AI and Data
Conference
27 SEPT, 2023 | KILKENNY
Thank you for joining us at the AWS AI and Data Conference 2023
The AWS AI and Data Conference 2023, took place on the 27th of September 2023 in the Lyrath Convention Centre, Kilkenny, Ireland. At this event, attendees learnt about the most cutting-edge machine learning tools, walking away with strategies to build future-proof applications, and bring more organisation to their data-driven endeavors.
There were 4 session tracks, 1 workshop, and 12 AWS demos on the day. Full agenda, session recordings and slides can be found below.
Registration is now closed
Featured Speakers
DR. WERNER VOGELS
Chief Technology Officer at Amazon.com
Dr. Werner Vogels is Chief Technology Officer at Amazon.com where he is responsible for driving the company’s customer-centric technology vision. As one of the forces behind Amazon’s approach to cloud computing, he is passionate about helping young businesses reach global scale, and transforming enterprises into fast-moving digital organisations.
Vogels joined Amazon in 2004 from Cornell University where he was a distributed systems researcher. He has held technology leadership positions in companies that handle the transition of academic technology into industry. Vogels holds a PhD from the Vrije Universiteit in Amsterdam and has authored many articles on distributed systems technologies for enterprise computing.
MIRIAM MCLEMORE
AWS Enterprise Strategist
In business and technology leadership positions throughout her 25-year career with The Coca-Cola Company, and now at Amazon Web Services (AWS), Miriam has consistently driven high impact global enterprise technology strategy, digital transformation, and data analytics to understand and engage the consumer, provide competitive advantage, and improve internal system efficiencies.
In diverse roles at Coca-Cola, she led top-tier strategy and development teams across 30 major global markets; identified and built mutually productive technology partnerships with external companies including Adobe, AWS, Facebook, Google, Box and VCs; delivered platforms from incubator and VC backed startups to large global business solutions; and led portfolio reviews, M&A due diligence/integration, and significant investment decisions.
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Event Agenda
| 45 mins | Keynote | |||
| Track 1 - Get started: Moving your data to the cloud | Track 2 - Building apps with modern databases | Track 3 - Get started: Building your data lake | Track 4 - Analyzing and getting insights | |
| 40 mins | Migrate your Oracle and SQL Server databases to Amazon RDS (200) | Which database to choose: Pick the right purpose-built database for the job (200) | How to go from zero to data lake in days (200) | Amazon Redshift use cases and deployment patterns (400) |
| Migrate your on-premises Data Warehouse to Amazon Redshift (200) | Building large scale data-driven apps with AWS databases (300) | Picking the right analytical engine for your needs (200) | Processing Big Data with Hadoop, Spark, and other frameworks in Amazon EMR (300) | |
| 40 mins | Why cloud databases like Amazon Aurora are more scalable and reliable (300) | Extreme Performance at Cloud Scale: supercharge your real-time apps with Amazon ElastiCache (300) | Breaking the silos: Extending your DW to your data lake (300) | Scalable, secure log analytics with Amazon Elasticsearch Service (200) |
| Deploying open source databases on AWS (200) | Databases for building business-critical enterprise apps (300) | Big data in the era of heavy privacy regulations (200) | Scalable, secure log analytics with Amazon Elasticsearch Service (200) | |
| 40 mins | Why cloud databases like Amazon Aurora are more scalable and reliable (300) | Extreme Performance at Cloud Scale: supercharge your real-time apps with Amazon ElastiCache (300) | Breaking the silos: Extending your DW to your data lake (300) | Scalable, secure log analytics with Amazon Elasticsearch Service (200) |
| 50 mins | Customer spotlight 1: How iRobot built the Roomba to use real-time data to smartly clean your home - 45 min or Customer spotlight 2: Equinox’s Data Warehouse modernization journey - 45 min Conclusion - 5 min | |||
Programme
Main Plenary
09:00am – 9:20am
Welcome
Speaker
- Mark Dunleavy - Head of Commercial in Ireland, AWS
09:20am – 10:05am
Using AI to tackle our planet's most urgent problems
In this keynote, Dr. Werner Vogels sheds light on global applications of AI, through the lens of UN SDGs relating to climate, hunger and health. Dr. Vogels will share perspectives on the data and hardware underpinning today's AI technologies, and the benefits of democratized access. With a focus on the Global South and impact-native organizations, the talk will cut through the noise surrounding recent advances to look at the positive impact AI is making right now on society and environment. Acknowledging the need for continued stewardship and responsibility, Dr. Vogels encourages increasing co-operation between government, industry, and enterprise. The keynote will end with a call-to-action for the audience - first find the data, then design the AI approach.
