This document discusses how big data and machine learning can be combined using Amazon Web Services (AWS). It covers common big data challenges around which tools to use, what data is available, and how to get started. It then demonstrates how to populate and query a data catalog on AWS to understand available data. Finally, it shows how machine learning can be driven by big data to generate better insights and products using agile AWS services.
Transform Government IT with VMware Cloud on AWS, an Integrated Hybrid SolutionAmazon Web Services
Government agencies are increasingly turning to commercial cloud service providers for the infrastructure flexibility to achieve consolidation, application modernization, and disaster recovery goals. For government customers running vSphere workloads, VMware and AWS have teamed up to provide a hybrid-cloud solution that eliminates the complexity and intensive resource management required to adopt the cloud. VMware Cloud on AWS™ removes traditional barriers to hybrid-cloud portability by integrating VMware Software-Defined Data Center (SDDC) technologies with AWS global infrastructure and application services. Customers can run VMware SDDC solutions on dedicated, bare-metal AWS infrastructure to create a common-cloud infrastructure, with unified deployment and operations across on-premises and public-cloud environments. Don’t miss this opportunity to discover why organizations are using VMware Cloud on AWS to bring to market hybrid-cloud strategies that streamline service delivery and your ability to achieve your mission.
Tim Hearn, Director, UK Public Sector, VMWare UK; Paul Bockelman, Senior Manager, Amazon Web Services
Mission (Not) Impossible: Applying NIST 800-53 High Impact-Controls on AWS fo...Amazon Web Services
The document discusses applying the NIST 800-53 high impact controls on AWS for GDPR compliance. It describes how AWS and third-party security tools like Trend Micro can help customers automate compliance with these controls by leveraging AWS services for identity and access management, logging, networking, and security tools for intrusion prevention, firewalls, and more. An AWS CloudFormation template called the Enterprise Accelerator provides an automated reference deployment of Trend Micro with AWS to help customers meet key NIST controls and simplify GDPR compliance efforts.
Achieving Your Department Objectives: Providing Better Citizen Services at Lo...Amazon Web Services
Most likely, your organisation is not in the business of running data centers, yet a significant amount of time and money is spent doing just that. AWS provides a way to acquire and use infrastructure on-demand, so that you pay only for what you consume. This puts more money back into the business, so that you can innovate more, expand faster, and be better-positioned to take advantage of new opportunities.
Fabrizio Pappalardo, Partner Manager, AWS
Building the Organisation of the Future: Leveraging Artificial Intelligence a...Amazon Web Services
Artificial intelligence and machine learning are no longer the stuff of science fiction. Organisations of all sizes are using these tools to create innovative artificial intelligences applications – namely, Amazon.com's own retail experience. Join us for an inside look at how Amazon thinks about this technology, and hear from Skinvision on how they’re using machine learning for early skin-cancer detection. Through these stories, gain insight into a range of new machine learning services on AWS for use in your own business.
Breght Boschker, CTO, Skinvision
Miguel Rojo Rossi, Solutions Architect Lead, AWS
Transforming Enterprise IT - Virtual Transformation Day Feb 2019Amazon Web Services
Speaker: Wesley Wilks, Dan Gallivan
As more and more enterprises start down the path of their digital transformation, the pressure on their IT organizations to support innovation across the business couldn’t be higher. In this session, we will outline a number of cutting-edge technologies as well as an operating model that will allow IT to position itself as a business enabler and not a blocker. We will be sharing some mechanisms that will enable the IT organization to meet the pace of innovation that is being set by the business while giving them the flexibility to leverage existing assets.
AWS Transformation Day is designed for enterprise organizations looking to make the move to the cloud in order to become more responsive, agile and innovative, while still staying secure and compliant. Join us for this virtual event and we'll share our experiences of helping enterprise customers accelerate the pace of migration and adoption of strategic services.
We recommend this event for IT and business leaders who are looking to create sustainable benefits and a competitive advantage by using the AWS Cloud.
Cloud Choices Quantifying the Cost and Risk Implications of CloudAmazon Web Services
- The document discusses quantifying the costs and risks of cloud computing choices. It addresses how perception and cognitive biases can impact outcomes of IT projects.
- Key factors that influence cloud adoption outcomes are identified, including focus on business impact, accountability, learning from past projects, planning, stakeholder consensus, leadership, and execution capabilities.
- Methods are presented for assessing complexity, decisiveness, and measuring costs, risks, and value to make informed cloud choices and reduce risks of cloud migration.
