comprehensive metadata descriptions for your data assets based on their documentation, enhancing discoverability, understanding, and the overall data governance within your AWS Cloud environment. This post shows you how to enrich your AWS Glue Data Catalog with dynamic metadata using foundation models (FMs) on Amazon Bedrock and your data documentation.

How FINRA established real-time operational observability for Amazon EMR big data workloads on Amazon EC2 with Prometheus and Grafana

FINRA performs big data processing with large volumes of data and workloads with varying instance sizes and types on Amazon EMR. Amazon EMR is a cloud-based big data environment designed to process large amounts of data using open source tools such as Hadoop, Spark, HBase, Flink, Hudi, and Presto. In this post, we talk about our challenges and show how we built an observability framework to provide operational metrics insights for big data processing workloads on Amazon EMR on Amazon Elastic Compute Cloud (Amazon EC2) clusters.

Your guide to AWS Analytics at AWS re:Invent 2024

It’s AWS re:Invent time, where you turn your ideas into reality. Get a front row seat to hear real stories from AWS customers, experts and leaders about navigating pressing topics like generative AI and data analytics. For data enthusiasts and data professionals alike, this blog is a curated and comprehensive guide to all analytics sessions, for you to efficiently plan your itinerary.

Ingest telemetry messages in near real time with Amazon API Gateway, Amazon Data Firehose, and Amazon Location Service

These organizations use third-party satellite-powered terminal devices for remote monitoring using telemetry and NMEA-0183 formatted messages generated in near real time. This post demonstrates how to implement a satellite-based remote alerting and response solution on the AWS Cloud to provide time-critical alerts and actionable insights, with a focus on telemetry message ingestion and alerts. Key services in the solution include Amazon API Gateway, Amazon Data Firehose, and Amazon Location Service.