AWS has been supporting companies across Australia and New Zealand to put their most innovative tools and technologies to work to achieve their business needs and goals. AWS and our ecosystem of partners has helped the likes of CP Mining, IntelliHQ, WesCEF, Oz Minerals, Woodside and many more to modernise their analytics and data architecture in order to successfully generate business value from their data.
This event series aimed to educate customers with a broader understanding of how to build next-gen data lakes and analytics platforms and make connections with AWS.
Semiconductor design companies, electronic design automation (EDA) vendors, and foundries remain competitive by innovating and reducing time to market. AWS is deeply invested in semiconductor use cases, including EDA, emulation, and smart manufacturing, including data lake and IoT/AI. We care about this because Amazon depends on faster semiconductor innovation from our suppliers and in our own silicon teams. We have a wide breadth of services that will directly benefit the entire industry. In this session, learn how to achieve the maximum possible performance and throughput from design and engineering workloads running on AWS. We demonstrate specific optimization techniques and share architectures to accelerate batch and interactive workloads on AWS. We also demonstrate how to extend and migrate on-premises, high performance compute workloads with AWS, and use a combination of On-Demand Instances, Reserved Instances, and Spot Instances to minimize costs. Learn how semiconductor customers address security as they move to the cloud as they discuss the AWS capabilities and controls available to secure sensitive design IP and offer strategies for data classification, management, and transfer to third parties.
AI/ML with Data Lakes: Counterintuitive Consumer Insights in Retail (RET206) ...Amazon Web Services
In this session, learn how data scientists in the retail industry, from companies like Tapestry, Coach, and Kate Spade, are finding new, counterintuitive consumer insights using AWS artificial intelligence services in a data lake. By leveraging data from various retail systems, including CRM, marketing, e-commerce, point of sale, order management, merchandising, and customer care, we show you how these consumer insights might influence new and interesting retail use cases while establishing a data-driven culture within the organization. Services referenced include Amazon S3, Amazon Machine Learning, Amazon QuickSight, Amazon SageMaker, among others.
Database Freedom. Database migration approaches to get to the Cloud - Marcus ...Amazon Web Services
Databases are at the heart of many of the software systems we build. Learn how to achieve the benefits of moving your core datastores to the AWS platform, by designing a migration model that retires tech debt and sets the platform for innovation. In this session we'll cover the different database options available on AWS, how you can start migrating your databases to the cloud, and cover tools like the AWS Database Migration Service (DMS) to largely automate this work for you.
Connecting the dots - How Amazon Neptune and Graph Databases can transform yo...Amazon Web Services
Amazon Neptune is the fully-managed graph database service that makes it easy to build and run applications for highly connected datasets. Come learn how to transform your business with Amazon Neptune and hear diverse use cases such as recommendation engines, knowledge graphs, fraud detection, social networks, network management and life sciences. Learn about using Amazon Neptune with Apache TinkerPop Gremlin traversals and RDF/SPARQL query processing and watch live how we derive valuable business insights, customer satisfaction by region, in a simple query.
Amazon Cloud Directory Deep Dive (DAT364) - AWS re:Invent 2018Amazon Web Services
Learn how companies like FocusCura and Clouden have on-boarded hierarchical data at scale using Amazon Cloud Directory, a highly available, fully managed, serverless, hierarchical datastore. It’s well-suited for such use cases as human resources applications, course catalogs, device registry, network topology, and any application that needs fine-grained permissions (authorization). We do a deep dive into the internals of Cloud Directory and discuss best practices.
Semiconductor design companies, electronic design automation (EDA) vendors, and foundries remain competitive by innovating and reducing time to market. AWS is deeply invested in semiconductor use cases, including EDA, emulation, and smart manufacturing, including data lake and IoT/AI. We care about this because Amazon depends on faster semiconductor innovation from our suppliers and in our own silicon teams. We have a wide breadth of services that will directly benefit the entire industry. In this session, learn how to achieve the maximum possible performance and throughput from design and engineering workloads running on AWS. We demonstrate specific optimization techniques and share architectures to accelerate batch and interactive workloads on AWS. We also demonstrate how to extend and migrate on-premises, high performance compute workloads with AWS, and use a combination of On-Demand Instances, Reserved Instances, and Spot Instances to minimize costs. Learn how semiconductor customers address security as they move to the cloud as they discuss the AWS capabilities and controls available to secure sensitive design IP and offer strategies for data classification, management, and transfer to third parties.
AI/ML with Data Lakes: Counterintuitive Consumer Insights in Retail (RET206) ...Amazon Web Services
In this session, learn how data scientists in the retail industry, from companies like Tapestry, Coach, and Kate Spade, are finding new, counterintuitive consumer insights using AWS artificial intelligence services in a data lake. By leveraging data from various retail systems, including CRM, marketing, e-commerce, point of sale, order management, merchandising, and customer care, we show you how these consumer insights might influence new and interesting retail use cases while establishing a data-driven culture within the organization. Services referenced include Amazon S3, Amazon Machine Learning, Amazon QuickSight, Amazon SageMaker, among others.
Database Freedom. Database migration approaches to get to the Cloud - Marcus ...Amazon Web Services
Databases are at the heart of many of the software systems we build. Learn how to achieve the benefits of moving your core datastores to the AWS platform, by designing a migration model that retires tech debt and sets the platform for innovation. In this session we'll cover the different database options available on AWS, how you can start migrating your databases to the cloud, and cover tools like the AWS Database Migration Service (DMS) to largely automate this work for you.