How Different Large Organizations are Approaching Cloud AdoptionAmazon Web Services
The implementation of highly scalable, easy-to-deploy technology is transforming enterprises, but it’s not a one-size-fits-all approach. Organizations begin their cloud adoption journeys in many ways. Some start with pilot projects and others jump into mission-critical programs, but they are all starting with an existing infrastructure. Adopting cloud doesn’t mean scrapping it all and starting over. This session explores how organizations are using cloud while building on their existing technology and lessons they’ve learned along the way. In this session we will discuss when and how to leverage hybrid cloud computing to meet the needs of the enterprise. We will cover popular hybrid cloud use cases in enterprises, pillars to design a secure hybrid cloud environment and how to get started with AWS.
Cloud Choices- Quantifying the Cost and Risk Implications of Cloud.pdfAmazon Web Services
This document discusses quantifying the costs and risks of cloud choices. It begins with an introduction of the presenters and an overview of topics to be covered, including why IT projects fail, best approaches to cloud adoption, and methods for quantifying costs, risks, and value. The document then explores various factors involved in cloud choices, such as focus on business impact versus technology, accountability, learning from past projects, planning, stakeholder consensus, leadership, and execution capabilities. Overall models and frameworks are presented for assessing decisions, risks, and developing business cases around cloud migration.
Transform Government IT with VMware Cloud on AWS, an Integrated Hybrid SolutionAmazon Web Services
Government agencies are increasingly turning to commercial cloud service providers for the infrastructure flexibility to achieve consolidation, application modernization, and disaster recovery goals. For government customers running vSphere workloads, VMware and AWS have teamed up to provide a hybrid-cloud solution that eliminates the complexity and intensive resource management required to adopt the cloud. VMware Cloud on AWS™ removes traditional barriers to hybrid-cloud portability by integrating VMware Software-Defined Data Center (SDDC) technologies with AWS global infrastructure and application services. Customers can run VMware SDDC solutions on dedicated, bare-metal AWS infrastructure to create a common-cloud infrastructure, with unified deployment and operations across on-premises and public-cloud environments. Don’t miss this opportunity to discover why organizations are using VMware Cloud on AWS to bring to market hybrid-cloud strategies that streamline service delivery and your ability to achieve your mission.
Tim Hearn, Director, UK Public Sector, VMWare UK; Paul Bockelman, Senior Manager, Amazon Web Services
Mission (Not) Impossible: Applying NIST 800-53 High Impact-Controls on AWS fo...Amazon Web Services
The document discusses applying the NIST 800-53 high impact controls on AWS for GDPR compliance. It describes how AWS and third-party security tools like Trend Micro can help customers automate compliance with these controls by leveraging AWS services for identity and access management, logging, networking, and security tools for intrusion prevention, firewalls, and more. An AWS CloudFormation template called the Enterprise Accelerator provides an automated reference deployment of Trend Micro with AWS to help customers meet key NIST controls and simplify GDPR compliance efforts.
Achieving Your Department Objectives: Providing Better Citizen Services at Lo...Amazon Web Services
Most likely, your organisation is not in the business of running data centers, yet a significant amount of time and money is spent doing just that. AWS provides a way to acquire and use infrastructure on-demand, so that you pay only for what you consume. This puts more money back into the business, so that you can innovate more, expand faster, and be better-positioned to take advantage of new opportunities.
Fabrizio Pappalardo, Partner Manager, AWS
Building the Organisation of the Future: Leveraging Artificial Intelligence a...Amazon Web Services
Artificial intelligence and machine learning are no longer the stuff of science fiction. Organisations of all sizes are using these tools to create innovative artificial intelligences applications – namely, Amazon.com's own retail experience. Join us for an inside look at how Amazon thinks about this technology, and hear from Skinvision on how they’re using machine learning for early skin-cancer detection. Through these stories, gain insight into a range of new machine learning services on AWS for use in your own business.
Breght Boschker, CTO, Skinvision
Miguel Rojo Rossi, Solutions Architect Lead, AWS
Transforming Enterprise IT - Virtual Transformation Day Feb 2019Amazon Web Services
Speaker: Wesley Wilks, Dan Gallivan
As more and more enterprises start down the path of their digital transformation, the pressure on their IT organizations to support innovation across the business couldn’t be higher. In this session, we will outline a number of cutting-edge technologies as well as an operating model that will allow IT to position itself as a business enabler and not a blocker. We will be sharing some mechanisms that will enable the IT organization to meet the pace of innovation that is being set by the business while giving them the flexibility to leverage existing assets.
