On Demand Sessions
Analyze Data Across Your Lake House Architecture with Amazon Redshift (Level 300)
Presentation will be available soon
Organizations can gain deeper and richer insights by bringing together all your relevant data of all structures and types and from all sources to analyze, using Lake House Architecture. You can use Amazon Redshift to query data across Redshift clusters, your S3 data lake, Amazon Aurora, and other operational databases with Redshift Data Sharing, Redshift Spectrum, and Redshift Federated Query. Learn how to enable a lake house architecture on Amazon Redshift.
Access Deeper Insights with Machine Learning (Level 100)
Presentation will be available soon
Learn how your business users can leverage AI/ML capabilities to enhance dashboards and reporting with no coding necessary. Using Amazon QuickSight’s built-in anomaly detection, forecasting, natural language processing, and the newly announced Amazon QuickSight Q, any business user, regardless of technical skill, can ask deeply analytical questions on all of your data and receive answers in seconds. Additionally, integration with Amazon SageMaker opens doors to bring your own predictive models to enrich your data visualizations.
Deliver Better Customer Experiences With Machine Learning in Real-Time (Level 200)
Presentation will be available soon
Organizations are increasingly using machine learning to make near-real-time decisions, such as placing an ad, assigning a driver, recommending a product, or even dynamically pricing products and services. Real-time machine learning can substantially enhance your customers' experience, resulting in better engagement and retention. In this session, you will learn how you can use AWS data streaming platforms to support real-time machine learning.
Find and Alert on Anomalies With ML Features in Amazon Elasticsearch Service (Level 200)
Presentation will be available soon
Many organizations are using Amazon Elasticsearch Service as their centralized infrastructure for Operational Analytics, leveraging its near real-time analytics capabilities and visualizations to monitor and find issues in their critical infrastructure and applications. Coupling the power of search and ML, Amazon ES can alert users of anomalies and issues even faster, enabling them to head off problems before they become acute.
Deploy Lake House Architecture to Enable Self-Service Analytics with AWS Lake Formation (Level 300)
Presentation will be available soon
Being data driven requires ubiquitous access to data in a secure and governed way. In this session you will learn how AWS Lake Formation makes it easy to build, manage, and secure your data lake. We will cover how to set up fine grained access permissions enabling secure access to data from a wide range of services. We will also cover how to update and delete data using Governed Tables and automatically optimize data for better query performance.
Accelerate Apache Spark and Other Big Data Application Development With EMR Studio (Level 300)
Presentation will be available soon
Amazon EMR is the industry-leading cloud big data platform for processing vast amounts of data using open source tools such as Apache Spark and Presto. In April, we released EMR Studio, a new integrated development environment for data scientists to develop, visualize, and debug applications written in R, Python, Scala, and PySpark. Join this session to learn how to use EMR and EMR Studio to accelerate your big data work.
Data Modernization eBook
Learn about the benefits of migrating your data infrastructure from on-premises to the cloud.
Modern Analytics Architecture eBook
Discover what a data-driven organization looks like, how to define your data strategy, keys to scaling machine learning, and the five steps to modernizing your data in this playbook.