Connecting the dots - How Amazon Neptune and Graph Databases can transform yo...Amazon Web Services
Amazon Neptune is the fully-managed graph database service that makes it easy to build and run applications for highly connected datasets. Come learn how to transform your business with Amazon Neptune and hear diverse use cases such as recommendation engines, knowledge graphs, fraud detection, social networks, network management and life sciences. Learn about using Amazon Neptune with Apache TinkerPop Gremlin traversals and RDF/SPARQL query processing and watch live how we derive valuable business insights, customer satisfaction by region, in a simple query.
Amazon Cloud Directory Deep Dive (DAT364) - AWS re:Invent 2018Amazon Web Services
Learn how companies like FocusCura and Clouden have on-boarded hierarchical data at scale using Amazon Cloud Directory, a highly available, fully managed, serverless, hierarchical datastore. It’s well-suited for such use cases as human resources applications, course catalogs, device registry, network topology, and any application that needs fine-grained permissions (authorization). We do a deep dive into the internals of Cloud Directory and discuss best practices.
Dissecting Media Asset Management Architecture and Media Archive TCO (MAE301)...Amazon Web Services
Every M&E migration strategy to AWS requires the customer and partners to design and implement a content ingest workflow. These services vary from simple file transfer to fairly complex workflows that do quality control, proxy creation, and metadata augmentation. In this session, we present a baseline process for moving content into a Media Asset Management system in AWS, leveraging common open-source tools for asset registry and using AWS ML services to augment the metadata associated with assets. We also talk about common considerations that M&E organizations should consider when moving their assets and workflows to the cloud. Topics include metadata input, modeling, storage services and policies, security considerations, and managing increased content demands. We also visit the different storage tiers for different archive use cases and offer a TCO model.
Modernizing .NET Applications on AWS (GPSCT204) - AWS re:Invent 2018Amazon Web Services
Many customers move to the cloud to innovate faster and gain more business agility. In order to recognize these benefits of the cloud, many customers are migrating their .NET applications to AWS, whilst innovating faster by taking advantage of cloud-native services. In this session, we will go through application modernization journey for a .NET application to AWS, and walkthrough Containerization as an option. We also discuss how easy it is for the customers to transform their business applications using AWS while using the familiar Microsoft toolset and workflows.
Driving Machine Learning and Analytics Use Cases with AWS Storage (STG302) - ...Amazon Web Services
You’ve designed and built a well-architected data lake and ingested extreme amounts of structured and unstructured data. Now what? In this session, we explore real-world use cases where data scientists, developers, and researchers have discovered new and valuable ways to extract business insights using advanced analytics and machine learning. We review Amazon S3, Amazon Glacier, and Amazon EFS, the foundation for the analytics clusters and data engines. We also explore analytics tools and databases, including Amazon Redshift, Amazon Athena, Amazon EMR, Amazon QuickSight, Amazon Kinesis, Amazon RDS, and Amazon Aurora; and we review the AWS machine learning portfolio and AI services such as Amazon SageMaker, AWS Deep Learning AMIs, Amazon Rekognition, and Amazon Lex. We discuss how all of these pieces fit together to build intelligent applications.
Modern data is massive, quickly evolving, unstructured, and increasingly hard to catalog and understand from multiple consumers and applications. This presentation will guide you though the best practices for designing a robust data architecture, highlightning the benefits and typical challenges of data lakes and data warehouses. We will build a scalable solution based on managed services such as Amazon Athena, AWS Glue, and AWS Lake Formation.
In this workshop, learn how to connect devices to AWS IoT and AWS Greengrass. Understand the architecture, and install and configure device communication using AWS Greengrass. In addition, take advantage of the opportunity to create various device communication scenarios with AWS Greengrass and simulate the data flow with sensor data. Attendees in workshop need an AWS account and are asked to bring their laptop.
ABD209_Accelerating the Speed of Innovation with a Data Sciences Data & Analy...Amazon Web Services
"Historically, silos of data, analytics, and processes across functions, stages of development, and geography created a barrier to R&D efficiency. Gathering the right data necessary for decision-making was challenging due to issues of accessibility, trust, and timeliness. In this session, learn how Takeda is undergoing a transformation in R&D to increase the speed-to-market of high-impact therapies to improve patient lives. The Data and Analytics Hub was built, with Deloitte, to address these issues and support the efficient generation of data insights for functions such as clinical operations, clinical development, medical affairs, portfolio management, and R&D finance. In the AWS hosted data lake, this data is processed, integrated, and made available to business end users through data visualization interfaces, and to data scientists through direct connectivity. Learn how Takeda has achieved significant time reductions—from weeks to minutes—to gather and provision data that has the potential to reduce cycle times in drug development. The hub also enables more efficient operations and alignment to achieve product goals through cross functional team accountability and collaboration due to the ability to access the same cross domain data.
Session sponsored by Deloitte"
Artificial Intelligence nella realtà di oggi: come utilizzarla al meglioAmazon Web Services
L'intelligenza Artificiale è qui questa volta, per restare. Per le aziende, l'intelligenza artificiale si concretizza in soluzioni che migliorano l'esperienza dei clienti ottimizzando, automatizzando e personalizzando attività ad alto volume e riducendo al contempo costi e tempi, accelerando notevolmente il ritmo di innovazione. In questa sessione, approfondiremo i servizi AI di AWS che promuovo l'innovazione in azienda mantenendo la conformità con diversi regimi come HIPAA, PCI e altro. Infine, presenteremo le architetture AWS necessarie per supportare i carichi di lavoro di apprendimento automatico e deep learning.
Run Production Workloads on Spot, Save up to 90% (CMP306-R1) - AWS re:Invent ...Amazon Web Services
Amazon EC2 Spot Instances enable you to use spare EC2 computing capacity— capacity that is often 90% less than On-Demand prices. In this session, learn how to effectively harness Spot Instances for production workloads. We explore application requirements for using Spot Instances, best practices learned from thousands of customers, and the services that make it easy to use. Finally, we run through practical examples of how to use Spot for the most common production workloads, the common pitfalls customers run into, and how to avoid them.
