AWS re:Invent 2024 - Analytics
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Table of Contents
Analytics
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This talk discusses the unification of insights from structured and unstructured data using Amazon Q and Amazon QuickSight. It highlights the key features and benefits of this integration, showcasing how it can help organizations streamline data analysis, enhance productivity, and make more informed decisions.
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This panel discussion explores how leading organizations in healthcare, finance, and logistics are leveraging Generative AI to drive innovation in data analytics and governance. The panelists share their experiences in overcoming data silos, embedding governance into workflows, and embracing bold, 'magical' use cases to stay ahead of the rapid pace of AI advancements.
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This talk discusses how AWS provides solutions for modern data architecture, including data sharing, data mesh, and the new SageMaker Unified Studio. The speakers cover the challenges of data silos and fragmented governance, and showcase how AWS services like Glue Data Catalog, Redshift Data Sharing, and SageMaker Lakehouse can address these issues and enable seamless and secure data sharing within and across organizations.
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The video discusses the cost-effective data processing capabilities of Amazon EMR, highlighting innovations in scalability, performance, and ease of use. The presenters share Roblox's journey in leveraging EMR for their large-scale data processing needs and the strategies they employed to optimize costs, such as using instance diversification, spot instances, and automated job and cluster tuning.
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This presentation introduces Amazon QuickSight's new Scenario Analysis feature, which simplifies complex business problem-solving by leveraging AI to automatically suggest analysis approaches, generate insights, and enable self-service exploration for business users. The presentation showcases how Scenario Analysis can drive efficiency and empower non-data-literate users to make data-driven decisions, as demonstrated through use cases from Rehrig Pacific Company and GoDaddy.
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This video discusses the innovations in AWS analytics, including zero-ETL and data integrations. The presentation covers the benefits of zero-ETL, such as simplified data pipelines, reduced operational overhead, and improved data latency, as well as customer use cases and the journey of Motive Technologies in adopting this technology.
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This presentation highlights the latest updates and innovations in Amazon QuickSight, including core business intelligence features, pixel-perfect reporting, embedded analytics, administration and workflow automation, and the integration of Amazon Q for natural language querying and generative AI-powered data storytelling. The session covers QuickSight's unique architecture, cost optimization, and governance capabilities, as well as new pricing models and a growing community of experts.
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The session discusses various data ingestion strategies and patterns using AWS services, focusing on seamless integration into data warehouses, data lakes, and log/search analytics engines. Key highlights include leveraging zero-ETL integrations, optimizing ingestion for batch and streaming data, and implementing best practices for reliable and cost-effective data ingestion architectures.
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The video discusses the benefits of migrating to Amazon QuickSight, a unified and scalable business intelligence platform, including significant cost savings, increased user adoption, and improved performance. The presenters share best practices and lessons learned from the migration journeys of Whole Foods Market and Itau Unibanco, highlighting the importance of executive sponsorship, phased implementation, and leveraging AWS resources.
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The video covers the launch of new features in AWS DataZone, a service for cataloging, discovering, sharing, and governing data across an organization. The presentation also includes customer stories from Cisco and The Weather Company on how they have used DataZone to address data silos, governance challenges, and enable self-service data access for their teams.
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AWS announced the launch of Amazon SageMaker Lakehouse, a unified data management platform that combines the flexibility of data lakes and the performance of data warehouses, enabling seamless access to data across different storage options and query engines through Iceberg-compatible APIs.
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This talk explores how AWS can help organizations revolutionize self-service analytics, empowering every team to become data experts. The presentation covers key building blocks of self-service analytics, such as zero-ETL integrations, unified data platforms, and generative business intelligence tools, demonstrating how AWS services can democratize data insights and drive innovation across an organization.
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The next generation of Amazon SageMaker introduces the SageMaker Unified Studio, a unified development environment for data processing, SQL analytics, machine learning, and generative AI app development, along with the SageMaker Catalog for data governance and the SageMaker Lakehouse for breaking down data silos across an organization's data estate.
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This video discusses the latest innovations in AWS analytics, including data warehousing and SQL analytics. The presentation covers Redshift's price performance, data sharing, Serverless, and the new Lakehouse architecture, as well as Charter Communications' journey in migrating to Redshift.
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This talk covers how Amazon Redshift Serverless and data sharing can enable scalable multi-warehouse architectures, allowing organizations to leverage AI-powered compute scaling and seamless data sharing to transform raw data into actionable insights in real-time. The session also includes real-world examples from Hilton on how they used these capabilities to build a high-performance, cost-effective, and scalable data platform to support their business needs.
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This video discusses the new innovations in AWS analytics and data processing services, including the SageMaker Unified Studio, improved performance and cost-efficiency in services like EMR and Athena, and how Bridgewater, a systematic global macro asset manager, leverages these tools to solve their data processing challenges at scale.
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This session discusses how AWS is scaling its data foundation capabilities to meet the demands of building generative AI applications. It covers various aspects such as processing unstructured data, vector data management, data integration, and data governance, as well as a real-world use case from Amazon Finance on how they leveraged the data foundation to enhance their data mesh with generative AI features.
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This presentation covers the benefits of using a multi-cluster architecture with Amazon Redshift, including improved workload isolation, scalability, and cost optimization. The speakers provide real-world examples from GE Aerospace's journey in adopting Redshift's multi-cluster capabilities to meet the growing demands of their data and analytics workloads.
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AWS QuickSight is a unified business intelligence service that delivers a variety of BI formats, including modern dashboards, pixel-perfect reporting, and augmented analytics with generative AI capabilities. Opendoor, a customer, shares their journey in migrating to QuickSight, highlighting the benefits of self-serve analytics, cost savings, and improved data governance.