Speaker
- Dr. Werner Vogels, Chief Technology Officer at Amazon.com
10:05am – 10:40am
Game Changers
Generative AI is increasingly a point of focus globally. Done right, your data can be your differentiator in delivering generative AI applications that meet your specific business and customer needs. Leaders play a critical role in enabling this innovation by removing blockers including siloed data, outdated governance, skilling, and legacy operating models. In this session, Miriam McLemore, current AWS Enterprise Strategist and former Corporate CIO of The Coca-Cola Company, will discuss strategies that help leaders maximize the value of generative AI by starting with the right data foundations.
Speakers
- Miriam McLemore, Director of Enterprise Strategy, AWS
10:40am – 11:10am
Tea/Coffee & Networking
11:10am – 11:45am
Generative AI - Making it real in the organisation
Generative AI has taken world by storm and has democratised innovation across the organization bringing potentially huge efficiencies and new opportunities. How do organizations capitalise on the generative AI wave and at the same time ensure that they have the correct checks and balances in place.
Taking lessons learned from Amazon's own experiences of innovating and managing with Generative AI, we will discuss how to ensure value creation is balanced with adequate risk management, organisational alignment and the capabilities your organization needs for success.
Speaker
- Richard Jones, AWS Enterprise Technologist, AWS
11:45am - 12:05pm
Unlocking customer insights in 3 weeks: Driving increased NPS with Amazon generative AI
Generative AI is revolutionising the way businesses harness their data. Informa, who deliver hundreds of international market-leading events, sought a method to scale understanding customer feedback. Discover how, working with Firemind and AWS, they used generative AI to surface insights from extensive customer feedback, to reveal actionable strategies that will increase event Net Promoter Scores (NPS) and customer satisfaction.
Speaker
- Ahmed Nuaman, Managing Director, Firemind
- Angus Turner, Head of Operational Performance, Informa Markets
12:05pm – 12:25pm
GenerativeBI: Self-service analytics
Natural Language Query supported by Large Language Models allows everyone in your business to make data driven decisions. We’ll show how Amazon QuickSight, the AWS service for data visualisation, supports self-service analytics at scale and how GenerativeBI opens a new era for data driven insights.
Speakers
- Neal Cauley, Principal WW GTM Lead Quicksight, AWS
12:25pm – 12:45pm
Generative AI for customer service with Amazon Connect
Generative AI is changing the way companies deliver impactful customer experiences. Today’s innovative solutions use a combination of AI services that can provide omnichannel self-service capabilities, assist agents with recommendations that resolve issues faster, and uncover real-time and post-call insights into customer conversations.
Speaker
- Peter Trimble, Senior Solutions Architect, AWS
Breakout tracks
Session Details
- Track1 Session 1
- Track2 Session 1
- Track3 Session 1
- Track4 Session 1
- Track5 Session 1
- Track6 Session 1
- Track7 Session 1
- Track8 Session 1
- Track9 Session 1
- Track10 Session 1
Track1 Session 1
Demo 1 - GenAI - Intelligent Document Processing
Track 2 - Building apps with mordern databases
9:00 AM - 10:00 AM PT
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Track 3 - Get started: Building your data lake
9:00 AM - 10:00 AM PT
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Track 4 - Analyzing and getting insights
9:00 AM - 10:00 AM PT
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Track2 Session 1
Demo 1 - GenAI - Intelligent Document Processing
Automate document processing with AWS Artificial Intelligence (AI) services. Extracting information from complex content in any document format such as insurance claims, mortgages, healthcare claims, contracts, and legal contracts.
