AWS Innovate Data Edition
Drive agility, digital transformation, and continuous innovation with your data today.

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 19 August, 2021

Reinvent your business with data

Welcome to AWS Innovate Online Conference - Data Edition, a free virtual event designed to inspire and empower you to make better decisions and innovate faster with your data. Learn how to unlock critical insights from your data and create a strong data foundation for rapid innovation while achieving agility, scalability, and cost-savings.

Build a modern data strategy by modernizing your data infrastructure, unifying your data, and innovating new experiences and re-imagining old processes with AI/ML.


Track 1:

Data-driven organizations

Track 2:

Modernize data infrastructure: Data movement & management

Track 3:

Modernize data infrastructure: Databases

Track 4:

Unify your data: Accelerating insights

Track 5:

Innovate with analytics & ML

 Why attend?

Join us as we feature AWS latest announcements, technologies, and innovations. Dive deep into business use cases, architectural, and modernization best practices.

 Who should attend?

Whether you are getting started with AWS, an advanced user, a business executive, or simply curious, we have a specific track for your level of experience and job role.


Agenda

Get inspired and learn how you can use data to accelerate innovation and drive greater agility and efficiency for your organization. Dive deep into any of the 50+ business and technical sessions led by AWS experts as they share key concepts, business use cases, and best practices to help you save time and costs managing data, eliminate data silos, gain accurate insights faster, and build a strong data foundation for rapid innovation. Don’t forget to prepare your questions and get them answered live by our AWS experts.

Agenda overview
 Download Agenda at a Glance »

Select a Track:

  • Opening keynote: Reinventing business with data
  • Data-driven organizations
  • Modernize data infrastructure: Data movement & management
  • Modernize data infrastructure: Databases
  • Unify your data: Accelerating insights
  • Innovate with analytics & ML
  •  Korean
  •  Japanese
  •  Indonesian
  • Opening keynote: Reinventing business with data
  • ico-innovate-data-keynote

    Opening keynote: Reinventing business with data

    Reinventing business with data (Level 100)

    Effective leaders rely on data to make informed decisions, look around corners, and take meaningful action. They build a modern data strategy to deliver insights to the people and applications that need it, securely and at any scale. Uncover the latest in database, data, analytics and AI/ML and get insights on how organizations are harnessing the power of data to accelerate innovation in their businesses. Jumpstart and build the modern data strategy that allows you to consolidate, store, curate, and analyze data at any scale, as well as share data insights with everyone who needs them.

    Speaker: Rahul Pathak, Vice President of Analytics, AWS
    Duration: 60mins

  • Data-driven organizations
  • ico-innovate-data-reinventing_your

    Data-driven organizations

    About the track

    Get inspired and learn how organizations are using AWS to solve business challenges, optimize business performance, and innovate faster. Start leveraging your data as a strategic asset and reinvent your business with data today.

    Building a smarter, faster business with a modern data strategy (Level 100)
    Data is at the core of every business and organizations to make informed decisions, look around corners, and take meaningful action. Building a data strategy is imperative and pivotal for businesses and organizations to stay relevant now, and in the future. This session covers across various industries how our customers have learnt and experimented over the past months using agile technology to unlock insights from their data and champion a culture of innovation to build for the future. Learn how modern data strategy inspires business innovation, transforms customer experiences, and improves business outcomes.

    Speaker: Olivier Klein, Lead Technologist, APJ, AWS
    Duration: 45mins


    Transform your data approach - Develop your modern data strategy (Level 100)
    While every organization has different data needs, disparate data sources, or unreliable data pipelines forming data silos and a lack of knowledge to harness their data goldmines into actionable insights, with the right modern data strategy, you can eliminate data silos, modernize your data and analytics architecture, and unlock the real value from your data to create the foundation for rapid innovation. Get insights and learn how to turn your data into a tool for innovation including achieving agility, scalability, and cost-savings.

