With the explosive data growth in the last 10 years, organizations are moving from monolithic applications to microservice architectures where they need to break down applications into smaller workloads. Adapting to this change, developers need to build on a solid, modern data platform to help address scalability, efficiency, performance, and total cost of ownership. AWS databases are purpose-built for modern applications, enabling developers to increase efficiency by using the right tool for the right job. In this session, review the portfolio of NoSQL databases that are optimized for specific data models (key-value, document, in-memory, and graph) and access patterns based on use cases to help you build modern applications on AWS.
In this session, see how to easily and securely connect Amazon SageMaker Studio notebooks to Amazon EMR to ...
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In this session, learn how AWS solutions can help along the data lifecycle, and hear customer stories of our top use cases.
In this session, learn about Amazon’s peculiar culture and how we innovate through four distinct, yet interdependent, elements: culture, mechanisms, architecture, and organization.
Join this session to learn strategies rooted in the first-hand experience of former CXOs on how to overcome these barriers to turn this vision into a reality.
Learn how AWS and Amazon have developed mechanisms for applying data and analytics to create scalable business efficiencies and address our customers’ most complex challenges.
In this session, tailored for business leaders, AWS enterprise strategists share how organizations can apply AI and ML to realize their futures.
In this chalk talk, dive into the mechanisms and mental models that help Amazon and AWS make high-velocity and high-quality decisions.
In this session, tailored for senior business and technology decision makers, learn about the approach Amazon.com takes to build and scale ML-enabled innovations.
In this session, explore the people and process considerations for building a modern data strategy.
Join this session to hear about emerging trends that AWS is seeing in the analytics market. These trends revolve around data ethics, new architectural patterns, data exchanges, and governance.
In this session, learn how AWS data storage, database, analytics, and machine learning technologies can help you use data to drive business outcomes.
Learn how to share data in a well governed way across your organizations and regions and through the external data exchange with the latest Amazon Redshift data sharing features.
Learn how AWS can help you invent new experiences, predict the future, optimize processes, and reduce costs with AI/ML.
Join this session if your organization is eager to embark on its digital transformation but is unsure how to get started with minimal business disruptions.
Learn how to get started with analytics in seconds with new serverless options in Amazon EMR, Amazon Redshift, Amazon MSK and Amazon Kinesis.
This session dives into the architecture and features of Amazon Aurora that provide developers a MySQL- and PostgreSQL-compatible database service without the typical database management overhead.
In this talk, learn what OpenSearch does, how to use it with popular open-source services, how you can use it on and off AWS, & how you can participate to make it perfect for your particular use case.
In this session, see how to easily and securely connect Amazon SageMaker Studio notebooks to Amazon EMR to infer from real-time Amazon Kinesis data streams.
In this session, learn about AWS programs, tools, and best practices for migrating your critical applications to the cloud, and discover the business value offered by AWS technologies.
Machine learning (ML) is driving innovation through more accurate predictions, reduced operational overhead, and improved customer experiences.