AWS Transformation Day is designed for enterprise organizations looking to make the move to the cloud in order to become more responsive, agile and innovative, while still staying secure and compliant. Join us for this virtual event and we'll share our experiences of helping enterprise customers accelerate the pace of migration and adoption of strategic services.
We recommend this event for IT and business leaders who are looking to create sustainable benefits and a competitive advantage by using the AWS Cloud.
Cloud Choices Quantifying the Cost and Risk Implications of CloudAmazon Web Services
- The document discusses quantifying the costs and risks of cloud computing choices. It addresses how perception and cognitive biases can impact outcomes of IT projects.
- Key factors that influence cloud adoption outcomes are identified, including focus on business impact, accountability, learning from past projects, planning, stakeholder consensus, leadership, and execution capabilities.
- Methods are presented for assessing complexity, decisiveness, and measuring costs, risks, and value to make informed cloud choices and reduce risks of cloud migration.
How Different Large Organizations are Approaching Cloud AdoptionAmazon Web Services
The implementation of highly scalable, easy-to-deploy technology is transforming enterprises, but it’s not a one-size-fits-all approach. Organizations begin their cloud adoption journeys in many ways. Some start with pilot projects and others jump into mission-critical programs, but they are all starting with an existing infrastructure. Adopting cloud doesn’t mean scrapping it all and starting over. This session explores how organizations are using cloud while building on their existing technology and lessons they’ve learned along the way. In this session we will discuss when and how to leverage hybrid cloud computing to meet the needs of the enterprise. We will cover popular hybrid cloud use cases in enterprises, pillars to design a secure hybrid cloud environment and how to get started with AWS.
Cloud Choices- Quantifying the Cost and Risk Implications of Cloud.pdfAmazon Web Services
This document discusses quantifying the costs and risks of cloud choices. It begins with an introduction of the presenters and an overview of topics to be covered, including why IT projects fail, best approaches to cloud adoption, and methods for quantifying costs, risks, and value. The document then explores various factors involved in cloud choices, such as focus on business impact versus technology, accountability, learning from past projects, planning, stakeholder consensus, leadership, and execution capabilities. Overall models and frameworks are presented for assessing decisions, risks, and developing business cases around cloud migration.
Introduction to the Security Perspective of the Cloud Adoption Framework (CAF)Amazon Web Services
by Michael Wasielewski, CISSP, CCSP, AWS
The Security Perspective of the AWS Cloud Adoption Framework (CAF) provides a framework for maturation via a structured program that incorporates best practices and processes to define, build, and optimize how you operate security controls in the AWS platform. The Security perspective of the CAF provides a set of 5 core foundational theme designed to help you structure your selection and implementation of controls that are right for your business: IAM, Detective Controls, Infrastructure Security, Data Protection, and Incident response. During this session, we address how to put the Security Perspective of the CAF into practice.
The document discusses lessons learned from Jonathan Allen's career in enterprise IT and strategies for moving to the cloud. It covers compelling reasons for cloud migration like agility, cost reduction, and facility decisions. It also discusses challenges of reskilling employees and account setup hurdles. The rest of the document outlines methods for modern product development using DevOps, agile teams, and design thinking. It emphasizes the importance of continuous testing and achieving organizational flow.
Transforming your Business Ops Team for Cloud - AWS Summit Sydney 2018Amazon Web Services
Transforming Your Business Operations Team for Cloud
As you migrate to the cloud your operations structure and practices evolve. Putting aside the technology, as a business owner how does this impact you? This session will highlight how automation and cloud operations models affect the way your business operates. You will learn from our shared customer stories, get a quick change management 101 for cloud operations and understand how Amazon Managed Services could allow you to focus more on delighting your customers.
Louise Stigwood, Enterprise Sales Manager, Amazon Web Services
The first step towards knowing your customer is to collect and extract insights and actionable information from your data. Learn how AWS enables you to cost efficiently store any amount of data and build an agile approach to data mining and visualization - helping you to make efficient business decisions and targeted offerings.
1) The document discusses building a minimum viable product (MVP) using Amazon Web Services (AWS).
2) It provides an example of an MVP for an omni-channel messenger platform that was built from 2017 to connect ecommerce stores to customers via web chat, Facebook Messenger, WhatsApp, and other channels.