    Speaker: Blair Layton, Head of Database - Public Sector , APJ, AWS
    Duration: 30mins


    Reinventing data and analytics strategy for media and entertainment with AWS (Level 100)
    Media and entertainment customers face industry-wide transformation, with companies reinventing how they create content, optimize media supply chains, and compete for audience attention across streaming, broadcast, and direct-to-consumer platforms. In this session, learn how to align our purpose-built capabilities for the different solution areas and help customers to transform content production, media supply chain, broadcast, direct-to-consumer & streaming, and analytics. With AWS, you can select the right tools to accelerate production launches, and see faster time to value.

    Speakers: 
    Christer Whitehorn, Lead Solution Architect, AWS Media Services, APJC
    Sumit Kalia, Storage Specialist, ANZ, Amazon Web Services
    Duration: 30mins


    How data literate is your organization (Level 100)
    Enterprises are sitting on data goldmines they can harness for unique business value and competitive advantage. But as most leaders know, becoming a data driven organization is much easier said than done. In this session, we discuss the common characteristics of a data-driven organization, and actions leaders can take to build one.

    Speaker: Babak Darashte, Head of Data & Analytics Solutions Architecture, APJ, AWS
    Duration: 30mins


    How AXA Singapore transformed into a data-driven enterprise through a modern data platform on AWS (Level 100)
    Organizations are on a data-driven journey to use actionable insights, analytics, and AI/ML to create new revenue streams, improve customer experience, and increase operational efficiency. AXA is one such organization that is leveraging analytics to transform from being an Insurance Provider to a Business Partner for their customers. In this session, learn how AXA fostered a customer-centric and “data-driven” self-service culture to enable their transformation.

    Speakers: 
    Ganamanas Das, Senior ASEAN GTM Specialist, AWS
    Romain Bourgeois, Head of Data Foundations, AXA Insurance Singapore
    Duration: 30mins


    Solving business challenges with your data (Level 100)
    Business impact driven by data insights has deeply implicated greater industry and citizen efficiencies. Discover the advantages of how Intel’s compute, powers AWS platforms to deliver better price performance for data analytics workloads while achieving faster time to data insights.

    Speaker: Akanksha Balani, AWS APJ Alliance head, Intel
    Duration: 30mins

  • Modernize data infrastructure: Data movement & management
  • ico-innovate-data-modernize_your

    Modernize data infrastructure: Data movement & management

    About the track

    Gain best practices and concepts around data movement, eliminating data silos, and analyzing diverse datasets easily while keeping your data secure. Find out how to easily capture and centralize your data in a quick, cost-effective, and secure fashion using AWS.

    Introduction to data movement and management (Level 100)
    We are increasingly seeing our customers turn to AWS to help them with better ways to move and manage their data from efficient management of costs, improve business agility to protection of their strategic data assets. In this session, we introduce the Data Movement and Management track and share how we are enabling our customers to generate insights from their datasets, busting data migration myths, securing the data, and implement best practices for data management across different industries.

    Speaker: Luke Anderson, Senior Manager, Storage Specialist, APJ, AWS
    Duration: 30mins


    A journey of analytic data to a warm lake, hot insights, and frozen glacier (Level 200)
    Traditional data warehouses struggle with vast amounts of data - it costs too much or data is siloed. This prohibits customers from innovating and extracting value from their data. Customers want to analyze their operations quicker and operationalize insights faster. In this session, we share how you can maximize performance and minimize the costs of your analytical data journey, from ingest, to processing, to archival for both structured and unstructured datasets, with a data heatmap classification. We focus on how you can combine services like Amazon Redshift for Data Warehousing, or Amazon FSx for Lustre for HPC Analytics, with Amazon S3, which forms the heart of the data lake for our customers.

    Speaker: Wali Akbari, Senior Storage Solutions Architect, APJ, AWS
    Duration: 30mins


    Migration myth busting on moving your data to AWS (Level 200)
    One of the most challenging steps in migrating to the cloud can be data migration – and these steps are often met with many myths and perceptions around the end-to-end process. With many tools and services now available to assist you, choosing the right methodology is an important process. AWS offers the most complete set of solutions for moving your data to the cloud that are optimized for two key variables – cost and time. In this session, we focus on busting some myths associated to data migration such as cost, time, network capabilities, online vs offline, data integrity, and migration tools. Learn which technologies and methods are best for your various needs, and how they work.

