Developing a data-driven culture requires a mindset shift. Learn from AWS customer examples and Amazon itself about how to address these challenges and transform your data into a strategic asset.

In this session, tailored to business leaders, AWS Enterprise Strategists share how organizations can embrace AI/ML, along with stories on how some customers use these solutions to achieve profound results.

Machine learning models such as large language models (LLMs) and diffusion models are sparking innovation and are ideal for use cases such as question answering, image generation, code generation, and more. The ever-increasing size and complexity of these models, poses challenges to achieve performance at scale, while keeping costs and power-consumption under control. Learn how AWS Trainium and AWS Inferentia can help you with faster, lower cost, and energy efficient training and deployment of your 100B+ parameter model.

Many organizations are sitting on a treasure trove of data but don’t know how to get value out of it. In this session, you will learn how AWS enables leading use cases of putting data to work.

In this session, learn how companies across industries are using artificial intelligence (AI) to address use cases that create measurable results.

In this leadership fireside chat, Steve Pavlosky, VP of Product Management for GE Digital, discusses ways to maximize the value of data by aligning strategic, technical, and business objectives.

Carrier’s Chief Digital Officer, Bobby George, and AWS Enterprise Strategist, John Clark, talk about earning buy-in for data transformation, evolving a data-centric culture, and how data strategy relates to sustainability.

In this session, learn how the simple integration of Amazon Personalize into your existing websites and marketing systems can create high-value personalization at every touchpoint.

Many organizations have a fragile or inadequate document processing pipeline. In this session, learn how to take advantage of AWS’s latest innovations in AI and ML to process documents efficiently.

In this session, you will learn about AWS Contact Center Intelligence (CCI) and Conversational AI solutions and how to integrate them into your preferred contact center solution.

In this session, we will share how AI services like Amazon Kendra and Amazon Lex can help you build conversational interfaces into any application quickly, with no machine learning expertise required.

In this session, hear how Amazon Connect unlocks AI/ML-powered innovation that offers personalized digital experiences, improved agent productivity, and captures business insights to optimize operational efficiency.

Join this session on predictive maintenance to learn how to prevent downtime in industrial machinery by automatically detecting abnormal behavior and proactively acting on potential failures.

In this session, learn how startup Vale partnered with ClearScale to use modern AI/ML technology to create a new platform for watching movies and TV shows through its Streaming Guide application.

The ML journey requires experimentation. In this session, learn how tools like Amazon SageMaker allow you to experiment faster so you can focus more on refining predictions and less on low-level code.

In this session, explore Amazon SageMaker machine learning operations (MLOps) features and learn how to increase automation and improve the quality of your ML workflows.

Join this session to learn how to increase productivity with SageMaker Studio notebook capabilities, from simplified data preparation to automatic conversion of notebook code to production-ready jobs.

In this session, learn how Amazon SageMaker reduces the time and cost to train and tune large-scale machine learning models without the need to manage infrastructure.

High-performance, cost-effective model deployment is critical to ML return on investment. In this session, learn how to use Amazon SageMaker’s inference abilities to quickly deploy ML models at scale.

Organizations everywhere are using ML to accurately predict outcomes. In this session, you will learn how to use Amazon SageMaker Canvas for cases across sales, marketing, finance, and operations.

In this session, hear how Amazon Omics supports large-scale health and life science analysis and collaborative research with purpose-built data stores, scalable workflows, and multimodal analytics.

In this session, learn how AWS can democratize analytics with ease of use and better price performance, making it easier for analysts and data scientists of all skill levels to use ML.

Learn about how Amazon Redshift, a pioneer in cloud data warehousing, is expanding how cloud data warehousing can deliver insights and grow the business for customers in various industries.

In this session, learn about the latest innovations in AWS Glue, a serverless, scalable data integration service that helps you discover, prepare, move, and integrate data from multiple sources.

This session helps cloud architects, data scientists, and developers design and build modern data streaming architectures that can quickly generate insights by leveraging AWS streaming services.

Learn how to use Amazon OpenSearch Service and Kinesis Data Firehose to set up a serverless solution to manage your log analytics infrastructure so you can focus on what matters most to your business.

