AWS Big Data Blog

Category: Analytics

Harness the power of your data with AWS Analytics

2020 has reminded us of the need to be agile in the face of constant and sudden change. Every customer I’ve spoken to this year has had to do things differently because of the pandemic. Some are focusing on driving greater efficiency in their operations and others are experiencing a massive amount of growth. Across […]

Introducing Amazon Redshift RA3.xlplus nodes with managed storage

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 […]

Amazon EMR Studio (Preview): A new notebook-first IDE experience with Amazon EMR

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. […]

Optimizing tables in Amazon Redshift using Automatic Table Optimization

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 […]

Announcing Amazon Redshift data sharing (preview)

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 […]

Get up to 3x better price performance with Amazon Redshift than other cloud data warehouses

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 […]

Bringing machine learning to more builders through databases and analytics services

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 […]

Create, train, and deploy machine learning models in Amazon Redshift using SQL with Amazon Redshift ML

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. […]

How the Allen Institute uses Amazon EMR and AWS Step Functions to process extremely wide transcriptomic datasets

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 […]

Ingesting Jira data into Amazon S3

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 […]