Demo 2 - GenAI - Code Whisperer
Build applications faster and more securely with your AI coding companion in your IDE, Sagemaker Studio, Lambda console, and Glue Studio.
Demo 3 – GenAI - Image and Video Generation
Stable Diffusion is a powerful deep learning model for generating detailed images from text descriptions. This demo showcases its capabilities in text-to-image and image-to-image generation, masking, and finetuning a model using Amazon Bedrock and Amazon SageMaker Foundation Models. It also includes moderation features using AWS AI services Rekognition and Comprehend.
Demo 4 - GenAI - Conversation Q&A
Explore conversation search utilising Large Language Models (LLM) and Amazon Kendra an intelligent search service. Explore use cases in developer support of AWS services, tax questions, and clinical trial use cases.
Demo 5 – Analytics - Generative BI
Learn how you can transform Business Intelligence applications with AI-driven Natural Language Querying using Amazon QuickSight Q
Demo 6 – Analytics - Semantic Search on Amazon Opensearch
Learn to build GenAI powered Semantic search experiences with Amazon Opensearch as a Vector Database.
Demo 7 – Analytics - Redshift ML
Extend the power of your Cloud Data warehouse to share data and collaborate along with building powerful ML applications using standard SQL commands.
Demo 8 – Analytics - Redshift Data sharing
Democratise data across and outside the organisation with data sharing on Amazon Redshift.
Demo 9 – Databases - Aurora Serverless V2
Learn to leverage Aurora Serverless v2 which scales instantly to support even the most demanding applications, autoscaling configuration and Multi-AZ support, Global Database, RDS Proxy, and read replicas capabilities.
Demo 10 – Databases - RDS Proxy for scaling connections and reducing failover time
Learn how to manage large number of open connections to the database server at a high rate, allowing applications to pool and share connections and improving database efficiency and application scalability and failover times.
Demo 11 – Databases - Aurora Machine Learning
Learn how to add ML-based predictions to applications via the familiar SQL programming language using Aurora Machine learning integration with Amazon Aurora.
Track3 Session 1
Tab 3 content
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Track4 Session 1
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Track5 Session 1
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Track6 Session 1
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Track7 Session 1
Tab 7 content
Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.
Track8 Session 1
Tab 8 content
Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.
Track9 Session 1
Tab 9 content
Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.
Track10 Session 1
Tab 10 content
Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.
Multiple City Registration
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Sessions will focus on providing an overview of AWS services and features, with the assumption that attendees are new to the topic Sessions will focus on providing an overview of AWS services and features, with the assumption that attendees are new to the topic Sessions will focus on providing an overview of AWS services and features, with the assumption that attendees are new to the topic Sessions will focus on providing an overview of AWS services and features, with the assumption that attendees are new to the topic
Session Proficiency Levels Explained
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Level 100
Introductory
Sessions will focus on providing an overview of AWS services and features, with the assumption that attendees are new to the topic
-
Level 200
Intermediate
Sessions will focus on providing best practices, details of service features and demos with the assumption that attendees have introductory knowledge of the topics
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Level 300
Advanced
Sessions will dive deeper into the selected topic. Presenters assume that the audience has some familiarity with the topic, but may or may not have direct experience implementing a similar solution
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Level 400
Expert
Sessions are for attendees who are deeply familiar with the topic, have implemented a solution on their own already, and are comfortable with how the technology works across multiple services, architectures, and implementations
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Featured Speakers
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Raju Gulabani, VP of Databases, Analytics & AI, AWS
Raju Gulabani is VP of Databases, Analytics & AI within AWS at Amazon.com. He is responsible for P&<, product management, engineering and operations for Database services such as Amazon Aurora and Amazon DynamoDB, and Analytics services such as Amazon Redshift and Amazon EMR, as well as AI services like Amazon Lex, Amazon Polly, and Amazon Rekognition. Prior to joining Amazon in his current position in 2010, Raju spent four years at Google and built the Google Apps business (now known as G Suite).Earlier in his career, Raju founded an Intel backed Wi-Fi Voice over IP company as well as held engineering management positions at Microsoft.