    Speaker: Naim Mucaj, Storage Specialist Solutions Architect, AWS
    Duration: 30mins


    Securing your data and data governance on AWS (Level 200)
    One of the most important pieces of a modern analytics architecture is the ability for customers to authorize, manage, and audit access to data. This can be challenging, because managing security, access control, goverence and audit trails across all of the data stores in your organization is complex, time-consuming, and error-prone. In this session, learn more about the overall security model and approaches to adopt when implementing analytics services on AWS including capabilities like centralized access control and policies, and column level filtering of data.

    Speaker: Kumar Nachiketa, Storage Partner Solutions Architect APJ, AWS
    Duration: 30mins


    Build a secured, mutable, high performance data lake in days with AWS Lake Formation (Level 200)
    Organizations are breaking down data silos and building petabyte-scale data lakes on AWS. Since its launch, AWS Lake Formation has accelerated data lake adoption by making it easy to build and secure for data lakes. In this session, we dive deep into a few existing and upcoming features in AWS Lake Formation to solve common data lake challenges, such as mutability, file compaction and enforcing consistent fine-grained access to data across different user personas from a wide range of analytics and ML services. Learn how AWS Lake Formation allows you to share data securely within your organization and your partners without duplication or data movement in just a few clicks.

    Speaker: Niladri Bhattachrya, Senior Analytics Specialist Solutions Architect, AWS
    Duration: 30mins


    Data preparation made easy with AWS Glue DataBrew (Level 300)
    Data analysts and data scientists have spent a bulk of their time running data preparation tasks manually for analytics and ML modelling use cases to get clean and formatted data to meet their needs. As data continues to grow in size and complexity, organizations around the world are under pressure to expand the number of people and reduce the time to prepare and unlock value from their data. In this session, dive deep into AWS Glue DataBrew, a new visual data preparation tool that enables data analysts and data scientists to clean and normalize data by up to 80% faster without writing any code. We explain how AWS Glue DataBrew works including popular transformations and provide a walkthrough with use cases for data preparation across the data stores.

    Speaker: Vikas Omer, Senior Analytics Specialist Solutions Architect, AWS
    Duration: 30mins


    Simplify data integration with AWS Glue (Level 200)
    Data integration is not simply about migrating data. It is the process that enables workflows to streamline communications between systems and components which allows you to extract the maximum value from your data. In this session, learn how AWS Glue provides customers with fully managed serverless extract, transform, and load (ETL) options to simplify data integration architecture.

    Speaker: Tom Mcmeekin, Solutions Architect, AWS
    Duration: 30mins

  • Modernize data infrastructure: Databases
  • ico-innovate-data-data_movment

    Modernize data infrastructure: Databases

    About the track

    In this track, find out how AWS cloud databases can help you meet your distinct use cases all while delivering operational efficiency, performance, availability, scalability, security, and compliance.

    Build the future of your business with AWS database (Level 100)
    Data is at the core of every application, and companies are looking to use data as the foundation for future innovation in their applications and their organizations. This session provides an overview for the modernize data architecture with AWS databases track including how to jumpstart and build for the future with our purpose built databases.

    Speaker: Tony Gibbs, Databases Solutions Architect Leader, APJ, AWS
    Duration: 30mins


    Purpose-built databases: Choose the right tool for each job (Level 200)
    Seldom can one database fit the needs of multiple distinct use cases. The days of the one-size-fits-all monolithic database are behind us and highly distributed applications are using many purpose-built databases. The world is changing, and the categories of databases continue to grow. We are increasingly seeing customers wanting to build Internet-scale applications that require diverse data models. In response to these needs, we now have the choice of relational, key-value, wide column, document, in-memory, graph, time-series, and ledger databases. Each solves a specific problem or group of problems. In this session, learn how AWS purpose-built databases meet the scale, performance, and manageability requirements of modern applications.

