Category: Analytics

Since we launched Amazon Redshift as a cloud data warehouse service more than seven years ago, tens of thousands of customers have built analytics workloads using it. We’re always listening to your feedback and, in December 2019, we announced our third-generation RA3 node type to provide you the ability to scale and pay for compute […]

We’re happy to announce Amazon EMR Studio (Preview), an integrated development environment (IDE) that makes it easy for data scientists and data engineers to develop, visualize, and debug applications written in R, Python, Scala, and PySpark. EMR Studio provides fully managed Jupyter notebooks and tools like Spark UI and YARN Timeline Service to simplify debugging. […]

Amazon Redshift is a fast, petabyte-scale cloud data warehouse delivering the best price–performance. Amazon Redshift automates common maintenance tasks and is self-learning, self-optimizing, and constantly adapting to your actual workload. Amazon Redshift has several features that automate performance tuning: automatic vacuum delete, automatic table sort, automatic analyze, and Amazon Redshift Advisor for actionable insights into […]

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL. Amazon Redshift offers up to 3x better price performance than any other cloud data warehouse. Tens of thousands of customers use Amazon Redshift to process exabytes of data […]

Since we announced Amazon Redshift in 2012, tens of thousands of customers have trusted us to deliver the performance and scale they need to gain business insights from their data. Amazon Redshift customers span all industries and sizes, from startups to Fortune 500 companies, and we work to deliver the best price performance for any use case. Earlier […]

Machine learning (ML) is becoming more mainstream, but even with the increasing adoption, it’s still in its infancy. For ML to have the broad impact that we think it can have, it has to get easier to do and easier to apply. We launched Amazon SageMaker in 2017 to remove the challenges from each stage […]

December 2022: Post was reviewed and updated to announce support of Prediction Probabilities for Classification problems using Amazon Redshift ML. Amazon Redshift is a fast, petabyte-scale cloud data warehouse data warehouse delivering the best price–performance. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. […]

This is a guest post by Gautham Acharya, Software Engineer III at the Allen Institute for Brain Science, in partnership with AWS Data Lab Solutions Architect Ranjit Rajan, and AWS Sr. Enterprise Account Executive Arif Khan. The human brain is one of the most complex structures in the universe. Billions of neurons and trillions of […]

Consolidating data from a work management tool like Jira and integrating this data with other data sources like ServiceNow, GitHub, Jenkins, and Time Entry Systems enables end-to-end visibility of different aspects of the software development lifecycle and helps keep your projects on schedule and within budget. Amazon Simple Storage Service (Amazon S3) is an object […]

Before you can create visuals and dashboards that convey useful information, you need to transform and prepare the underlying data. The range and complexity of data transformation steps required depends on the visuals you would like in your dashboard. Often, the data transformation process is time-consuming and highly iterative, especially when you are working with […]