What's New with Amazon Redshift ft. McDonald's (ANT350-R1) - AWS re:Invent 2018Amazon Web Services
Learn about the latest and hottest features of Amazon Redshift. We’ll deep dive into the architecture and inner workings of Amazon Redshift and discuss how the recent availability, performance, and manageability improvements we’ve made can significantly enhance your user experience. We’ll also share glimpse of what we are working on and our plans for the future. McDonald's will join us to share how they leverage a data lake powered by Redshift, Redshift spectrum and Athena to get quick insights.
[NEW LAUNCH!] How to build and deploy Windows file system in AWS using Amazon...Amazon Web Services
If you have compute-intensive workloads like high performance computing, machine learning, and media processing then this is the workshop for you! Our new file storage service, Amazon FSx for Lustre, provides compute-optimized storage with fully managed Lustre file systems that can deliver hundreds of gigabytes of throughput and sub-millisecond latencies. You will learn how to spin up an FSx for Lustre file system in minutes, feed data to it from an S3 data lake, run analyses while writing results back to S3, and then spin down the file system once the workload is finished.
SAP provides software that many organizations continue to use to manage core workload requirements, with a significant number of these organizations running their SAP workloads on AWS. However, SAP doesn’t need to be operated similarly in the cloud as it is on premise. AWS can still drive innovation, even in operating solutions from companies such as SAP. Join us to see how organizations who have a strong leverage on AWS, carry over their platform knowledge to SAP workloads. They can improve the efficiency of their application teams - from easier migrations, to reducing time spent in operations, and overall improving the flexibility of delivering SAP workloads.
M&E Leadership Session: The State of the Industry, What's New from AWS for M&...Amazon Web Services
In this wide-ranging keynote session, first hear from AWS VP Carla Stratfold on the major forces affecting the industry, then learn from AWS Global M&E Tech Lead Usman Shakeel about the latest and most exciting releases coming out of re:Invent relevant to the M&E industry. And finally, hear how technical leaders at the forefront of the industry are responding to accelerating changes in the media landscape.
Microservices on AWS: Architectural Patterns and Best Practices | AWS Summit ...AWS Summits
This session is the first of 5 sessions that will cover a fully functioning system we have built to demonstrate how to rapidly develop systems using the AWS platform. This session we will start with a demo and an architecture review in which we will break into the different subsystems. In the second part of the session we will zoom into the Microservices part of the solution.Microservices are an architectural and organizational approach to software development where software is composed of small independent services that communicate over well-defined APIs. This session demonstrates the use of services like Amazon ECS, AWS Cloud Map and Amazon API Gateway and can help you understand where you can utilize microservices architecture in your own organization and understand areas of potential savings and increased agility.
Alexa, Ask Jarvis to Create a Serverless App for Me (SRV315) - AWS re:Invent ...Amazon Web Services
Today, we can build and deploy a serverless application in minutes without having to write a line of code using pre-built AWS CloudFormation templates, or services such as the AWS Serverless Application Repository. But can we push the limits even more? In this workshop, we use the Serverless Application Repository combined with Amazon Alexa to create Iron Man's Jarvis look-a-like skill. You learn hands-on with Alexa, Amazon Lex, Amazon SageMaker, and the AWS Serverless Application Repository.
The Amazon.com Database Journey to AWS – Top 10 Lessons Learned (DAT326) - AW...Amazon Web Services
In this session, we share the top 10 lessons learned from migrating the online transaction processing (OLTP) and data warehouse (DW) databases used by Amazon.com to AWS services, such as Amazon Relational Database Service (Amazon RDS), Amazon Aurora, Amazon Redshift, and Amazon DynamoDB. We discuss the challenges associated with operating and managing legacy OLTP and DW databases at Amazon.com scale and how the Amazon.com team successfully executed the database freedom program across different organizations and geographies.
Enabling Transformation through Agility & Innovation - AWS Transformation Day...Amazon Web Services
Learn how AWS can help transform your business. With AWS, enterprises are becoming more agile, secure, and scalable. This helps to promote innovation, shorten cycles to respond to business requirements, increase employee productivity, and retain and recruit top talent.
Improve business performance, reduce costs, and reinvent your IT strategies. Topics include how to maximize the value of your Enterprise workloads with AWS, foster a culture of innovation, manage risk and security, and new ways to think about product development, how to modernize the delivery of IT services, and best practices for adopting the cloud at scale.
SKL208 - Turbocharge your Business with AI and Machine Learning - Tel Aviv Su...Boaz Ziniman
This session will focus on the basic building blocks of Artificial Intelligence (AI) and Machine Learning (ML) using AWS services. It will help you to identify use cases for ML with real-world examples, and help you create the right conditions for delivering successful ML-based solutions to your business.
TiVo: How to Scale New Products with a Data Lake on AWS and QuboleAmazon Web Services
In our webinar, representatives from TiVo, creator of a digital recording platform for television content, will explain how they implemented a new big data and analytics platform that dynamically scales in response to changing demand. You’ll learn how the solution enables TiVo to easily orchestrate big data clusters using Amazon Elastic Cloud Compute (Amazon EC2) and Amazon EC2 Spot instances that read data from a data lake on Amazon Simple Storage Service (Amazon S3) and how this reduces the development cost and effort needed to support its network and advertiser users. TiVo will share lessons learned and best practices for quickly and affordably ingesting, processing, and making available for analysis terabytes of streaming and batch viewership data from millions of households.