    Speaker: William Wong, Senior Database Solutions Architect, AWS
    Duration: 30mins


    Transform your Oracle database operating model by leveraging AWS managed databases (Level 200)
    Organizations are looking to free up their valuable Oracle DBA resources and shift their efforts to activities that are business enablers. The best way to do that is to leverage the power of fully managed databases in the cloud. This session shows why you should consider moving your self-managed Oracle Databases to Amazon RDS for Oracle and how you can achieve it in the most efficient way. We showcase the benefits of a managed database operating model, discuss some transformative cost saving techniques, and walk through some best practice migration patterns. We demonstrate how to migrate an on-premise Oracle database to Amazon RDS Oracle in AWS with minimal downtime. We will also share the key ingredients for migration success, walk through the tools and mechanisms available to deliver a smooth transition, and introduce the additional benefits achievable by migrating from Oracle to a purpose-built database like Amazon Aurora Postgres.

    Speaker: Matt McClernon, Solutions Architect, Oracle, AWS
    Duration: 30mins


    SQL Server on AWS: Choosing the right strategy (Level 300)
    Customers have been running Microsoft Workloads on AWS for over 12 years, longer than any other cloud provider. In this session, learn about the journey of migrating Microsoft SQL Server to AWS. While there is no one-size-fits-all approach for migrating SQL Server workloads to the cloud, there are three primary ways to move SQL Server-based applications to AWS. You can choose to lift and shift to Amazon EC2 or move to fully managed Amazon RDS or modernize with AWS purpose built databases. We explain the benefit of each approach to make the right choice and illustrate on the multiple architectural patterns for efficient migration of Microsoft SQL Server to different target platforms in AWS. The session also walks through available tools and services like AWS Database Migration Service, AWS Schema Conversion Tool, AWS Snow devices, AWS Storage Gateway and AWS DataSync to support you in your migration journey. Uncover and learn more about strategies and best practices to migrate or modernize your SQL Server workloads on AWS.

    Speaker: Rita Ladda, Senior Database Solutions Architect, AWS
    Duration: 30mins


    Architecting on AWS managed databases like a rockstar! (Level 300)
    Self-managing databases, either on-premises or in the cloud, can be time-consuming, complex, and expensive. With AWS fully managed database services, such as Amazon RDS, Amazon Aurora, Amazon Neptune, Amazon ElastiCache, and Amazon DocumentDB, you do not need to worry about server provisioning, patching, setup, configuration, backups, or recovery. Instead, you can spend time innovating and building new applications and leave the infrastructure management to AWS. In this session, learn how to easily migrate and maintain database infrastructure and break free from managing legacy systems using AWS managed databases, all while delivering operational efficiency, performance, availability, scalability, security, and compliance. We demonstrate the benefits of using custom built processers that deliver the best price performance for your cloud workloads. To conclude, we explain and provide a walk through on the best practices in architecting critical databases on Amazon Aurora.

    Speaker: Roneel Kumar, Senior Database Solutions Architect, AWS
    Duration: 30mins


    Build scalable, global applications with NoSQL databases (Level 200)
    When building global applications, low latency access to data is critical. Many organizations are revamping their data strategy as part of their digital transformation initiatives. Application modernization is a common theme for these initiatives, and a highly available, highly scalable database is a key requirement to succeed. Amazon DynamoDB and Amazon DocumentDB are designed from the ground up as fully managed, scalable, and purpose-built database services engineered for mission-critical workloads. In this session, learn how you can leverage Amazon DocumentDB and Amazon DynamoDB to build globally distributed applications on AWS.

    Speaker: Sean Shiriver, Senior DynamoDB Specialist Solutions Architect, AWS
    Duration: 30mins


    Extreme performance at cloud scale: Supercharge your real-time applications with Amazon ElastiCache (Level 200)
    With the explosive growth of business-critical, real-time applications, performance is one of the top considerations for companies across industries. Learn how you can improve performance to impact both revenue and customer satisfaction through a distributed cache with Amazon ElastiCache for Redis. ElastiCache is a fully managed in-memory caching service that enables microsecond latency and flexible scaling for real-time applications. In this session, discover how caching can supercharge your workloads to and best practices for getting started with ElastiCache.