3) The founder discusses how they started with an MVP in 2017 with 200 ecommerce stores in Hong Kong and Taiwan, and have since expanded to over 5000 clients across Southeast Asia using AWS for scaling.
Learn how you can use AWS to adapt to a changing interconnected market, and take advantage of global responsiveness and minimal barriers to innovation. AWS can help you create value for the business in addition to saving costs on infrastructure. Gain insights from lessons learned and recommendations on how to accelerate the path to business value.
Containers are an increasingly important way for developers to package and deploy their applications. AWS offers multiple container products to help you deploy, manage, and scale containers in production: Amazon Elastic Container Service (ECS) is a fully-managed container orchestration service; Amazon ECS for Kubernetes (EKS) is a managed service that makes it easy for you to run Kubernetes on AWS; Amazon Elastic Container Registry (ECR) is a fully-managed Docker container registry; and AWS Fargate is a technology for deploying and managing containers without having to manage the underlying infrastructure.
At AWS, security is job zero. AWS has worked with global enterprises to meet their respective security requirements and has developed a broad portfolio of services to help customers run highly secure workloads in the cloud. This session will describe how Amazon has been managing security of the cloud at hyper-scale and adding new capabilities that help secure customer applications and data such as Inspector, GuardDuty, and Macie. Leave this session with a better understanding of how these services operate and how easy it is to integrate them into your secure cloud environment.
Presenter: Kurt Gray, Global Account Solutions Architect, AWS
How to Enable Single Sign On to Multiple AWS Accounts and Business Applicatio...Amazon Web Services
by Vijay Sharma, Senior Product Manager, AWS
Creating multiple AWS accounts helps manage AWS resources for different users, teams, and applications, but managing access for multiple AWS accounts can be difficult to scale. AWS Single Sign-On (SSO), a new cloud SSO service, makes it easy to sign in to multiple AWS accounts and business applications. You will learn how to use AWS SSO and AWS Directory Service to enable users to access their AWS accounts and business applications using their existing corporate credentials. You will also learn how to manage user permissions centrally to AWS resources when users access the AWS Management Console using AWS SSO.
As Public Sector development teams transition to cloud-based architectures and adopt more agile processes, the tools they need to support their development cycles will change. In this session, we'll take you through the transition that Amazon made to a service-oriented architecture over a decade ago. We will share the lessons we learned, the processes we adopted, and the tools we built to increase both our agility and reliability. We will also introduce you to the AWS Code family services which were born out of Amazon's internal DevOps experience and are utilised by many Public Sector customers globally.
Mario Vlachakis, Solutions Architect, AWS
Distinguishing the hype from reality can be a bit confusing, especially when you consider the attention that AI gets from the media and commentators. So, how can your organisation get started and put AI to work for you? That is the question I will answer in this talk. From greater customer intimacy, increasing competitive advantage and improving efficiency, I will discuss and show how AI can be used today and help the organisation in more impactful ways.
Essere conformi al GDPR, il regolamento generale sulla protezione dei dati personali entrato in vigore il 25 maggio 2018, può risultare complicato ma AWS ha gli strumenti per guidarti attraverso tutto il processo. In questa sessione approfondiremo i meccanismi di automazione che AWS offre ai propri clienti per aiutarli nell'implementazione dei propri programmi di sicurezza e privacy e vedremo quali sono gli strumenti specifici messi a disposizione da AWS per indirizzare alcuni requisiti del GDPR.
What IT Transformation Really Means for the EnterpriseTom Laszewski
The document discusses the challenges facing enterprises and how transformation is needed. It outlines both the disadvantages enterprises currently face, such as high customer expectations and constant change, as well as advantages they have like existing customer bases and resources. It then discusses how enterprises can transform by adopting new mechanisms, architectures, cultures and organizations that promote innovation, such as developing minimum viable products, using microservices architectures, and establishing small autonomous teams. New technologies like serverless computing and machine learning are also enabling this transformation. Overall, the document argues that enterprises of all kinds must transform to keep up with the changing environment.
Jonathan Allen outlines a 12-step approach to scaling talent transformation to the cloud. The key steps include: accepting the change, providing training and hands-on experience, creating small "two-pizza" cross-functional teams, bringing in experts, having teams build something real, scaling learning by splitting teams, pursuing certification, recognizing expertise, leading by example, and creating a unified job structure. The approach emphasizes organizational change management and building cloud skills at scale through a structured knowledge progression.