TiVo: How to Scale New Products with a Data Lake on AWS and QuboleAmazon Web Services
In our webinar, representatives from TiVo, creator of a digital recording platform for television content, will explain how they implemented a new big data and analytics platform that dynamically scales in response to changing demand. You’ll learn how the solution enables TiVo to easily orchestrate big data clusters using Amazon Elastic Cloud Compute (Amazon EC2) and Amazon EC2 Spot instances that read data from a data lake on Amazon Simple Storage Service (Amazon S3) and how this reduces the development cost and effort needed to support its network and advertiser users. TiVo will share lessons learned and best practices for quickly and affordably ingesting, processing, and making available for analysis terabytes of streaming and batch viewership data from millions of households.
Dissecting Media Asset Management Architecture and Media Archive TCO (MAE301)...Amazon Web Services
Every M&E migration strategy to AWS requires the customer and partners to design and implement a content ingest workflow. These services vary from simple file transfer to fairly complex workflows that do quality control, proxy creation, and metadata augmentation. In this session, we present a baseline process for moving content into a Media Asset Management system in AWS, leveraging common open-source tools for asset registry and using AWS ML services to augment the metadata associated with assets. We also talk about common considerations that M&E organizations should consider when moving their assets and workflows to the cloud. Topics include metadata input, modeling, storage services and policies, security considerations, and managing increased content demands. We also visit the different storage tiers for different archive use cases and offer a TCO model.
Modernizing .NET Applications on AWS (GPSCT204) - AWS re:Invent 2018Amazon Web Services
Many customers move to the cloud to innovate faster and gain more business agility. In order to recognize these benefits of the cloud, many customers are migrating their .NET applications to AWS, whilst innovating faster by taking advantage of cloud-native services. In this session, we will go through application modernization journey for a .NET application to AWS, and walkthrough Containerization as an option. We also discuss how easy it is for the customers to transform their business applications using AWS while using the familiar Microsoft toolset and workflows.
Driving Machine Learning and Analytics Use Cases with AWS Storage (STG302) - ...Amazon Web Services
You’ve designed and built a well-architected data lake and ingested extreme amounts of structured and unstructured data. Now what? In this session, we explore real-world use cases where data scientists, developers, and researchers have discovered new and valuable ways to extract business insights using advanced analytics and machine learning. We review Amazon S3, Amazon Glacier, and Amazon EFS, the foundation for the analytics clusters and data engines. We also explore analytics tools and databases, including Amazon Redshift, Amazon Athena, Amazon EMR, Amazon QuickSight, Amazon Kinesis, Amazon RDS, and Amazon Aurora; and we review the AWS machine learning portfolio and AI services such as Amazon SageMaker, AWS Deep Learning AMIs, Amazon Rekognition, and Amazon Lex. We discuss how all of these pieces fit together to build intelligent applications.
Modern data is massive, quickly evolving, unstructured, and increasingly hard to catalog and understand from multiple consumers and applications. This presentation will guide you though the best practices for designing a robust data architecture, highlightning the benefits and typical challenges of data lakes and data warehouses. We will build a scalable solution based on managed services such as Amazon Athena, AWS Glue, and AWS Lake Formation.
In this workshop, learn how to connect devices to AWS IoT and AWS Greengrass. Understand the architecture, and install and configure device communication using AWS Greengrass. In addition, take advantage of the opportunity to create various device communication scenarios with AWS Greengrass and simulate the data flow with sensor data. Attendees in workshop need an AWS account and are asked to bring their laptop.
ABD209_Accelerating the Speed of Innovation with a Data Sciences Data & Analy...Amazon Web Services
"Historically, silos of data, analytics, and processes across functions, stages of development, and geography created a barrier to R&D efficiency. Gathering the right data necessary for decision-making was challenging due to issues of accessibility, trust, and timeliness. In this session, learn how Takeda is undergoing a transformation in R&D to increase the speed-to-market of high-impact therapies to improve patient lives. The Data and Analytics Hub was built, with Deloitte, to address these issues and support the efficient generation of data insights for functions such as clinical operations, clinical development, medical affairs, portfolio management, and R&D finance. In the AWS hosted data lake, this data is processed, integrated, and made available to business end users through data visualization interfaces, and to data scientists through direct connectivity. Learn how Takeda has achieved significant time reductions—from weeks to minutes—to gather and provision data that has the potential to reduce cycle times in drug development. The hub also enables more efficient operations and alignment to achieve product goals through cross functional team accountability and collaboration due to the ability to access the same cross domain data.
Session sponsored by Deloitte"
Artificial Intelligence nella realtà di oggi: come utilizzarla al meglioAmazon Web Services
L'intelligenza Artificiale è qui questa volta, per restare. Per le aziende, l'intelligenza artificiale si concretizza in soluzioni che migliorano l'esperienza dei clienti ottimizzando, automatizzando e personalizzando attività ad alto volume e riducendo al contempo costi e tempi, accelerando notevolmente il ritmo di innovazione. In questa sessione, approfondiremo i servizi AI di AWS che promuovo l'innovazione in azienda mantenendo la conformità con diversi regimi come HIPAA, PCI e altro. Infine, presenteremo le architetture AWS necessarie per supportare i carichi di lavoro di apprendimento automatico e deep learning.
Run Production Workloads on Spot, Save up to 90% (CMP306-R1) - AWS re:Invent ...Amazon Web Services
Amazon EC2 Spot Instances enable you to use spare EC2 computing capacity— capacity that is often 90% less than On-Demand prices. In this session, learn how to effectively harness Spot Instances for production workloads. We explore application requirements for using Spot Instances, best practices learned from thousands of customers, and the services that make it easy to use. Finally, we run through practical examples of how to use Spot for the most common production workloads, the common pitfalls customers run into, and how to avoid them.