    Speaker: Damon Lacaille, Senior ElastiCache Specialist Solutions Architect, AWS
    Duration: 30mins

  • Unify your data: Accelerating insights
  • ico-innovate-data-unify_your

    Unify your data: Accelerating insights

    About the track

    Learn the approaches, tools, and frameworks to break down data silos, unify your data, and make data more accessible to everyone who needs it and can seamlessly discover, access, and analyze the data in a secure and governed way.

    Harness the power of your data with AWS analytics (Level 100)
    Data is growing exponentially, coming from various sources, is increasingly diverse, and needs to be securely accessed and analyzed by any number of applications and people. Learn how analytics on AWS and the Lake House architecture puts the right tools in your hands to create delightful customer experiences and data-driven organizations.

    Speaker: Francis McGregor Macdonald, Principal Analytics Senior Solutions Architect, AWS
    Duration: 30mins


    Analytics services optimized for your use case (Level 200)
    AWS gives you the broadest and deepest portfolio of purpose-built analytics services optimized for your unique analytics use cases. These services are all designed to be the best in class, which means you never have to compromise on performance, scale, or cost when using them.

    Speaker: Francis McGregor Macdonald, Principal Analytics Senior Solutions Architect, AWS
    Duration: 30mins


    Break free from the constraints of on-premises data warehouses with Amazon Redshift (Level 200)
    Customers with on-premises data warehouses find them complex and expensive to manage, especially with respect to data load and performance. With Amazon Redshift, the most popular data warehouse solution in the cloud, get ready to scale storage and compute independently, increase available computing power under the hood and manage unpredictable workload spikes, automatically optimize throughput, including taking care of undifferentiated heavy lifting and let you focus on addressing challenges that are core to your business. In this session, learn how customers have made the move, the migration tools offered by AWS, and new features in Amazon Redshift that makes migration faster and easier.

    Speaker: Marco Ullasci, Senior Analytics Specialist Solutions Architect, AWS
    Duration: 30mins


    New data warehousing use cases with Amazon Redshift (Level 200)
    As data grows, we need innovative approaches to get insight from all the information at scale and speed. You can use new Redshift features to do more with your data. Amazon Redshift powers the lake house architecture – enabling you to query data across your data warehouse, data lake, and operational databases to gain faster and deeper insights. You can use the Redshift data API makes to build web-services based applications that access your data using Python, Node.js, and other languages supported by the Amazon SDK. You can simplify JSON and semi-structured data handling with the SUPER data type. You can enable data as a service, cross group collaboration, and workload isolation with data sharing. And you can run scan, filtering, and aggregation operations up to 10X faster than other enterprise cloud data warehouses with AQUA for Redshift. Join this session and learn about these new features and use cases.

    Speaker: Kerry McRae, Solutions Architect, AWS
    Duration: 30mins


    Modernize log analytics with Amazon Elasticsearch Service (Level 200)
    Organisations of all sizes use Amazon Elasticsearch Service to handle their log analytics workloads. With its deep integration with AWS native services and open source frameworks, customers can build robust, cost effective, and scalable log analytics solutions to process from several GBs to petabytes of data. In this session, we will review the best practices and design patterns to build scalable and secure log analytics solutions using Amazon Elasticsearch Service.

    Speaker: Muhammad Ali, Senior Analytics Specialist Solutions Architect, AWS
    Duration: 30mins


    Beyond batch processing - real-time analytics at scale with Apache Flink (Level 300)
    Real-time analytics are on the rise. Apache Flink is a popular purpose-built framework and distributed processing engine for large scale low latency data processing in real-time. In this session, we cover a brief overview of this popular framework, and a demo to build a real-time sentiment analysis application to analyze customer feedback with Apache Flink on Amazon Kinesis Data Analytics Studio.

    Speaker: Masudur Rahaman Sayem, Analytics Specialist Solutions Architect, AWS
    Duration: 30mins


    Move Apache Spark, Hadoop, Presto, and other big data applications to the cloud with Amazon EMR (Level 300)
    Organizations can use Amazon EMR to run petabyte-scale analysis using Apache Spark, Hadoop, Presto and other open source frameworks at less than half of the cost of traditional on-premises solutions. Amazon EMR makes it easy to set up, operate, and scale big data environments by automating time-consuming tasks like provisioning capacity and tuning clusters, and runs applications faster than open source Apache Spark and Presto. Join this session to learn more about EMR and how to move and orchestrate big data applications in AWS.