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The video presents a comprehensive overview of how AWS QuickSight can help organizations scale business intelligence (BI) to all users. It showcases QuickSight's features, deployment practices, and customer success stories, highlighting the platform's ability to enable data-driven decision-making across the enterprise.
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This session provides a comprehensive overview of how customers can modernize their data warehouses using Amazon Redshift. The session features real-world case studies from Zalando and ADP, highlighting their successful migrations to Redshift and the benefits they have achieved, such as improved performance, scalability, and cost optimization.
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This session explores strategies to optimize costs and improve efficiency for log analytics and search workloads using Amazon OpenSearch Service. The presenters discuss techniques like vector quantization, OpenSearch Serverless, and Amazon OpenSearch Ingestion Service to help customers reduce costs and improve performance.
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This session discusses strategies for building highly performant data solutions using serverless analytics services like Amazon Redshift, Athena, OpenSearch, and Glue. The speakers share real-world examples and best practices for optimizing latency, scalability, efficiency, and cost when designing data architectures for diverse use cases like high-concurrency workloads, real-time intelligence, and self-service analytics.
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This talk showcases how Amazon QuickSight, combined with generative AI capabilities, can empower business analysts and end-users to more effectively build dashboards, ask questions, and tell data-driven stories. The presenters demonstrate how QuickSight and Amazon Q can enable self-service analytics and deliver insights to organizations, using real-world examples from Availity and Anthology.
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Compute
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The video discusses the challenges of operating Apache Kafka and Apache Flink at scale, and how AWS Managed Services for Kafka and Flink can simplify the process by offloading infrastructure management and providing features like automatic scaling, high availability, and cost optimization.
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Data
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HelloFresh's journey to build a scalable, user-centric data platform that powers their growing business and delivers personalized experiences for customers. The talk highlights the challenges they faced, the lessons they learned, and the technical solutions they implemented to transform their data landscape and unlock new business opportunities.
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Data Governance
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The video discusses the importance of data quality and how AWS Glue Data Quality can help organizations build high-quality data products. It also showcases Vanguard's journey in implementing a custom data platform powered by AWS Glue Data Quality to address their data quality challenges.
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Developer Experience
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The session discusses the importance of data lineage, how OpenLineage provides a standard for capturing lineage metadata, and how Amazon DataZone leverages OpenLineage to provide a comprehensive data governance solution. The presenters showcase how DataZone's lineage capabilities can address key data management use cases, such as trust, impact analysis, troubleshooting, and governance.
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This session introduces Amazon Q Developer, a generative AI-powered assistant that simplifies complex data tasks and reduces development time for builders. The session also showcases new capabilities in SageMaker Unified Studio and SageMaker Data Processing that leverage Amazon Q to streamline data integration, SQL querying, and Apache Spark application upgrades.
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This talk discusses how AWS re:Invent 2024 will revolutionize search applications for generative AI, highlighting the advancements in semantic search, conversational interfaces, and the role of OpenSearch in powering these solutions. The speakers from AWS, Adobe, and Freshworks share their experiences and insights on leveraging these technologies to enhance customer experiences and drive business value.
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This session provides an overview of transactional data lakes and how AWS services, such as EMR, Athena, and Glue, support open table formats like Apache Iceberg, Hudi, and Delta Lake to enable efficient data management, performance optimization, and fine-grained access control for modern data architectures.
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The video discusses the challenges of data integration and replication across multiple applications, and introduces AWS's zero-ETL solution to simplify this process. The solution enables seamless replication of data from various SaaS applications into the Amazon SageMaker Lakehouse and Amazon Redshift, providing a unified data access and accelerating insights for customers.
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The session covered how AWS Analytics Services can be used to build a data strategy for AI/ML applications, including ingesting data, processing it, ensuring data quality, and governing the data. It also discussed using AWS Bedrock to enable natural language to SQL translation and leveraging structured data in generative AI applications, as well as how Nexthink built a generative AI-based ticketing system using AWS services.
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The video discusses how AWS QuickSight and Amazon Q can be embedded into applications to enable data monetization and enhanced analytics capabilities. It showcases how two AWS customers, Docebo and aCommerce, have successfully integrated QuickSight and Amazon Q into their products, providing their users with seamless and customizable data visualization and natural language querying experiences.
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The talk covers the importance of a business data catalog in providing context and democratizing access to data. It showcases how AWS services like Glue Data Catalog, DataZone, and SageMaker Data Catalog can help organizations build and manage their enterprise data catalog, enabling technical and business users to discover, understand, and consume data assets.
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This session explores the evolution of data processing, from batch to stream processing, and how modern businesses can accelerate value from their data by leveraging streaming technologies like Amazon Kinesis and Apache Flink. The presenters provide an overview of the challenges with batch processing, highlight the advantages of stream processing, and guide the audience through a sample architecture for migrating from batch to streaming.
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This talk explores how to leverage AWS services and generative AI to build community engagement tools for event planning and promotion. The presenters demonstrate using Amazon Q Business to scrape data, create custom applications, and generate content to streamline the organization of user group meetups and conferences.
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Observability
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The session discusses how Amazon OpenSearch Service can be used to build observability platforms for applications, providing features like high-speed data ingestion, long-term data retention, and powerful analytics capabilities. The speakers share their experiences with migrating to OpenSearch Service and showcase the latest features, including the new OpenSearch UI that consolidates observability data from multiple sources and provides a guided user experience.
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The video discusses the latest innovations in data streaming on AWS, including improvements to performance, cost, availability, and ease of use across services like Amazon Kinesis, Amazon MSK, and Amazon Managed Streaming for Apache Flink. The presentation also features a customer case study from Verizon, highlighting how they were able to address their streaming challenges by migrating to AWS services.
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