AWS Big Data Blog

AWS re:Invent 2023 Amazon Redshift Sessions Recap

Amazon Redshift powers data-driven decisions for tens of thousands of customers every day with a fully managed, AI-powered cloud data warehouse, delivering the best price-performance for your analytics workloads. Customers use Amazon Redshift as a key component of their data architecture to drive use cases from typical dashboarding to self-service analytics, real-time analytics, machine learning (ML), data sharing and monetization, and more.

This year’s AWS re:Invent conference, held in Las Vegas from November 27 through December 1, showcased the advancements of Amazon Redshift to help you further accelerate your journey towards modernizing your cloud analytics environments. To learn more about the latest and greatest advancements and how customers are powering data-driven decision-making using Amazon Redshift, watch the re:Invent sessions available on demand listed in this post.


Adam Selipsky, Chief Executive Officer of Amazon Web Services

Watch Adam Selipsky, CEO of Amazon Web Services, as he shares his perspective on cloud transformation. He highlights innovations in data, infrastructure, and artificial intelligence and machine learning that are helping AWS customers achieve their goals faster, mine untapped potential, and create a better future. Learn more about the AWS zero-ETL future with newly launched AWS databases integrations with Amazon Redshift.

Swami Sivasubramanian, Vice President of AWS Data and Machine Learning

Watch Swami Sivasubramanian, Vice President of Data and AI at AWS, to discover how you can use your company data to build differentiated generative AI applications and accelerate productivity for employees across your organization. Learn more about these new generative AI features to increase productivity including Amazon Q generative SQL in Amazon Redshift.

Peter DeSantis, Senior Vice President of AWS Utility Computing

Watch Peter DeSantis, Senior Vice President of AWS Utility Computing, as he deep dives into the engineering that powers AWS services. Get a closer look at how scaling for data warehousing works in AWS with the latest introduction of AI driven scaling and optimizations in Amazon Redshift Serverless to enable better price-performance for your workloads.

Innovation Talks

Data drives transformation: Data foundations with AWS analytics with G2 Krishnamoorthy, Vice President of AWS Analytics

G2’s session discusses strategies for embedding analytics into your applications and ideas for building a data foundation that supports your business initiatives. With new capabilities for self-service and straightforward builder experiences, you can democratize data access for line of business users, analysts, scientists, and engineers. Hear also from Adidas, GlobalFoundries, and University of California, Irvine.


ANT203 | What’s new in Amazon Redshift

Watch this session to learn about the newest innovations within Amazon Redshift—the petabyte-scale AWS Cloud data warehousing solution. Amazon Redshift empowers users to extract powerful insights by securely and cost-effectively analyzing data across data warehouses, operational databases, data lakes, third-party data stores, and streaming sources using zero-ETL approaches. Easily build and train machine learning models using SQL within Amazon Redshift to generate predictive analytics and propel data-driven decision-making. Learn about Amazon Redshift’s newest functionality to increase reliability and speed to insights through near-real-time data access, ML, and more—all with impressive price-performance.

ANT322 | Modernize analytics by moving your data warehouse to Amazon Redshift

Watch this session to hear from AWS customers as they share their journeys moving to a modern cloud data warehouse and analytics with Amazon Redshift. Learn best practices for building powerful analytics and ML applications and operating at scale while keeping costs low.

ANT211 | Powering self-service & near real-time analytics with Amazon Redshift

To stay competitive, allowing data citizens across your organization to see near-real-time analytics without worrying about data infrastructure management is crucial for your business. In this session, learn how your data users can get to near-real-time insights on streaming data with Amazon Redshift and AWS streaming data services. Explore a solution using flexible querying tools and a serverless architecture, which brings intelligent automation and scaling capabilities, and maintains consistently high performance for even the most demanding and volatile workloads.

ANT325 | Amazon Redshift: A decade of innovation in cloud data warehousing

Exponential data growth has created unique challenges for data practitioners to manage data warehouses that can support high performance workloads at scale within cost constraints. Amazon Redshift has been constantly innovating over the last decade to give you a modern, massively parallel processing cloud data warehouse that delivers the best price-performance, ease of use, scalability, and reliability. In this session, learn about Amazon Redshift’s technical innovations including serverless, AI/ML-powered autonomics, and zero-ETL data integrations. Discover how you can use Amazon Redshift to build a data mesh architecture to analyze your data.

ANT326 | Set up a zero-ETL-based analytics architecture for your organizations

ETL (extract, transform, and load data) can be challenging, time-consuming, and costly. AWS is building a zero-ETL future with capabilities like streaming ingestion into the data warehouse, federated querying, and connectors that access data in place across databases, data lakes, and third-party data sources without data movement. In this session, learn how zero-ETL investments such as Amazon Aurora zero-ETL integration with Amazon Redshift drive direct integration between AWS data services to allow data engineers to focus on creating value from data instead of spending time and resources building pipelines.

ANT351 | [NEW LAUNCH] Multi-data warehouse writes through Amazon Redshift data sharing

Organizations want simple and secure ways for their teams to meet their ETL SLAs, optimize costs, and collaborate on live data. With multi-data warehouse writes available through Amazon Redshift data sharing, you can write to the same databases with multiple warehouses at the same time. Join this session to learn how you can keep your ETL jobs completing predictably and on time, collaborate on live data with multiple teams, and better optimize your costs with this newly launched capability.

ANT 352 | [NEW LAUNCH] Amazon Q generative SQL in Amazon Redshift Query Editor

SQL, the industry standard language for data analytics, often requires users to spend a lot of time understanding an organization’s complex metadata in order to write and carry out complex SQL queries for data insights. Join this session to learn how you can help SQL users of all skill levels within your organization derive insights faster with the new Amazon Q generative SQL capability in Amazon Redshift Query Editor. This session demonstrates how this functionality works and how to use text prompts in plain English to build effective queries, including complex multi-table join or nested queries.

ANT 354 | [NEW LAUNCH] AI-powered scaling and optimization for Amazon Redshift Serverless

Amazon Redshift Serverless makes it easier to run analytics workloads of any size without having to manage data warehouse infrastructure. Redshift Serverless helps developers, data scientists, and analysts work across various data sources to build reports, applications, machine learning models, and more. In this session, learn about Redshift Serverless new AI-driven scaling and optimization functionality. This new functionality proactively adapts to workload changes and applies tailored performance optimizations by intelligently predicting query patterns and using machine learning, increasing consistent price-performance.

SEC245 | Simplify and improve access control for your AWS analytics services

As organizations adopt new AWS services, end users need more access to data across a full range of AWS analytics services to extract value and insights. Data end users are accustomed to seamless authentication to their AWS applications, and cloud administrators want more granular, user-based access control over their data. Join this session to learn how to simplify and improve access control using a new AWS IAM Identity Center feature, known as trusted identity propagation, along with supported AWS analytics services. Also learn how to audit user and group-based access activity across interconnected AWS managed applications so that you can align better with regulatory and sovereignty requirements.

What’s new with Amazon Redshift

Want to learn more about the most recent features launched in Amazon Redshift? Refer to Amazon Redshift announcements at AWS re:Invent 2023 to enable analytics on all your data to learn about all of the Amazon Redshift launch announcements made at 2023 AWS re:Invent


About the Author

Mia Heard is a product marketing manager for Amazon Redshift, a fully managed, AI-powered cloud data warehouse with the best price-performance for analytic workloads.