Learn how you can use cloud-native business analytics to provide your users with ML-powered interactive dashboards, natural language query, and embedded analytics to provide insights to users at scale.

Do you self-manage open-source Spark, Presto, Elasticsearch, or SOLR solutions? Using AWS tools and best practices to migrate to fully managed and serverless options will save you time and money.

Alex DeBrie, an AWS Hero, will walk you through the key steps and principles that will guide you as you model your data in the DynamoDB database.

Dive deep into the exciting features Amazon Aurora offers, including Aurora Serverless v2 and Global Database. Also, learn about recent innovations that enhance performance, scalability, and security.

In this session, learn about the newest capabilities available on RDS for MySQL: Amazon RDS blue/green deployments, Optimized Writes, and Optimized Reads.

Learn about innovation that delivers 100% performance improvement for Amazon ElastiCache, a fully managed caching service that delivers real-time performance for modern, internet-scale applications.

In this session, learn how you can use open-source relational databases and new technologies, such as key-value, document, and graph, to modernize your applications and enhance their performance.

In this session, learn about the latest Amazon DocumentDB innovations, features, and updates that will push past the scalability limits seen in traditional databases.

This session recaps all noteworthy AWS operational database launches in 2022. These innovations cover three themes: interoperability, performance and scale, and advanced operational techniques.

Come learn how AWS is investing in a zero extract, transform, and load (ETL) future so you can quickly and easily connect to and act on all your data.

In this session, learn how your organization can overcome the challenge of making data available to more people and how AWS makes analytics and machine learning easy for everyone.

Watch a demo on how to transfer data from SAP to a serverless S3 data lake using AppFlow, catalog using AWS Glue, execute queries using AWS Athena, and visualize it on QuickSight.

Learn best practices for optimizing data lake performance on Amazon S3 using storage optimization tools and processes. Then, use your data lake with industry-leading AWS tools to gain data insights.

On-premises data lakes can be complex to migrate. Learn how AWS migration services can help accelerate the transition to a data lake built on AWS quickly and securely.

In this session, you will learn how customers use AWS Data Exchange to streamline their third-party data procurement, ingestion, and management as they implement a modern data architecture.

Learn how to design, build, and operationalize a data mesh architecture on AWS—one that will help navigate data challenges, optimize analytics processes, and deliver insights faster.

Learn how to implement a data and machine learning governance strategy with AWS.  We will also explore Amazon DataZone and new ML governance tools for Amazon SageMaker.

AWS resources can deliver data resiliency to critical systems with options from high recovery point and time objectives to full disaster recovery to address inadvertent changes or other data events.

This session will explain how AWS storage services are designed with built-in resilience, sharing best practices for configuring our storage services for your resilience and high-availability needs.

In this session, learn how AWS is committed to providing the tools, resources, and purpose-built services that customers need to put responsible AI into practice.

Managing data access is essential. In this session, learn successful patterns for implementing access controls at varying levels of granularity and scale to maintain tight control over data.

We will describe how digital sovereignty and data protection requirements are evolving, and describe how these requirements can be met by the technical, legal, and operational controls AWS provides.

In this session, learn how organizations can apply AWS analytics services to discover, access, and share their data across organizational boundaries so it can be accessed for analytics.

1:00pm – 1:30pm PT | 4:00pm – 4:30pm ET

1:30pm – 2:00pm PT | 4:30pm – 5:00pm ET

2:00pm – 2:15pm PT | 5:00pm – 5:15pm ET

2:15pm – 2:35pm PT | 5:15pm – 5:35pm ET

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2:50pm – 3:10pm PT | 5:50pm – 6:10pm ET

3:10pm – 3:25pm PT | 6:10pm – 6:25pm ET

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3:40pm – 3:55pm PT | 6:40pm – 6:55pm ET

3:55pm – 4:10pm PT | 6:55pm – 7:10pm ET

4:10pm – 4:30pm PT | 7:10pm – 7:30pm ET

4:30pm – 5:00pm PT | 7:30pm – 8:00pm ET