What's New with Amazon Redshift ft. McDonald's (ANT350-R1) - AWS re:Invent 2018Amazon Web Services
Learn about the latest and hottest features of Amazon Redshift. We’ll deep dive into the architecture and inner workings of Amazon Redshift and discuss how the recent availability, performance, and manageability improvements we’ve made can significantly enhance your user experience. We’ll also share glimpse of what we are working on and our plans for the future. McDonald's will join us to share how they leverage a data lake powered by Redshift, Redshift spectrum and Athena to get quick insights.
[NEW LAUNCH!] How to build and deploy Windows file system in AWS using Amazon...Amazon Web Services
If you have compute-intensive workloads like high performance computing, machine learning, and media processing then this is the workshop for you! Our new file storage service, Amazon FSx for Lustre, provides compute-optimized storage with fully managed Lustre file systems that can deliver hundreds of gigabytes of throughput and sub-millisecond latencies. You will learn how to spin up an FSx for Lustre file system in minutes, feed data to it from an S3 data lake, run analyses while writing results back to S3, and then spin down the file system once the workload is finished.
SAP provides software that many organizations continue to use to manage core workload requirements, with a significant number of these organizations running their SAP workloads on AWS. However, SAP doesn’t need to be operated similarly in the cloud as it is on premise. AWS can still drive innovation, even in operating solutions from companies such as SAP. Join us to see how organizations who have a strong leverage on AWS, carry over their platform knowledge to SAP workloads. They can improve the efficiency of their application teams - from easier migrations, to reducing time spent in operations, and overall improving the flexibility of delivering SAP workloads.
M&E Leadership Session: The State of the Industry, What's New from AWS for M&...Amazon Web Services
In this wide-ranging keynote session, first hear from AWS VP Carla Stratfold on the major forces affecting the industry, then learn from AWS Global M&E Tech Lead Usman Shakeel about the latest and most exciting releases coming out of re:Invent relevant to the M&E industry. And finally, hear how technical leaders at the forefront of the industry are responding to accelerating changes in the media landscape.
Microservices on AWS: Architectural Patterns and Best Practices | AWS Summit ...AWS Summits
This session is the first of 5 sessions that will cover a fully functioning system we have built to demonstrate how to rapidly develop systems using the AWS platform. This session we will start with a demo and an architecture review in which we will break into the different subsystems. In the second part of the session we will zoom into the Microservices part of the solution.Microservices are an architectural and organizational approach to software development where software is composed of small independent services that communicate over well-defined APIs. This session demonstrates the use of services like Amazon ECS, AWS Cloud Map and Amazon API Gateway and can help you understand where you can utilize microservices architecture in your own organization and understand areas of potential savings and increased agility.
Alexa, Ask Jarvis to Create a Serverless App for Me (SRV315) - AWS re:Invent ...Amazon Web Services
Today, we can build and deploy a serverless application in minutes without having to write a line of code using pre-built AWS CloudFormation templates, or services such as the AWS Serverless Application Repository. But can we push the limits even more? In this workshop, we use the Serverless Application Repository combined with Amazon Alexa to create Iron Man's Jarvis look-a-like skill. You learn hands-on with Alexa, Amazon Lex, Amazon SageMaker, and the AWS Serverless Application Repository.
The Amazon.com Database Journey to AWS – Top 10 Lessons Learned (DAT326) - AW...Amazon Web Services
In this session, we share the top 10 lessons learned from migrating the online transaction processing (OLTP) and data warehouse (DW) databases used by Amazon.com to AWS services, such as Amazon Relational Database Service (Amazon RDS), Amazon Aurora, Amazon Redshift, and Amazon DynamoDB. We discuss the challenges associated with operating and managing legacy OLTP and DW databases at Amazon.com scale and how the Amazon.com team successfully executed the database freedom program across different organizations and geographies.
Enabling Transformation through Agility & Innovation - AWS Transformation Day...Amazon Web Services
Learn how AWS can help transform your business. With AWS, enterprises are becoming more agile, secure, and scalable. This helps to promote innovation, shorten cycles to respond to business requirements, increase employee productivity, and retain and recruit top talent.
Improve business performance, reduce costs, and reinvent your IT strategies. Topics include how to maximize the value of your Enterprise workloads with AWS, foster a culture of innovation, manage risk and security, and new ways to think about product development, how to modernize the delivery of IT services, and best practices for adopting the cloud at scale.
SKL208 - Turbocharge your Business with AI and Machine Learning - Tel Aviv Su...Boaz Ziniman
This session will focus on the basic building blocks of Artificial Intelligence (AI) and Machine Learning (ML) using AWS services. It will help you to identify use cases for ML with real-world examples, and help you create the right conditions for delivering successful ML-based solutions to your business.
TiVo: How to Scale New Products with a Data Lake on AWS and QuboleAmazon Web Services
In our webinar, representatives from TiVo, creator of a digital recording platform for television content, will explain how they implemented a new big data and analytics platform that dynamically scales in response to changing demand. You’ll learn how the solution enables TiVo to easily orchestrate big data clusters using Amazon Elastic Cloud Compute (Amazon EC2) and Amazon EC2 Spot instances that read data from a data lake on Amazon Simple Storage Service (Amazon S3) and how this reduces the development cost and effort needed to support its network and advertiser users. TiVo will share lessons learned and best practices for quickly and affordably ingesting, processing, and making available for analysis terabytes of streaming and batch viewership data from millions of households.
TiVo: How to Scale New Products with a Data Lake on AWS and QuboleAmazon Web Services
In our webinar, representatives from TiVo, creator of a digital recording platform for television content, will explain how they implemented a new big data and analytics platform that dynamically scales in response to changing demand. You’ll learn how the solution enables TiVo to easily orchestrate big data clusters using Amazon Elastic Cloud Compute (Amazon EC2) and Amazon EC2 Spot instances that read data from a data lake on Amazon Simple Storage Service (Amazon S3) and how this reduces the development cost and effort needed to support its network and advertiser users. TiVo will share lessons learned and best practices for quickly and affordably ingesting, processing, and making available for analysis terabytes of streaming and batch viewership data from millions of households.