Security & Compliance are very important for most businesses. Learn how AWS enables you to securely use the cloud for you most vital business applications and how you can ensure that you are compliant with a large set of security standards and government regulations like GDPR.
Security, Risk and Compliance of Your Cloud Journey - Tel Aviv Summit 2018Amazon Web Services
How can you ensure your environment is Secure? How can you implement an effective governance model in your organization? The AWS Cloud Adoption Framework (CAF) and its Security Perspective provide a structured approach to make risk based decisions, build security guardrails and meet your compliance goals as you migrate to AWS. The Security perspective of the CAF provides a set of 5 core themes designed to help you structure your selection and implementation of controls that are right for your business: IAM, Detective Controls, Infrastructure Security, Data Protection and Incident response. In this session you will learn what it takes to lead a Secure Cloud Journey for your organization and make key strategic decisions.
Mastering the Secret Sauce to SaaS - Adrian De Luca - AWS TechShift ANZ 2018Amazon Web Services
Gartner predicts APAC cloud services spend will be $15.8B by 2020. With the SaaS segment growing at an average of 24% year on year, your customers are increasingly expecting to consume software as a service. In this session you will hear how SaaS delivery accelerates customer adoption, helping you go global, use the AWS SaaS Reference Architecture to implement best practices and leverage AWS programs to help you achieve success on your journey.
How Nubank Automates Fine-Grained Security with IAM, AWS Lambda, and CI/CD (F...Amazon Web Services
Cloud-native and with security integrated early in the software development process, Nubank is the largest digital bank in the world outside of Asia. Demand for higher levels of service and value, constantly evolving technology capabilities, and stringent regulatory requirements are all powerful forces reshaping retail banking. In this session, Nubank CTO Edward Wible discusses how the company mixes engineering culture, security philosophy and structure, automation, and integration with AWS security services. Learn how to leverage the day-to-day software development workflow for extensive security and maximum engineering throughput while minimizing the operational pain of running a large infrastructure.
Starting your Cloud Transformation Journey - Tel Aviv Summit 2018Boaz Ziniman
Understand the values your organization can get from the cloud is the first step in your cloud transformation journey.
We will share best practices for getting started with Cloud Computing and not only from the technical perspective (culture change and gains, building teams, business case, project selection and more). Join us for this session and Let's Start your Cloud journey.
This document summarizes an AWS seminar presentation on AI and machine learning services. It discusses AWS's mission to put machine learning in the hands of every developer and data scientist. It provides an overview of AWS machine learning application services like Amazon Rekognition, Polly, Lex, and Translate. It also covers AWS machine learning platform services like Amazon SageMaker and deep learning frameworks. Finally, it discusses AWS machine learning infrastructure services like EC2 P3 instances, the Deep Learning AMI, and AWS DeepLens.
This document discusses big data and machine learning. It begins by defining big data using the 5 V's: volume, velocity, variety, veracity, and value. It then discusses challenges organizations face with big data, including which tools to use and determining what data they have. The remainder discusses how to gain business value from data through architectures like data lakes, analytics, and machine learning services on AWS. It provides an example of how Netflix evolved its data pipeline and emphasizes agility. Finally, it discusses how machine learning relies on big data and new tools are needed for data scientists.
Building a Data Lake in Amazon S3 & Amazon Glacier (STG401-R1) - AWS re:Inven...Amazon Web Services
The document discusses building a data lake using Amazon S3 and Amazon Glacier for storage. It covers topics like what is big data, what is a data lake, achievable business outcomes from a data lake, securing the data lake, and examples of what can be done with analytics services on AWS. The presentation provides examples of using services like Amazon Comprehend, Amazon Transcribe, Kinesis, Athena and QuickSight for natural language processing, audio analysis, real-time streaming and visualization.
Introduction to the Security Perspective of the Cloud Adoption Framework (CAF)Amazon Web Services
by Michael Wasielewski, CISSP, CCSP, AWS
The Security Perspective of the AWS Cloud Adoption Framework (CAF) provides a framework for maturation via a structured program that incorporates best practices and processes to define, build, and optimize how you operate security controls in the AWS platform. The Security perspective of the CAF provides a set of 5 core foundational theme designed to help you structure your selection and implementation of controls that are right for your business: IAM, Detective Controls, Infrastructure Security, Data Protection, and Incident response. During this session, we address how to put the Security Perspective of the CAF into practice.