    Speaker: Melody Yang, Senior Analytics Specialist Solutions Architect, AWS
    Duration: 30mins

  • Innovate with analytics & ML
  • ico-innovate-data-invent_new

    Innovate with analytics & ML

    About the track

    Discover the various machine learning integration services available on AWS that can help you build, deploy, and innovate at scale. We also focus on how AI services are applied to common use cases such as personalized recommendations, identity verification, and automating document processing workflow.

    Invent new experiences and reimagine processes with Analytics and Machine Learning (Level 100)
    In this session, we show you how to reinvent new experiences and reimagine old processes with Analytics and AI & Machine Learning (ML) to match your business and organization needs. We explain how customers turn their data into insights using a modern data architecture and focus on the different ways ML is added to AWS database and analytics services to help practitioners use ML without prior knowledge.

    Speaker: Anna Conigilo, Manager Analytics Specialist Solutions Architect, AWS
    Duration: 30mins


    Democratize machine learning (ML) in your organization with SQL, Amazon Redshift, and Amazon SageMaker (Level 200)
    With Redshift ML, you can take advantage of Amazon SageMaker, a fully managed machine learning service, without learning new tools or languages. You can use familiar SQL commands in your Amazon Redshift data warehouse to create, train, and apply machine learning models. For example, you can use customer retention data in Redshift to train a churn detection model and then apply that model to your dashboards for your marketing team to offer incentives to customers at risk of churning. Redshift ML makes the model available as a SQL function within your Redshift data warehouse so you can easily apply it directly in your queries and reports. Join this session to learn how to easily use ML in your data science work.

    Speaker: Anna Conigilo, Manager Analytics Specialist Solutions Architect, AWS
    Duration: 30mins


    Embedding analytics into your SaaS applications with Amazon QuickSight (Level 200)
    As businesses become more data driven there is a growing importance on providing users with quick and seamless access to these actionable insights. By moving information closer to the primary user experience through applications and portals, data practitioners are looking to deliver insights to their users where they are. In this session, learn how to bring data closer to your users by seamlessly embedding analytics within applications using Amazon QuickSight. We walk through how you can quickly leverage QuickSight APIs to embed your own analytics and share a few tips and tricks to help you easily enhance your applications with rich, interactive data visualizations and analytics without any custom development.

    Speaker: Olivia Carline, QuickSight Solution Architect, AWS
    Duration: 30mins


    Deliver better customer experiences with machine learning in real-time (Level 300)
    Businesses are increasingly using machine learning (ML) to make near-real-time decisions, such as placing an ad, assigning a driver, recommending a product, detecting fraudulent transactions or even dynamically pricing products and services. Real-time machine learning can substantially enhance your customers' experience, resulting in better engagement and retention. In this session, learn how to use AWS data streaming platforms such as Amazon Kinesis to collect and process data in real-time, and Amazon SageMaker Feature Store, which provides a fully managed central repository for ML features, to support real-time machine learning. We will also walk through the architecture that supports the ML-backed decisions in near-real time for a credit card fraud detection use case.

    Speaker: Aneesh Chandra PN, Senior Analytics Specialist Solutions Architect, AWS
    Duration: 30mins


    Sentiment analysis using Amazon Aurora machine learning integration (Level 200)
    In this session, learn how to turn relational data into insights using Amazon Aurora and the integration with Machine learning. Uncover and learn how to take existing data in your relational database, for example product reviews, blog comments, and extract sentiments hidden in it. We walk through the Aurora's integration with Amazon Comprehend which uses Natural Learning processing (NLP) and Amazon SageMaker, and focus on using simple SQL queries to achieve this. And yes, no prior knowledge of machine learning needed!