AWS Data-Driven Insights Learning Series_ANZ Sep 2019 Part 2Amazon Web Services
AWS has been supporting companies across Australia and New Zealand to put their most innovative tools and technologies to work to achieve their business needs and goals. AWS and our ecosystem of partners has helped the likes of CP Mining, IntelliHQ, WesCEF, Oz Minerals, Woodside and many more to modernise their analytics and data architecture in order to successfully generate business value from their data.
This event series aimed to educate customers with a broader understanding of how to build next-gen data lakes and analytics platforms and make connections with AWS.
Whatever your mission, you need to empower your team to make smart decisions. Effective organizations use self-service analytics that combine data from multiple sources, to inform data-driven, timely problem-solving. Join AWS databases, analytics, machine learning, and blockchain expert, Darin Briskman, to explore how citizens in Canada and beyond are better served by organizations that promote decision-making through data.
Women in Big Data Forum’s mission is to strengthen the diversity in the big data field. As part of this initiative, they encourage and attract more female talent to the big data & analytics field and help them to connect, engage and grow.
AWS Summit Singapore 2019 | Big Data Analytics Architectural Patterns and Bes...AWS Summits
Speaker: Renee Lo, Head of Big Data, Analytics, and AI, ASEAN, AWS
Customer Speaker: Natalia Kozyura, Head of Innovation Center, FWD Group
We discuss architectural principles that simplify big data analytics. We'll apply these principles to various stages of big data processing: collect, store, process, analyse, and visualise. We'll discuss how to choose the right technology in each stage based on criteria such as data structure, query latency, cost, request rate, item size, data volume, durability, and so on. Finally, we provide reference architectures, design patterns, and best practices for assembling these technologies to solve your big data problems at the right cost.
McGraw-Hill Optimizes Analytics Workloads with DatabricksAmazon Web Services
Using Databricks, McGraw-Hill securely transformed itself from a collection of data silos with limited access to data and minimal collaboration to an organization with democratized access to data and machine learning. This ultimately enables its data teams to rapidly identify usage patterns predicting student performance, so they can make timely enhancements to the software that proactively guide at-risk students through the course material.
Join our webinar to learn:
- How a cloud-based unified analytics platform can help your company perform analytics faster, at lower cost.
- How to mitigate challenges presented by data silos so data science teams can collaborate effectively.
- How to implement data analytics infrastructure to put models into production quickly
In this session, we show you how to understand what data you have, how to drive insights, and how to make predictions using purpose-built AWS services. Learn about the common pitfalls of building data lakes and discover how to successfully drive analytics and insights from your data. Also learn how services such as Amazon S3, AWS Glue, Amazon Redshift, Amazon Athena, Amazon EMR, Amazon Kinesis, and Amazon Machine Learning (Amazon ML) services work together to build a successful data lake for various roles, including data scientists and business users.
From Insights to Action, How to build and maintain a Data Driven Organization...Amazon Web Services Korea
데이터는 혁신과 변혁의 토대입니다. 비즈니스 혁신을 이끄는 혁신은 특정 시점의 전략이나 솔루션이 아니라 성장을 위한 반복적이고 집단적인 계획입니다. 혁신에 이러한 접근 방식을 채택하는 기업은 전략과 비즈니스 문화에서 데이터를 기반으로 하는 경우가 많습니다. 이러한 접근 방식을 개발하려면 리더가 데이터를 조직의 자산처럼 취급하고 조직이 더 나은 비즈니스 성과를 위해 데이터를 활용할 수 있도록 권한을 부여해야 합니다. AWS와 Amazon이 어떻게 데이터와 분석을 활용하여 확장 가능한 비즈니스 효율성을 창출하고 고객의 가장 복잡한 문제를 해결하는 메커니즘을 개발했는지 알아보십시오.
GPSTEC201_Building an Artificial Intelligence Practice for Consulting PartnersAmazon Web Services
Companies around the world are looking at using artificial intelligence and machine learning to launch new innovative products and services and to drive efficiencies via automation in their businesses. Come to this session to understand why you should consider building an AI/ML practice in your consulting company. Learn the importance of having strong data engineering skills, including data annotation, and get some tips on building a data science team that can deliver customer projects.
Presentation on ISV Best Practices by Stanley Chan, Head of Technology Partners, APAC, AWS and Pete Yamasaki, Regional Director, APAC, Druva, at AWS Partner Summit Mumbai 2018
Cloud migration is more than simply a business efficiency or a cost-saving measure. It’s a critical step towards digital transformation, innovation and operational resilience that has opened up opportunities for those who’ve embraced cloud adoption.
Whether you are looking to embark on your cloud migration or scaling the number of applications you’re moving to the cloud, it does not need to be a daunting task or one that you go at alone. AWS offers 10 years of experience helping businesses to efficiently move their legacy on-premises systems to the cloud. We work closely alongside numerous local delivery partners to help you meet your business needs.
Our Cloud Migration insights forum helps you to learn how to simplify your cloud journey with AWS.
ATC302_How to Leverage AWS Machine Learning Services to Analyze and Optimize ...Amazon Web Services
In this session, you’ll learn how AdTech companies use AWS services like Glue, Athena, Quicksight, and EMR to analyze your Google DoubleClick Campaign Manager data at scale without the burden of infrastructure or worries about server maintenance. We’ll live-process a click stream so you can see how Machine Learning can help maximize your revenue by finding the most optimal path of a campaign and we’ll look at a real world demo from A9’s Advertising Science Team of how they use the data to build Look-alike Model in their projects.