The document discusses lessons learned from Jonathan Allen's career in enterprise IT and strategies for moving to the cloud. It covers compelling reasons for cloud migration like agility, cost reduction, and facility decisions. It also discusses challenges of reskilling employees and account setup hurdles. The rest of the document outlines methods for modern product development using DevOps, agile teams, and design thinking. It emphasizes the importance of continuous testing and achieving organizational flow.
Transforming your Business Ops Team for Cloud - AWS Summit Sydney 2018Amazon Web Services
Transforming Your Business Operations Team for Cloud
As you migrate to the cloud your operations structure and practices evolve. Putting aside the technology, as a business owner how does this impact you? This session will highlight how automation and cloud operations models affect the way your business operates. You will learn from our shared customer stories, get a quick change management 101 for cloud operations and understand how Amazon Managed Services could allow you to focus more on delighting your customers.
Louise Stigwood, Enterprise Sales Manager, Amazon Web Services
The first step towards knowing your customer is to collect and extract insights and actionable information from your data. Learn how AWS enables you to cost efficiently store any amount of data and build an agile approach to data mining and visualization - helping you to make efficient business decisions and targeted offerings.
1) The document discusses building a minimum viable product (MVP) using Amazon Web Services (AWS).
2) It provides an example of an MVP for an omni-channel messenger platform that was built from 2017 to connect ecommerce stores to customers via web chat, Facebook Messenger, WhatsApp, and other channels.
3) The founder discusses how they started with an MVP in 2017 with 200 ecommerce stores in Hong Kong and Taiwan, and have since expanded to over 5000 clients across Southeast Asia using AWS for scaling.
Learn how you can use AWS to adapt to a changing interconnected market, and take advantage of global responsiveness and minimal barriers to innovation. AWS can help you create value for the business in addition to saving costs on infrastructure. Gain insights from lessons learned and recommendations on how to accelerate the path to business value.
Containers are an increasingly important way for developers to package and deploy their applications. AWS offers multiple container products to help you deploy, manage, and scale containers in production: Amazon Elastic Container Service (ECS) is a fully-managed container orchestration service; Amazon ECS for Kubernetes (EKS) is a managed service that makes it easy for you to run Kubernetes on AWS; Amazon Elastic Container Registry (ECR) is a fully-managed Docker container registry; and AWS Fargate is a technology for deploying and managing containers without having to manage the underlying infrastructure.
At AWS, security is job zero. AWS has worked with global enterprises to meet their respective security requirements and has developed a broad portfolio of services to help customers run highly secure workloads in the cloud. This session will describe how Amazon has been managing security of the cloud at hyper-scale and adding new capabilities that help secure customer applications and data such as Inspector, GuardDuty, and Macie. Leave this session with a better understanding of how these services operate and how easy it is to integrate them into your secure cloud environment.
Presenter: Kurt Gray, Global Account Solutions Architect, AWS
How to Enable Single Sign On to Multiple AWS Accounts and Business Applicatio...Amazon Web Services
by Vijay Sharma, Senior Product Manager, AWS
Creating multiple AWS accounts helps manage AWS resources for different users, teams, and applications, but managing access for multiple AWS accounts can be difficult to scale. AWS Single Sign-On (SSO), a new cloud SSO service, makes it easy to sign in to multiple AWS accounts and business applications. You will learn how to use AWS SSO and AWS Directory Service to enable users to access their AWS accounts and business applications using their existing corporate credentials. You will also learn how to manage user permissions centrally to AWS resources when users access the AWS Management Console using AWS SSO.
As Public Sector development teams transition to cloud-based architectures and adopt more agile processes, the tools they need to support their development cycles will change. In this session, we'll take you through the transition that Amazon made to a service-oriented architecture over a decade ago. We will share the lessons we learned, the processes we adopted, and the tools we built to increase both our agility and reliability. We will also introduce you to the AWS Code family services which were born out of Amazon's internal DevOps experience and are utilised by many Public Sector customers globally.
Mario Vlachakis, Solutions Architect, AWS
Distinguishing the hype from reality can be a bit confusing, especially when you consider the attention that AI gets from the media and commentators. So, how can your organisation get started and put AI to work for you? That is the question I will answer in this talk. From greater customer intimacy, increasing competitive advantage and improving efficiency, I will discuss and show how AI can be used today and help the organisation in more impactful ways.
