Category: Amazon Redshift

This post describes how HPE Aruba automated their Supply Chain management pipeline, and re-architected and deployed their data solution by adopting a modern data architecture on AWS.

Amazon Redshift, a warehousing service, offers a variety of options for ingesting data from diverse sources into its high-performance, scalable environment. Whether your data resides in operational databases, data lakes, on-premises systems, Amazon Elastic Compute Cloud (Amazon EC2), or other AWS services, Amazon Redshift provides multiple ingestion methods to meet your specific needs. The currently […]

In this post, we demonstrate how to use the AWS CDK and DSF to create a multi-data warehouse platform based on Amazon Redshift Serverless. DSF simplifies the provisioning of Redshift Serverless, initialization and cataloging of data, and data sharing between different data warehouse deployments.

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.

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.

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. […]

Unlocking the true value of data often gets impeded by siloed information. Traditional data management—wherein each business unit ingests raw data in separate data lakes or warehouses—hinders visibility and cross-functional analysis. A data mesh framework empowers business units with data ownership and facilitates seamless sharing. However, integrating datasets from different business units can present several […]

In this post, we show how to capture the data quality metrics for data assets produced in Amazon Redshift. With Amazon DataZone, the data owner can directly import the technical metadata of a Redshift database table and views to the Amazon DataZone project’s inventory. As these data assets gets imported into Amazon DataZone, it bypasses the AWS Glue Data Catalog, creating a gap in data quality integration. This post proposes a solution to enrich the Amazon Redshift data asset with data quality scores and KPI metrics.

Amazon Redshift Advisor offers recommendations about optimizing your Redshift cluster performance and helps you save on operating costs. In this post, we show you how to use the ListRecommendations API to set up email notifications for Advisor recommendations on your Redshift cluster. These recommendations, such as identifying tables that should be vacuumed to sort the data or finding table columns that are candidates for compression, can help improve performance and save costs.

As businesses strive to make informed decisions, the amount of data being generated and required for analysis is growing exponentially. This trend is no exception for Dafiti, an ecommerce company that recognizes the importance of using data to drive strategic decision-making processes. With the ever-increasing volume of data available, Dafiti faces the challenge of effectively managing and extracting valuable insights from this vast pool of information to gain a competitive edge and make data-driven decisions that align with company business objectives. The growing need for storage space to maintain data from over 90 sources and the functionality available on the new Amazon Redshift node types, including managed storage, data sharing, and zero-ETL integrations, led us to migrate from DC2 to RA3 nodes. In this post, we share how we handled the migration process and provide further impressions of our experience.