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Ryan Kelly, Data Architect, Equinox
Ryan Kelly is a data architect at Equinox, where he helps outline and implement frameworks for data initiatives. He also leads clickstream tracking which helps aid teams with insights on their digital initiatives. Ryan loves making it easier for people to reach and ingest their data for the purposes of business intelligence, analytics, and product/service enrichment. He also loves exploring and vetting new technologies to see how they can enhance what they do at Equinox
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Richard Boyd, Cloud Data Engineer, iRobot
Richard Boyd is a cloud data engineer with the iRobot Corporation’s Cloud Data Platform where he builds tools and services to support the world’s most beloved vacuum cleaner. Before joining iRobot, Richard built discrete event simulators for Amazon’s automated fulfillment centers in Amazon Robotics. His previous roles include cyber warfare systems analyst at MIT and research for the Center for Army Analysis. He holds advanced degrees in Applied Mathematics & Statistics.
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Raju Gulabani, VP of Databases, Analytics & AI, AWS
Raju Gulabani is VP of Databases, Analytics & AI within AWS at Amazon.com. He is responsible for P&<, product management, engineering and operations for Database services such as Amazon Aurora and Amazon DynamoDB, and Analytics services such as Amazon Redshift and Amazon EMR, as well as AI services like Amazon Lex, Amazon Polly, and Amazon Rekognition. Prior to joining Amazon in his current position in 2010, Raju spent four years at Google and built the Google Apps business (now known as G Suite).Earlier in his career, Raju founded an Intel backed Wi-Fi Voice over IP company as well as held engineering management positions at Microsoft.
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Ryan Kelly, Data Architect, Equinox
Ryan Kelly is a data architect at Equinox, where he helps outline and implement frameworks for data initiatives. He also leads clickstream tracking which helps aid teams with insights on their digital initiatives. Ryan loves making it easier for people to reach and ingest their data for the purposes of business intelligence, analytics, and product/service enrichment. He also loves exploring and vetting new technologies to see how they can enhance what they do at Equinox
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Richard Boyd, Cloud Data Engineer, iRobot
Richard Boyd is a cloud data engineer with the iRobot Corporation’s Cloud Data Platform where he builds tools and services to support the world’s most beloved vacuum cleaner. Before joining iRobot, Richard built discrete event simulators for Amazon’s automated fulfillment centers in Amazon Robotics. His previous roles include cyber warfare systems analyst at MIT and research for the Center for Army Analysis. He holds advanced degrees in Applied Mathematics & Statistics.
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Raju Gulabani, VP of Databases, Analytics & AI, AWS
Raju Gulabani is VP of Databases, Analytics & AI within AWS at Amazon.com. He is responsible for P&<, product management, engineering and operations for Database services such as Amazon Aurora and Amazon DynamoDB, and Analytics services such as Amazon Redshift and Amazon EMR, as well as AI services like Amazon Lex, Amazon Polly, and Amazon Rekognition. Prior to joining Amazon in his current position in 2010, Raju spent four years at Google and built the Google Apps business (now known as G Suite).Earlier in his career, Raju founded an Intel backed Wi-Fi Voice over IP company as well as held engineering management positions at Microsoft.