Essere conformi al GDPR, il regolamento generale sulla protezione dei dati personali entrato in vigore il 25 maggio 2018, può risultare complicato ma AWS ha gli strumenti per guidarti attraverso tutto il processo. In questa sessione approfondiremo i meccanismi di automazione che AWS offre ai propri clienti per aiutarli nell'implementazione dei propri programmi di sicurezza e privacy e vedremo quali sono gli strumenti specifici messi a disposizione da AWS per indirizzare alcuni requisiti del GDPR.
What IT Transformation Really Means for the EnterpriseTom Laszewski
The document discusses the challenges facing enterprises and how transformation is needed. It outlines both the disadvantages enterprises currently face, such as high customer expectations and constant change, as well as advantages they have like existing customer bases and resources. It then discusses how enterprises can transform by adopting new mechanisms, architectures, cultures and organizations that promote innovation, such as developing minimum viable products, using microservices architectures, and establishing small autonomous teams. New technologies like serverless computing and machine learning are also enabling this transformation. Overall, the document argues that enterprises of all kinds must transform to keep up with the changing environment.
Jonathan Allen outlines a 12-step approach to scaling talent transformation to the cloud. The key steps include: accepting the change, providing training and hands-on experience, creating small "two-pizza" cross-functional teams, bringing in experts, having teams build something real, scaling learning by splitting teams, pursuing certification, recognizing expertise, leading by example, and creating a unified job structure. The approach emphasizes organizational change management and building cloud skills at scale through a structured knowledge progression.
Security & Compliance are very important for most businesses. Learn how AWS enables you to securely use the cloud for you most vital business applications and how you can ensure that you are compliant with a large set of security standards and government regulations like GDPR.
Security, Risk and Compliance of Your Cloud Journey - Tel Aviv Summit 2018Amazon Web Services
How can you ensure your environment is Secure? How can you implement an effective governance model in your organization? The AWS Cloud Adoption Framework (CAF) and its Security Perspective provide a structured approach to make risk based decisions, build security guardrails and meet your compliance goals as you migrate to AWS. The Security perspective of the CAF provides a set of 5 core themes designed to help you structure your selection and implementation of controls that are right for your business: IAM, Detective Controls, Infrastructure Security, Data Protection and Incident response. In this session you will learn what it takes to lead a Secure Cloud Journey for your organization and make key strategic decisions.
Mastering the Secret Sauce to SaaS - Adrian De Luca - AWS TechShift ANZ 2018Amazon Web Services
Gartner predicts APAC cloud services spend will be $15.8B by 2020. With the SaaS segment growing at an average of 24% year on year, your customers are increasingly expecting to consume software as a service. In this session you will hear how SaaS delivery accelerates customer adoption, helping you go global, use the AWS SaaS Reference Architecture to implement best practices and leverage AWS programs to help you achieve success on your journey.
How Nubank Automates Fine-Grained Security with IAM, AWS Lambda, and CI/CD (F...Amazon Web Services
Cloud-native and with security integrated early in the software development process, Nubank is the largest digital bank in the world outside of Asia. Demand for higher levels of service and value, constantly evolving technology capabilities, and stringent regulatory requirements are all powerful forces reshaping retail banking. In this session, Nubank CTO Edward Wible discusses how the company mixes engineering culture, security philosophy and structure, automation, and integration with AWS security services. Learn how to leverage the day-to-day software development workflow for extensive security and maximum engineering throughput while minimizing the operational pain of running a large infrastructure.
Starting your Cloud Transformation Journey - Tel Aviv Summit 2018Boaz Ziniman
Understand the values your organization can get from the cloud is the first step in your cloud transformation journey.
We will share best practices for getting started with Cloud Computing and not only from the technical perspective (culture change and gains, building teams, business case, project selection and more). Join us for this session and Let's Start your Cloud journey.
This document summarizes an AWS seminar presentation on AI and machine learning services. It discusses AWS's mission to put machine learning in the hands of every developer and data scientist. It provides an overview of AWS machine learning application services like Amazon Rekognition, Polly, Lex, and Translate. It also covers AWS machine learning platform services like Amazon SageMaker and deep learning frameworks. Finally, it discusses AWS machine learning infrastructure services like EC2 P3 instances, the Deep Learning AMI, and AWS DeepLens.
This document discusses big data and machine learning. It begins by defining big data using the 5 V's: volume, velocity, variety, veracity, and value. It then discusses challenges organizations face with big data, including which tools to use and determining what data they have. The remainder discusses how to gain business value from data through architectures like data lakes, analytics, and machine learning services on AWS. It provides an example of how Netflix evolved its data pipeline and emphasizes agility. Finally, it discusses how machine learning relies on big data and new tools are needed for data scientists.
