Category: Analytics

In this post, you’ll learn how Amazon EMR Serverless eliminates the need to configure local disk storage for Apache Spark workloads through a new serverless storage capability. We explain how this feature automatically handles shuffle operations, reduces data processing costs by up to 20%, prevents job failures from disk capacity constraints, and enables elastic scaling by decoupling storage from compute.

Organizations often struggle with building scalable and maintainable data lakes—especially when handling complex data transformations, enforcing data quality, and monitoring compliance with established governance. Traditional approaches typically involve custom scripts and disparate tools, which can increase operational overhead and complicate access control. A scalable, integrated approach is needed to simplify these processes, improve data reliability, […]

Amazon Redshift federated permissions simplify permissions management across multiple Redshift warehouses. In this post, we show you how to define data permissions one time and automatically enforce them across warehouses in your AWS account, removing the need to re-create security policies in each warehouse.

In this post, we demonstrate how Kiro CLI and the MSK MCP server can streamline your Kafka management. Through practical examples and demonstrations, we show you how to use these tools to perform common administrative tasks efficiently while maintaining robust security and reliability.

In this post, we show you how to unify governance and metadata across Amazon SageMaker Unified Studio and Atlan through a comprehensive bidirectional integration. You’ll learn how to deploy the necessary AWS infrastructure, configure secure connections, and set up automated synchronization to maintain consistent metadata across both platforms.

In this post, we demonstrate how to implement Apache Spark Connect on Amazon EMR on Amazon Elastic Compute Cloud (Amazon EC2) to build decoupled data processing applications. We show how to set up and configure Spark Connect securely, so you can develop and test Spark applications locally while executing them on remote Amazon EMR clusters.

In this post, we discuss how Taxbit partnered with Amazon Web Services (AWS) to streamline their crypto tax analytics solution using Amazon S3 Tables, achieving 82% cost savings and five times faster processing times.

In this post, we show how to create and update Iceberg tables with partitions in the Data Catalog using the AWS SDK and AWS CloudFormation.

With Kinesis Data Firehose, customers can use a fully managed, reliable, and scalable data streaming solution to Splunk. In this post, we tell you a bit more about the Kinesis Data Firehose and Splunk integration. We also show you how to ingest large amounts of data into Splunk using Kinesis Data Firehose.

In this post, we discuss the best practices that you can follow while querying Apache Iceberg data with Amazon Redshift