How can data governance accelerate your business initiatives?

How can you use existing enterprise capabilities to
build your data governance roadmap and secure funding?

In this data governance master class, Kevin Lewis guides you
through common mis-steps, and provides proven best practices.


Download your master class guide for the videos below.

Excepteur sint est non

Quis Nostrud laboris Exercitation ullamco

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea. commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

At vero eos et accusamus et iusto odio dignissimos ducimus qui blanditiis praesentium voluptatum deleniti atque corrupti quos dolores et quas molestias excepturi sint occaecati cupiditate non provident, similique sunt. culpa qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio. Nam libero tempore, cum soluta nobis est eligendi optio cumque nihil impedit quo minus id quod maxime placeat facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet ut et voluptates repudiandae sint et molestiae non recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat

  • At vero eos et accusamus et iusto odio dignissimos
  • Ducimus qui blanditiis praesentium voluptatum Deleniti
  • atque corrupti quos dolores et quas Molestias excepturi
  • sint occaecati cupiditate non Provident, similique
  • sunt culpa qui officia deserunt Mollitia animi, id est laborum et dolorum fuga
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

Need a reminder to review the virtual master class guide and videos? Copy and paste the details below into your calendar. If you plan on reviewing the guide and all the recordings, we recommend scheduling a full hour for review.

How can data governance accelerate your business initiatives? How can you use existing enterprise capabilities to build your data governance roadmap and secure funding? Watch this introductory virtual master class with expert, Kevin Lewis, to guide you through common mis-steps and learn proven best practices: https://www.youtube.com/watch?v=2gQGOztkvMI&list=PLhr1KZpdzukfWyXL8pfR6TPEZvHahr7iV

Hungry for more? Check out our library of on-demand data governance master classes here: https://pages.awscloud.com/GLOBAL-devadopt-DL-Data-governance-master-class-2023-learn.html

You can pick and choose the videos most important to you, or watch them all in order (recommended). Make sure to download the master class guide for extra templates and resources, too.

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

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

Nulla eleifend felis vitae velit tristique imperdiet. Etiam nec imperdiet elit. Pellentesque sem lorem, scelerisque sed facilisis sed, vestibulum sit amet eros.

Track4 Session 1

Tab 4 content

Integer ultrices lacus sit amet lorem viverra consequat. Vivamus lacinia interdum sapien non faucibus. Maecenas bibendum, lectus at ultrices viverra, elit magna egestas magna, a adipiscing mauris justo nec eros.

Track5 Session 1

Tab 5 content

Nulla eleifend felis vitae velit tristique imperdiet. Etiam nec imperdiet elit. Pellentesque sem lorem, scelerisque sed facilisis sed, vestibulum sit amet eros.

Track6 Session 1

Tab 6 content

Integer ultrices lacus sit amet lorem viverra consequat. Vivamus lacinia interdum sapien non faucibus. Maecenas bibendum, lectus at ultrices viverra, elit magna egestas magna, a adipiscing mauris justo nec eros.

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.

Watch our videos

  • What is data governance?

    Play button for Class 1: What is data governance?

    Learn why business and IT need to work together, and how Amazon's working backwards method can help you.

  • How do we align with business initiatives?

    Play button for class 2: How do we align with business initiatives?

    Align to funded business initiatives. Determine what data is needed for those business initiatives.

  • What is a good model for data governance?

    Play button for class 3: What is a good model for data governance?

    Use data governance capabilities that help you curate the best data, understand the context of that data, and protect it across the lifecycle.

  • How do we plan a data governance roadmap?

    Play button for class 4: How do we plan a data governance roadmap?

    Identify funded business initiatives and how their data requirements will overlap. Don't forget to establish fit-for-purpose guardrails.

  • How can we distribute data governance responsibilities?

    Play button for class 5: Which roles do we need?

    Balance centralized capabilities with decentralized responsibilities to increase speed and agility. 


  • How can we use the enterprise operating model?

    Play button for class 6: How can we use the enterprise operating model?

    Leverage enterprise capabilities for strategic planning to promote your successes and plan future projects.


  • Does self-service analytics relate to data governance?

    Play button for class 7: Does self-service analytics relate to data governance?

    Enable self-service while establishing coherent, trustworthy analytics and reducing wasteful reinvention.


  • Does ML governance relate to data governance?

    Play button for class 8: Does ML governance related to data governance?

    Use good quality data in your ML models. Plan and manage various aspects of model building, deployment, monitoring, and more. 

  • How can AWS help with data governance?

    Play button for class 9: Does AWS have tools for data governance?

    Choose tools that support your data governance model: curate, understand, and protect. AWS has services that support your strategy.

  • JAN 21 2020
    Sunt in Culpa
  • JAN 21 2020
    Sunt in Culpa
  • JAN 21 2020
    Sunt in Culpa
  • JAN 21 2020
    Sunt in Culpa
  • JAN 21 2020
    Sunt in Culpa
  • JAN 21 2020
    Sunt in Culpa

Please complete the form to download your training guide.

Image of master class program guide cover.

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

  • 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

  • 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

  • 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

Quis Nostrud Exercitation

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.

Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est. laborum.

Excepteur Sint Occaecat Cupidatat

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

About your instructor, Kevin Lewis



As a Global Practice Principal for data analytics at AWS Professional Services, Kevin Lewis guides customers through the entire data analytics journey, from planning and organizing to building and deploying. He brings nearly three decades of expertise in managing large-scale data initiatives. Prior to joining AWS, Kevin was a director of the data strategy and governance practice at Teradata. His career began at Publix Super Markets, where he started as a bagger in high school and, several steps later, led Publix’s data management program, spearheading the planning and development of an enterprise-wide data analytics ecosystem.

Headshot of instructor Kevin Lewis

Featured Speakers

  • 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.

  • 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.

  • 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.

  • 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

Epic Logo Image

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

Yelp Logo Image

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.

Yelp

Airbnb Logo Image

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.

Airbnb

Lyft Image

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.

Lyft

FAQS

  1. Where is AWS Innovate hosted?
  2. What is the price of attending AWS Innovate?
  3. Who should attend AWS Innovate?
  4. 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.