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Ryan Kelly, Data Architect, Equinox
Ryan Kelly is a data architect at Equinox, where he helps outline and implement frameworks for data initiatives. He also leads clickstream tracking which helps aid teams with insights on their digital initiatives. Ryan loves making it easier for people to reach and ingest their data for the purposes of business intelligence, analytics, and product/service enrichment. He also loves exploring and vetting new technologies to see how they can enhance what they do at Equinox
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Richard Boyd, Cloud Data Engineer, iRobot
Richard Boyd is a cloud data engineer with the iRobot Corporation’s Cloud Data Platform where he builds tools and services to support the world’s most beloved vacuum cleaner. Before joining iRobot, Richard built discrete event simulators for Amazon’s automated fulfillment centers in Amazon Robotics. His previous roles include cyber warfare systems analyst at MIT and research for the Center for Army Analysis. He holds advanced degrees in Applied Mathematics & Statistics.
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Raju Gulabani, VP of Databases, Analytics & AI, AWS
Raju Gulabani is VP of Databases, Analytics & AI within AWS at Amazon.com. He is responsible for P&<, product management, engineering and operations for Database services such as Amazon Aurora and Amazon DynamoDB, and Analytics services such as Amazon Redshift and Amazon EMR, as well as AI services like Amazon Lex, Amazon Polly, and Amazon Rekognition. Prior to joining Amazon in his current position in 2010, Raju spent four years at Google and built the Google Apps business (now known as G Suite).Earlier in his career, Raju founded an Intel backed Wi-Fi Voice over IP company as well as held engineering management positions at Microsoft.
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Ryan Kelly, Data Architect, Equinox
Ryan Kelly is a data architect at Equinox, where he helps outline and implement frameworks for data initiatives. He also leads clickstream tracking which helps aid teams with insights on their digital initiatives. Ryan loves making it easier for people to reach and ingest their data for the purposes of business intelligence, analytics, and product/service enrichment. He also loves exploring and vetting new technologies to see how they can enhance what they do at Equinox
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Richard Boyd, Cloud Data Engineer, iRobot
Richard Boyd is a cloud data engineer with the iRobot Corporation’s Cloud Data Platform where he builds tools and services to support the world’s most beloved vacuum cleaner. Before joining iRobot, Richard built discrete event simulators for Amazon’s automated fulfillment centers in Amazon Robotics. His previous roles include cyber warfare systems analyst at MIT and research for the Center for Army Analysis. He holds advanced degrees in Applied Mathematics & Statistics.
Customer Highlights
Epics Games’ entire analytics platform runs on AWS. Billions of game events, like player interactions on the map, their accuracy, damage taken and dealt, and what resources they are using are all sent to AWS.
Epics Games’ entire analytics platform runs on AWS. Billions of game events, like player interactions on the map, their accuracy, damage taken and dealt, and what resources they are using are all sent to AWS.
Epics Games’ entire analytics platform runs on AWS. Billions of game events, like player interactions on the map, their accuracy, damage taken and dealt, and what resources they are using are all sent to AWS.
Epics Games’ entire analytics platform runs on AWS. Billions of game events, like player interactions on the map, their accuracy, damage taken and dealt, and what resources they are using are all sent to AWS.
FAQS
- Where is AWS Innovate hosted?
- What is the price of attending AWS Innovate?
- Who should attend AWS Innovate?
- How do I get the certificate of attendance?
Q: Where is this event?
A: This event is an online event, hosted by AWS on the INXPO platform.
Q: Who should attend this event?
A: Developers building data-driven apps; DBAs and data engineers who are building analytics infrastructure and data pipelines; Analysts and data scientists who are deriving insights that answer complex business quesions and building/trainining machine learning models.
Q: How much does this event cost?
A: There is no cost to attend this event.
Q: What are the prerequisites before attending the event?
A: There are no prerequisites for attending the event. We encourage attendees to browse the Database and Analytics pages on the AWS website to get a brief overview of the services available to them.