Similar to AWS Data-Driven Insights Learning Series ANZ Sep 2019 Part 1 (20)
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Amazon Web Services
Il Forecasting è un processo importante per tantissime aziende e viene utilizzato in vari ambiti per cercare di prevedere in modo accurato la crescita e distribuzione di un prodotto, l’utilizzo delle risorse necessarie nelle linee produttive, presentazioni finanziarie e tanto altro. Amazon utilizza delle tecniche avanzate di forecasting, in parte questi servizi sono stati messi a disposizione di tutti i clienti AWS.
In questa sessione illustreremo come pre-processare i dati che contengono una componente temporale e successivamente utilizzare un algoritmo che a partire dal tipo di dato analizzato produce un forecasting accurato.
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Amazon Web Services
La varietà e la quantità di dati che si crea ogni giorno accelera sempre più velocemente e rappresenta una opportunità irripetibile per innovare e creare nuove startup.
Tuttavia gestire grandi quantità di dati può apparire complesso: creare cluster Big Data su larga scala sembra essere un investimento accessibile solo ad aziende consolidate. Ma l’elasticità del Cloud e, in particolare, i servizi Serverless ci permettono di rompere questi limiti.
Vediamo quindi come è possibile sviluppare applicazioni Big Data rapidamente, senza preoccuparci dell’infrastruttura, ma dedicando tutte le risorse allo sviluppo delle nostre le nostre idee per creare prodotti innovativi.
Ora puoi utilizzare Amazon Elastic Kubernetes Service (EKS) per eseguire pod Kubernetes su AWS Fargate, il motore di elaborazione serverless creato per container su AWS. Questo rende più semplice che mai costruire ed eseguire le tue applicazioni Kubernetes nel cloud AWS.In questa sessione presenteremo le caratteristiche principali del servizio e come distribuire la tua applicazione in pochi passaggi
Vent'anni fa Amazon ha attraversato una trasformazione radicale con l'obiettivo di aumentare il ritmo dell'innovazione. In questo periodo abbiamo imparato come cambiare il nostro approccio allo sviluppo delle applicazioni ci ha permesso di aumentare notevolmente l'agilità, la velocità di rilascio e, in definitiva, ci ha consentito di creare applicazioni più affidabili e scalabili. In questa sessione illustreremo come definiamo le applicazioni moderne e come la creazione di app moderne influisce non solo sull'architettura dell'applicazione, ma sulla struttura organizzativa, sulle pipeline di rilascio dello sviluppo e persino sul modello operativo. Descriveremo anche approcci comuni alla modernizzazione, compreso l'approccio utilizzato dalla stessa Amazon.com.
Come spendere fino al 90% in meno con i container e le istanze spot Amazon Web Services
L’utilizzo dei container è in continua crescita.
Se correttamente disegnate, le applicazioni basate su Container sono molto spesso stateless e flessibili.
I servizi AWS ECS, EKS e Kubernetes su EC2 possono sfruttare le istanze Spot, portando ad un risparmio medio del 70% rispetto alle istanze On Demand. In questa sessione scopriremo insieme quali sono le caratteristiche delle istanze Spot e come possono essere utilizzate facilmente su AWS. Impareremo inoltre come Spreaker sfrutta le istanze spot per eseguire applicazioni di diverso tipo, in produzione, ad una frazione del costo on-demand!
In recent months, many customers have been asking us the question – how to monetise Open APIs, simplify Fintech integrations and accelerate adoption of various Open Banking business models. Therefore, AWS and FinConecta would like to invite you to Open Finance marketplace presentation on October 20th.
Event Agenda :
Open banking so far (short recap)
• PSD2, OB UK, OB Australia, OB LATAM, OB Israel
Intro to Open Finance marketplace
• Scope
• Features
• Tech overview and Demo
The role of the Cloud
The Future of APIs
• Complying with regulation
• Monetizing data / APIs
• Business models
• Time to market
One platform for all: a Strategic approach
Q&A
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Amazon Web Services
Per creare valore e costruire una propria offerta differenziante e riconoscibile, le startup di successo sanno come combinare tecnologie consolidate con componenti innovativi creati ad hoc.
AWS fornisce servizi pronti all'utilizzo e, allo stesso tempo, permette di personalizzare e creare gli elementi differenzianti della propria offerta.
Concentrandoci sulle tecnologie di Machine Learning, vedremo come selezionare i servizi di intelligenza artificiale offerti da AWS e, anche attraverso una demo, come costruire modelli di Machine Learning personalizzati utilizzando SageMaker Studio.
OpsWorks Configuration Management: automatizza la gestione e i deployment del...Amazon Web Services
Con l'approccio tradizionale al mondo IT per molti anni è stato difficile implementare tecniche di DevOps, che finora spesso hanno previsto attività manuali portando di tanto in tanto a dei downtime degli applicativi interrompendo l'operatività dell'utente. Con l'avvento del cloud, le tecniche di DevOps sono ormai a portata di tutti a basso costo per qualsiasi genere di workload, garantendo maggiore affidabilità del sistema e risultando in dei significativi miglioramenti della business continuity.
AWS mette a disposizione AWS OpsWork come strumento di Configuration Management che mira ad automatizzare e semplificare la gestione e i deployment delle istanze EC2 per mezzo di workload Chef e Puppet.
Scopri come sfruttare AWS OpsWork a garanzia e affidabilità del tuo applicativo installato su Instanze EC2.
