Join us in Miami
You're invited to join us in person for this one-day event on Thursday October 12, or Friday, October 13, at Miami Marriott Biscayne Bay. AWS experts will give you an in-depth look at the value of data and how you can implement a modern data strategy.
✉️ You can also invite a colleague! Click here to share.
About the event
Exabytes of data are being generated every single day. Because data is vast, dynamic, and comes in different formats, extracting value from it can be challenging. Harnessing the full potential of data requires an end-to-end modern strategy. To discover insights like customer churn rates, organizations need to unify different types of data in a data lake where they can use tools to analyze data and build dashboards to drive insights. They can use data to fuel machine learning too, creating better customer experiences and improving operational efficiency.
Join AWS technical specialists as they take you on a journey of how an online service provider uses data to investigate a decline in customers, ultimately discovering an action they can take to improve their own processes. While on this journey, you will learn about key services to build your data foundation on AWS and gain valuable hands-on experience working backwards from a real-world customer problem.
Who should attend?
Business analysts, data analysts, data engineers, and IT professionals who are curious about how to use multiple AWS services together to create an end-to-end solution to a business problem, such as customer churn.
This will be a hands-on keyboard event where you will be reading and running code. Come solo or bring your team to build collaboratively! However, space is limited and all attendees must register.
Why should I attend?
At this event, you will:
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Gain hands-on experience with multiple AWS services to solve a business challenge
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Use advanced analytics to gather insights about customers
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Architect a solution on AWS
After the event, we will email attendees a Certificate of Attendance.
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100,000+ databases migrated to AWS 10,000+ data lakes and data warehouses deployed on AWS Hundreds of thousands of customers rely on AWS Databases
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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 |
Agenda
Registration
9:00 AM - 10:00 AM ET
- Registration opens at 9:00 AM.
Welcome and Introduction
10:00 AM - 10:10 AM ET
- To kick off the event, we will start with an overview of goals for the day.
Business Challenge
10:10 AM - 10:30 AM ET
- In this session, we will dive into the business challenge we're architecting a solution for throughout the event.
Querying the Data Lake
10:30 AM - 11:00 AM ET
- Next, we will cover storing data in Amazon S3, registering data with AWS Glue Data Catalog, and querying data with SQL.
Break
11:00 AM - 11:15 AM ET
- Sessions to resume at 11:15 AM
Lab 1
11:15 AM - 11:30 AM ET
- In this hands-on lab, we'll cover adding data to Amazon S3, cataloging it with AWS Glue, and querying it with SQL via Amazon Athena.
Data Visualization
11:30 AM - 12:00 PM ET
- Next, we'll cover creating visualizations of data in Amazon S3.
Lunch
12:00 PM - 1:00 PM ET
- Lunch will be provided at the venue. Sessions to resume at 1:00 PM.
Lab 2
1:00 PM - 1:20 PM ET
- In this next lab, we'll cover creating visualizations and analyses with Amazon QuickSight.
Streaming Data
1:20 PM - 1:40 PM ET
- In this session, we'll cover collecting streaming data into a streaming data system, and persisting the data.
Lab 3
1:40 PM - 1:55 PM ET
- In our third lab, we'll cover acquiring data into Amazon Kinesis Data Streams and persisting it to Amazon S3 via Amazon Kinesis Data Firehose.
Data Enrichment
1:55 PM - 2:15 PM ET
- In our next lab, we'll cover acquiring data into Amazon Kinesis Data Streams and persisting it to Amazon S3 via Amazon Kinesis Data Firehose.
Break
2:15 PM - 2:30 PM ET
- Sessions to resume at 2:30 PM.
Lab 4
2:30 PM - 3:00 PM ET
- In this lab, we'll use an AWS Lambda function to read data from Amazon S3, extract sentiment and key phrases with Amazon Comprehend, and store it back to Amazon S3.
Data Insights
3:00 PM - 3:15 PM ET
- In this session, we will cover querying enriched data with SQL, and creating visualizations of enriched data.
Lab 5
3:15 PM - 3:30 PM ET
- Our final lab of the day will cover querying enriched data in Amazon S3 and creating analyses in Amazon Quicksight to illustrate insight into customer sentiment.
Wrap-Up and Next Steps
3:30 PM - 4:00 PM ET
- As we wrap up our day of learning, we'll share some resources for you to utilize until next time.
Networking Happy Hour
4:00 PM -5:00 PM ET
- Join us for an on-site happy hour for refreshments, networking, and one-on-one time with our AWS technical specialists.
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
Migrate your Oracle and SQL Server databases to
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.
Track2 Session 1
Migrate your Oracle and SQL Server databases to
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.
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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Compass UOL is a global digital transformation company that designs and builds digital-native platforms with cutting-edge technologies to help businesses innovate and thrive in their industries. As a long-term AWS partner, Compass UOL utilizes AWS solutions and services to deliver successful products to large global clients and have recently provided best-in-class training as they led the Data-Driven Everything event in Brazil for top professionals and C-Level executives.
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
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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
✉️ Invite a colleague! Click here to share.
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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.
-
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.
-
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
-
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.
-
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.
-
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
-
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.