Category: Analytics

To meet the demands of diverse data integration use cases, AWS Glue now supports SaaS connectivity for Salesforce. This enables users to quickly preview and transfer their customer relationship management (CRM) data, fetch the schema dynamically on request, and query the data. This post explores the new Salesforce connector for AWS Glue and demonstrates how to build a modern extract, transform, and load (ETL) pipeline with AWS Glue ETL scripts.

This blog post provides a step-by-step guide to integrating IAM Identity Center with Microsoft Entra ID as the IdP and configuring Amazon Redshift as an AWS managed application. Additionally, you’ll learn how to set up the Amazon Redshift driver in Tableau, enabling SSO directly within Tableau Desktop.

Today, we are pleased to announce the general availability of AWS Glue job queuing. Job queuing increases scalability and improves the customer experience of managing AWS Glue jobs. With this new capability, you no longer need to manage concurrency of your AWS Glue job runs and attempt retries just to avoid job failures due to high concurrency. This post demonstrates how job queuing helps you scale your Glue workloads and how job queuing works.

In a previous post, we showed how Zero Copy data federation empowers businesses to access Amazon Redshift data within the Salesforce Data Cloud to enrich customer 360 data with operational data. This two-part series explores how analytics teams can access customer 360 data from Salesforce Data Cloud within Amazon Redshift to generate insights on unified data without the overhead of extract, transform, and load (ETL) pipelines. In this post, we cover data sharing between Salesforce Data Cloud and customers’ AWS accounts in the same AWS Region. Part 2 covers cross-Region data sharing between Salesforce Data Cloud and customers’ AWS accounts.

In this post, we share a chargeback model that you can use to track and allocate the costs of Spark workloads running on Amazon EMR on EC2 clusters. We describe an approach that assigns Amazon EMR costs to different jobs, teams, or lines of business. You can use this feature to distribute costs across various business units. This can assist you in monitoring the return on investment for your Spark-based workloads.

In this post, I’ll walk you through how to copy data from one Amazon Relational Database Service (Amazon RDS) for PostgreSQL database to another, while scrubbing PII along the way using AWS Glue. You will learn how to prepare a multi-account environment to access the databases from AWS Glue, and how to model an ETL data flow that automatically masks PII as part of the transfer process, so that no sensitive information will be copied to the target database in its original form.

In this post, we explore the performance benefits of using the Amazon EMR runtime for Apache Spark and Apache Iceberg compared to running the same workloads with open source Spark 3.5.1 on Iceberg tables. Iceberg is a popular open source high-performance format for large analytic tables. Our benchmarks demonstrate that Amazon EMR can run TPC-DS […]

The current scaling approach of Amazon Redshift Serverless increases your compute capacity based on the query queue time and scales down when the queuing reduces on the data warehouse. However, you might need to automatically scale compute resources based on factors like query complexity and data volume to meet price-performance targets, irrespective of query queuing. […]

When you use Amazon OpenSearch Service for time-bound data like server logs, service logs, application logs, clickstreams, or event streams, storage cost is one of the primary drivers for the overall cost of your solution. Over the last year, OpenSearch Service has released features that have opened up new possibilities for storing your log data […]

In today’s data-driven world, the ability to seamlessly integrate and utilize diverse data sources is critical for gaining actionable insights and driving innovation. As organizations increasingly rely on data stored across various platforms, such as Snowflake, Amazon Simple Storage Service (Amazon S3), and various software as a service (SaaS) applications, the challenge of bringing these […]