    Speaker: Suman Debnath, Principal Developer Advocate, AISPL
    Duration: 30mins


    Building a document processing solution with Amazon Textract, database, data lakes, and analytics on AWS (Level 200)
    Organizations have many traditional documents and forms that hold critical business data. These documents, such as medical forms, insurance claims and loan applications, have structured and unstructured data that are either extracted by humans or by rule-based systems which are not easily scalable, have high costs, and could produce low-accuracy extraction results. In this session, learn how to use Amazon Textract to extract structured data to more accessible file types or to a queryable database, integrate a data lake and analytics solution, visualize the extraction results and deploy your automated document processing workflow into production, at scale.

    Speaker: Ryan Hendriks, Principal Solution Architect – Data Modernization, AWS
    Duration: 30mins


    Image and video analysis with Amazon Rekognition and Analytics on AWS (Level 200)
    Organisations are looking for ways to extract data from images and videos. Storing and manual cataloging of such media is expensive, error-prone, and hard to scale. Computer vision technology enables digital media professionals to generate valuable insights at a quick pace and at a lower cost by automatically identifying the contents of images and video. In this session, learn how you can integrate artificial intelligence into your media workflows with Amazon Rekognition, a deep learning-based image and video analysis service. We will also cover different use cases in applications such as security, public safety, identity verification, and media and entertainment.

    Speaker: Rohini Gaonkar, Senior Developer Advocate, India, AISPL
    Duration: 30mins

  •  Korean
  •  Japanese
  •  Indonesian

Session levels designed for you

INTRODUCTORY
Level 100

Sessions are focused on providing an overview of AWS services and features, with the assumption that attendees are new to the topic.

INTERMEDIATE
Level 200

Sessions are focused on providing best practices, details of service features and demos with the assumption that attendees have introductory knowledge of the topics.

ADVANCED
Level 300

Sessions 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.

Conference Time

  • Australia & New Zealand
  • ASEAN & Pakistan
  • India & Sri Lanka
  • Japan
  • Korea
  • Australia & New Zealand
  • Australia
     GMT+10 (AEST)

    Timing 1: 9.00am - 2.30pm
    Timing 2: 3.00pm - 8.30pm

    New Zealand
     GMT+12 (NZST)

    Timing 1: 11.00am - 4.30pm
    Timing 2: 5.00pm - 10.30pm

  • ASEAN & Pakistan
  • Singapore
    Malaysia
    Phillippines
     GMT+8 (SGT/MYT/PHT)

    Timing 1: 7.00am - 12.30pm
    Timing 2: 1.00pm - 6.30pm

    .
    Thailand
    Vietnam
    .
     GMT+7 (ICT)

    Timing 1: 6.00am - 11.30am
    Timing 2: 12.00pm - 5.30pm

    .
    Indonesia
    .
    .
     GMT+7 (WIB)

    Timing 1: 0600 - 1130
    Timing 2: 1200 - 1730

    .
    Pakistan
    .
    .
     GMT+5 (PKT)

    Timing 1: 4.00am - 9.30am
    Timing 2: 10.00am - 3.30pm

    .
  • India & Sri Lanka
  • India
     GMT+5.30 (IST)

    Timing 1: 4.30am - 10.00am
    Timing 2: 10.30am - 4.00pm

    Sri Lanka
     GMT+530 (SLST)

    Timing 1: 4.30am - 10.00am
    Timing 2: 10.30am - 4.00pm

  • Japan
  • Japan
     GMT+9 (JST)

    Timing 1: 8.00am - 1.30pm
    Timing 2: 2.00pm - 7.30pm

  • Korea
  • Korea
     GMT+9 (KST)

    Timing 1: 8.00am - 1.30pm
    Timing 2: 2.00pm - 7.30pm

Featured Speakers

Rahul Pathak

Rahul Pathak
Vice President of Analytics, AWS

Olivier Klein

Olivier Klein,
Chief Technologist, APJ, AWS

Olivier Klein

Jack Berkowitz
SVP Product Development (ADP Data Cloud), ADP

Olivier Klein

Prasad Ramakrishnan
Chief Information Officer & Chief Information Security Officer, Freshworks


Learn more about Data & Analytics on AWS

10,000

customers use data lake and
data warehouse
on AWS

Leader in Gartner Magic Quadrant for Cloud AI Developer Services

450,000

databases migrated to AWS

3x

faster petabyte-scale analysis than standard Apache Spark

89%

of deep learning projects in the cloud run on AWS


Frequently Asked Questions

1. Where is AWS Innovate hosted?
2. Who should attend AWS Innovate?
3. How do I get the certificate of attendance?
4. Are there sessions in other languages?
5. Do I need to attend all the timings?
6. What is the price of attending AWS Innovate?
7. Can I get a confirmation of my AWS Innovate registration?

