AWS Big Data Blog

New Powered by QuickSight program helps AWS partners embed interactive analytics in applications to enable data-driven experiences

Applications today generate enormous amounts of data. This provides an incredible opportunity for independent software vendors (ISVs) to deliver business intelligence (BI) offerings as a part of their application, providing visuals, dashboards, and self-service capabilities to customers. These insights are crucial for data-driven decision-making for end-users of these apps, especially if surfaced in the moments […]

How Fresenius Medical Care aims to save dialysis patient lives using real-time predictive analytics on AWS

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. This post is co-written by Kanti Singh, Director of Data & Analytics at Fresenius Medical Care. Fresenius Medical Care is the world’s leading provider of kidney care […]

Removing complexity to improve business performance: How Bridgewater Associates built a scalable, secure, Spark-based research service on AWS

This is a guest post co-written by Sergei Dubinin, Oleksandr Ierenkov, Illia Popov and Joel Thompson, from Bridgewater. Bridgewater’s core mission is to understand how the world works by analyzing the drivers of markets and turning that understanding into high-quality portfolios and investment advice for our clients. Within Bridgewater Technology, we strive to make our […]

Reduce network traffic costs of your Amazon MSK consumers with rack awareness

Amazon Managed Streaming for Apache Kafka (Amazon MSK) runs Apache Kafka clusters for you in the cloud. Although using cloud services means you don’t have to manage racks of servers any more, we take advantage of rack aware features in Apache Kafka to spread risk across AWS Availability Zones and increase availability of Amazon MSK […]

How Fannie Mae built a data mesh architecture to enable self-service using Amazon Redshift data sharing

This post is co-written by Kiran Ramineni and Basava Hubli, from Fannie Mae. Amazon Redshift data sharing enables instant, granular, and fast data access across Amazon Redshift clusters without the need to copy or move data around. Data sharing provides live access to data so that users always see the most up-to-date and transactionally consistent […]

Set up federated access to Amazon Athena for Microsoft AD FS users using AWS Lake Formation and a JDBC client

Tens of thousands of AWS customers choose Amazon Simple Storage Service (Amazon S3) as their data lake to run big data analytics, interactive queries, high-performance computing, and artificial intelligence (AI) and machine learning (ML) applications to gain business insights from their data. On top of these data lakes, you can use AWS Lake Formation to […]

Amazon Redshift data sharing best practices and considerations

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift data sharing allows for a secure and easy way to share live data for reading across Amazon Redshift clusters. It allows an […]

New row and column interactivity options for tables and pivot tables in Amazon QuickSight – Part 1

Amazon QuickSight is a fully-managed, cloud-native business intelligence (BI) service that makes it easy to create and deliver insights to everyone in your organization. You can make your data come to life with rich interactive charts and create beautiful dashboards to share with thousands of users, either directly within a QuickSight application, or embedded in […]

Introducing AWS Glue interactive sessions for Jupyter

Interactive Sessions for Jupyter is a new notebook interface in the AWS Glue serverless Spark environment. Starting in seconds and automatically stopping compute when idle, interactive sessions provide an on-demand, highly-scalable, serverless Spark backend to Jupyter notebooks and Jupyter-based IDEs such as Jupyter Lab, Microsoft Visual Studio Code, JetBrains PyCharm, and more. Interactive sessions replace […]

From centralized architecture to decentralized architecture: How data sharing fine-tunes Amazon Redshift workloads

From centralized architecture to decentralized architecture: How data sharing fine-tunes Amazon Redshift workloads

Amazon Redshift is a fast, petabyte-scale cloud data warehouse delivering the best price-performance. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Today, tens of thousands of customers run business-critical workloads on Amazon Redshift. With the significant growth of data for big […]