Partners

View All Exhibitors

Amazon Web Services

Black Diamond
location1417

Sponsored Sessions

  • Introductory
    Breakout Session
    Technical Executive
    Business Executive
    IT / DBA
    BI / Analyst
    Data Scientist
    Software Developer
    Security Practitioner
    Marketing Practitioner
    Product Manager
    DevOps
    Data Engineer
    MLOps
    Generative AI
    2:00pm - 3:00pm
    Not industry-specific
    2979
    AI & GenAI
    Cortex AI LLMs
    No
    Mon, Jun 2
    All Days
    Not department-specific
    Other (Industry-A)
    AI & GenAI (Topic)
    BI / Analyst (Role)
    Business Executive (Role)
    Data Engineer (Role)
    Data Scientist (Role)
    IT / DBA (Role)
    Marketing Practitioner (Role)
    Product Manager (Role)
    Security Practitioner (Role)
    Software Developer (Role)
    Technical Executive (Role)
    OnDemand
    2:00 p.m. Monday, Jun 02
    Monday, Jun 02

    Experience the next evolution of AI with Amazon Nova, a groundbreaking suite of foundation models that's redefining what's possible. With exceptional multi-modal capabilities across 200+ languages and seamless integration with Amazon Bedrock, Alexa+ and Amazon Q. Nova helps organizations transform customer experiences and streamline operations.

    Join us to explore how leading companies are leveraging Nova's unmatched price performance to turn cutting-edge AI into real-world success stories. Learn how Snowflake data users and engineering teams can build generative AI applications using Snowflake and Amazon Nova powered by Amazon Bedrock.

  • Intermediate
    Hands-on Lab
    Technical Executive
    IT / DBA
    Data Scientist
    Software Developer
    Product Manager
    DevOps
    Data Engineer
    MLOps
    Data Engineering & Streaming
    1:00pm - 2:00pm
    Not industry-specific
    2975
    Data Engineering & Pipelines
    AI & GenAI
    Streamlit in Snowflake
    No
    Tue, Jun 3
    Wed, Jun 4
    All Days
    Not department-specific
    Other (Industry-A)
    AI & GenAI (Topic)
    Data Engineering & Streaming (Topic)
    Data Engineer (Role)
    Data Scientist (Role)
    IT / DBA (Role)
    Product Manager (Role)
    Software Developer (Role)
    Technical Executive (Role)
    1:00 p.m. Wednesday, Jun 04
    1:00 p.m. Tuesday, Jun 03
    Tuesday, Jun 03
    Wednesday, Jun 04

    Organizations have various streaming use cases where they need to ingest unstructured data — such as customer reviews or social media comments in text or JSON format — into a lakehouse. Before storing this data in database tables, they often want to process it in real time using generative AI capabilities, such as fraud analysis, sentiment analysis and summarization.

    This hands-on lab provides step-by-step guidance on building an end-to-end data pipeline using Amazon Bedrock, Amazon Managed Service for Apache Flink, Amazon Data Firehose and Snowflake.

    • Speakers

    Headshot of Nithyashree Alwarsamy

    Nithyashree Alwarsamy

    Partner Solutions Architect

    Amazon Web Services, Inc.

    Nithyashree Alwarsamy is a Partner Solutions Architect at Amazon Web Services, specializing in data and analytics solutions with a focus on Snowflake. With the strong background in cloud architecture and data engineering, Nithyashree works closely with Snowflake and joint customers to design scalable, secure and cost-effective data platforms on AWS. Leveraging deep expertise in modern data architectures, Nithyashree helps organizations unlock the full potential of their data by integrating Snowflake's cloud-native data platform with the breadth of AWS services.

    Headshot of Matt Dinger

    Matt Dinger

    Global Epic Leader

    AWS

    Experienced leader with a proven track record for developing high performing teams, creating results-oriented processes driving consensus in high pressure and competitive environments, and ensuring successful customer outcomes in an international business unit. Recognized for effective communication at all levels of an organization, consistently achieving financial targets, and making informed decisions with imperfect information.