Q: Where is AWS Innovate hosted?
A:
AWS Innovate is an online conference. After filling up the registration form, you will receive an email to complete your registration. Please follow the instructions and complete the steps to receive the confirmation email and gain access to the event on 19 August, 2021.

Q: Who should attend AWS Innovate?
A:
Whether you are new to AWS or an experienced user, you can learn something new at AWS Innovate. AWS Innovate is designed to help you develop the right skills to create new insights, enable new efficiencies, and make faster, accurate decisions.

Q: How do I get the certificate of attendance?
A:
Complete watching 5 or more sessions on the live day to receive a certificate of attendance by 31 August, 2021. This will be sent to your email address that you used to register for the event.

Q: Are there sessions in other languages?
A:
AWS Innovate is also available in Korean, Japanese, and Indonesian.

Q: Do I need to attend all the timings?
A:
The sessions are repeated across the timings to accommodate attendees in different time zones. You may select any timing that works best for you.

Q: What is the price of attending AWS Innovate?
A:
AWS Innovate is a free online conference.

Q: Can I get a confirmation of my AWS Innovate registration?
A:
After filling up the registration form, you will receive an email to complete your registration. Please follow the instructions and complete the steps to receive the confirmation email and gain access to the event on 19 August, 2021.

Q: How can I contact the online conference organizers?
A:
If you have questions that have not been answered in the FAQs above, please email us.

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Rahul Pathak, Vice President of Analytics, AWS

Rahul Pathak is Vice President of Analytics at AWS and is responsible for Amazon Athena, Amazon Elasticsearch Service, EMR, Glue, Lake Formation, and Redshift. Over his nine years at AWS, he has focused on managed database, analytics, and database services. Rahul has over twenty years of experience in technology and has co-founded two companies, one focused on digital media analytics and the other on IP-geolocation. He holds a degree in Computer Science from MIT and an Executive MBA from the University of Washington.

Olivier Klein, Chief Technologist, APJ, AWS

Olivier is a hands-on technologist with more than 10 years of experience in the industry and has been helping customers build resilient, scalable, secure, and cost-effective applications and create innovative and data-driven business models. He advises on how emerging technologies in the AI, ML, and IoT spaces can help create new products, make existing processes more efficient, provide overall business insights, and leverage new engagement channels for consumers. 

Jack Berkowitz, SVP Product Development (ADP Data Cloud), ADP

Jack is the Senior Vice President at ADP where he leads business and product development for ADP Data Cloud. Data Cloud provides People Analytics, Compensation and HR Benchmarking products to HR departments. In addition, Data Cloud partners to use benchmarking data across the industry. He also manages a team that builds and operationalizes machine learning applications across ADP’s varied HR, Payroll and Time applications around the world. Prior to joining ADP, he was the VP of products and Data Science, Oracle Adaptive Intelligence where he led product strategy, management and data science for Oracle's data driven Cloud Applications, combining data science, web-scale data assets, and enterprise application data into targeted intelligent systems.

Prasad Ramakrishnan Chief Information Officer & Chief Information Security Officer, Freshworks

Prasad is the chief information officer and chief information security officer (CISO) of Freshworks, leading the company’s IT vision, strategy and execution. He is a seasoned IP professional , SaaS evangelist, and go-to thought leader on all things cloud and security at Freshworks. He handles 3 portfolios at FW – Platform engineering, Site Reliability engineering and Product integrations. He is the key decision maker on technology stack and is our primary stakeholder. Before joining Freshworks, he was VP at Walmart Labs for 5 years. He worked with Amazon from 1998- 2001 as Sr. Engineering Manager at Seattle.