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsAmazon Web Services
Vuoi conoscere le opzioni per eseguire Microsoft Active Directory su AWS? Quando si spostano carichi di lavoro Microsoft in AWS, è importante considerare come distribuire Microsoft Active Directory per supportare la gestione, l'autenticazione e l'autorizzazione dei criteri di gruppo. In questa sessione, discuteremo le opzioni per la distribuzione di Microsoft Active Directory su AWS, incluso AWS Directory Service per Microsoft Active Directory e la distribuzione di Active Directory su Windows su Amazon Elastic Compute Cloud (Amazon EC2). Trattiamo argomenti quali l'integrazione del tuo ambiente Microsoft Active Directory locale nel cloud e l'utilizzo di applicazioni SaaS, come Office 365, con AWS Single Sign-On.
Dal riconoscimento facciale al riconoscimento di frodi o difetti di fabbricazione, l'analisi di immagini e video che sfruttano tecniche di intelligenza artificiale, si stanno evolvendo e raffinando a ritmi elevati. In questo webinar esploreremo le possibilità messe a disposizione dai servizi AWS per applicare lo stato dell'arte delle tecniche di computer vision a scenari reali.
Amazon Web Services e VMware organizzano un evento virtuale gratuito il prossimo mercoledì 14 Ottobre dalle 12:00 alle 13:00 dedicato a VMware Cloud ™ on AWS, il servizio on demand che consente di eseguire applicazioni in ambienti cloud basati su VMware vSphere® e di accedere ad una vasta gamma di servizi AWS, sfruttando a pieno le potenzialità del cloud AWS e tutelando gli investimenti VMware esistenti.
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
Crea la tua prima serverless ledger-based app con QLDB e NodeJSAmazon Web Services
Molte aziende oggi, costruiscono applicazioni con funzionalità di tipo ledger ad esempio per verificare lo storico di accrediti o addebiti nelle transazioni bancarie o ancora per tenere traccia del flusso supply chain dei propri prodotti.
Alla base di queste soluzioni ci sono i database ledger che permettono di avere un log delle transazioni trasparente, immutabile e crittograficamente verificabile, ma sono strumenti complessi e onerosi da gestire.
Amazon QLDB elimina la necessità di costruire sistemi personalizzati e complessi fornendo un database ledger serverless completamente gestito.
In questa sessione scopriremo come realizzare un'applicazione serverless completa che utilizzi le funzionalità di QLDB.
Con l’ascesa delle architetture di microservizi e delle ricche applicazioni mobili e Web, le API sono più importanti che mai per offrire agli utenti finali una user experience eccezionale. In questa sessione impareremo come affrontare le moderne sfide di progettazione delle API con GraphQL, un linguaggio di query API open source utilizzato da Facebook, Amazon e altro e come utilizzare AWS AppSync, un servizio GraphQL serverless gestito su AWS. Approfondiremo diversi scenari, comprendendo come AppSync può aiutare a risolvere questi casi d’uso creando API moderne con funzionalità di aggiornamento dati in tempo reale e offline.
Inoltre, impareremo come Sky Italia utilizza AWS AppSync per fornire aggiornamenti sportivi in tempo reale agli utenti del proprio portale web.
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareAmazon Web Services
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
In queste slide, gli esperti AWS e VMware presentano semplici e pratici accorgimenti per facilitare e semplificare la migrazione dei carichi di lavoro Oracle accelerando la trasformazione verso il cloud, approfondiranno l’architettura e dimostreranno come sfruttare a pieno le potenzialità di VMware Cloud ™ on AWS.
Amazon Elastic Container Service (Amazon ECS) è un servizio di gestione dei container altamente scalabile, che semplifica la gestione dei contenitori Docker attraverso un layer di orchestrazione per il controllo del deployment e del relativo lifecycle. In questa sessione presenteremo le principali caratteristiche del servizio, le architetture di riferimento per i differenti carichi di lavoro e i semplici passi necessari per poter velocemente migrare uno o più dei tuo container.
25. 2727
Nitric Acid Yield Optimisation
Production
Moisture
V1
V2
Operator DashboardYield Algorithm
Extract
Data for selected
sensors extracted
every 5 mins using
Macroview datapump
Ingest
Raw data ingested
by AWS, meta tags
applied and results
stored in data lake
Process
Data cleansed and
engineered using a
Spark cluster and
stored in data lake
Serve
Curated data loaded to
data mart every 15
mins and optimisation
model applied
Visualise
Dashboard performs
live query of data
mart to advise
operating conditions
Raw Data
37. Fastest way to build secure data lakes
Data Lake Storage
Data
Catalog
Access
ControlBlueprints ML-based
data prep
Lake Formation
Data Lakes AWS Glue
Amazon Redshift
Data warehousing
Amazon EMR
Hadoop + Spark
Athena
Interactive analytics
Amazon
QuickSight
Comprehensive list of integrated tools
enable every user equally
Centralized management of fine
grained permission empower security
officers
Simplified ingest and cleaning enables
data engineers to build faster
Cost effective, durable storage with
global replication capabilities
44. Workflows : Orchestrate repeatable data pipelines
Easy way to create and visualise
you business transformation
rules
Allows for parameters and
pipeline state to be shared
across stages
Dynamic views allow inspection
of current running workflows
for diagnostic and current state
information.
45. Simplified and more granular security permissions
Control data access with simple
grant and revoke permissions
Specify permissions on tables
and columns rather than on
buckets and objects
Easily view policies granted to a
particular user
Audit all data access at one
place
47. Search and collaborate across multiple teams and users
Text based search across all of
your metadata
Add attributes like Data owners,
stewards, and other as table
properties
Add data sensitivity level,
column definitions, and others
as column properties
48. AWS Lake Formation pricing
No additional charges – Only pay for the
underlying services used.
58. H O W W E C A N H E L P
• Brainstorming
• Data platform architecture
• Building of prototype within your accounts that can be brought into production
• Work side-by-side with Amazon experts
Data Lab
• Practical education on Big Data and analytics for new and experienced
practitioners
• Learn best practice solution architecture for building modern data
platforms
Data & Analytics Learning Training and Certification