Building a Data Lake in Amazon S3 & Amazon Glacier (STG401-R1) - AWS re:Inven...Amazon Web Services
The document discusses building a data lake using Amazon S3 and Amazon Glacier for storage. It covers topics like what is big data, what is a data lake, achievable business outcomes from a data lake, securing the data lake, and examples of what can be done with analytics services on AWS. The presentation provides examples of using services like Amazon Comprehend, Amazon Transcribe, Kinesis, Athena and QuickSight for natural language processing, audio analysis, real-time streaming and visualization.
Social Media Analytics with Amazon QuickSight (ANT370) - AWS re:Invent 2018Amazon Web Services
Realizing the value of social media analytics can bolster your business goals. This type of analysis has grown in recent years due to the large amount of available information and the speed at which it can be collected and analyzed. In this workshop, we build a serverless data processing and machine learning (ML) pipeline that provides a multi-lingual social media dashboard of tweets within Amazon QuickSight. We leverage API-driven ML services, AWS Glue, Amazon Athena and Amazon QuickSight. These building blocks are put together with very little code by leveraging serverless offerings within AWS.
In this workshop, learn how to create a cloud-based business intelligence platform and deliver dynamic insights through a custom Alexa Skill. Together, we architect a data analytics platform using Amazon S3, Amazon Athena, Amazon QuickSight, Amazon DynamoDB, Amazon CloudWatch on the backend, and a voice-based user interface through a private Alexa Skill deployed via Alexa for Business on the front end.
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.
Big Data on AWS - To infinity and beyond! - Tel Aviv Summit 2018Amazon Web Services
A data lake is an architectural approach that allows you to store massive amounts of data into a central location, so it's readily available to be categorized, processed, analyzed and consumed by diverse groups within an organization.
In this session, we will introduce the Data Lake concept and its implementation on AWS.
We will explain the different roles our services play and how they fit into the Data Lake picture.
Modern Cloud Data Warehousing ft. Equinox Fitness Clubs: Optimize Analytics P...Amazon Web Services
Most companies are overrun with data, yet they lack critical insights to make timely and accurate business decisions. They are missing the opportunity to combine large amounts of new, unstructured big data that resides outside their data warehouse with trusted, structured data inside their data warehouse. In this session, we discuss the most common use cases with Amazon Redshift, and we take an in-depth look at how modern data warehousing blends and analyzes all your data to give you deeper insights to run your business. Equinox Fitness Clubs joins us to share their journey from static reports, redundant data, and inefficient data intergration to a modern and flexible data lake and data warehouse architecture that delivers dynamic reports based on trusted data.
This document discusses implementing a data lake on AWS to securely store, categorize, and analyze all types of data in a centralized repository. It describes key attributes of a data lake like decoupled storage and compute, rapid ingestion and transformation, and schema on read. It then outlines various AWS services that can be used to build a data lake like S3, Athena, EMR, Redshift, Glue, and Kinesis. It provides examples of streaming IoT data into a data lake and running queries and analytics on the data.
Automate Business Insights on AWS - Simple, Fast, and Secure Analytics PlatformsAmazon Web Services
Business analysts require easy access to data from across different parts of the business. In this session, learn why more customers have adopted Amazon Redshift than any other cloud-native Data Warehouse, and how they are building a broader analytics capability with data lakes on AWS.
Understand how AWS built machine learning (ML) into the services, taking away many of the time-intensive tasks of building an analytics platform. We cover why these customers choose Amazon Redshift for the accessibility to analysts, business reporting, deep security, ability to scale from GB to PB, and integration with the broader platform.
Learn about these customers who are increasingly opening insights to data analysts for data discovery and data scientists for machine learning. We also share how the AWS services such as AWS Glue and the coming ML-enabled AWS Lake Formation take away most of the heavy lifting,
The first step towards knowing your customer is to collect and extract insights and actionable information from your data. Learn how AWS enables you to cost efficiently store any amount of data and build an agile approach to data mining and visualization - helping you to make efficient business decisions and targeted offerings.
How TrueCar Gains Actionable Insights with Splunk Cloud PPTAmazon Web Services
The vast amount of big data that today’s companies generate makes it difficult to separate the signal from the noise. Organizations need to derive meaningful insights into operations and business to take action. TrueCar needed a better way to manage, search, and analyze their hybrid environment. In this webinar, you’ll learn how TrueCar centralized all of their data in one place using Amazon Kinesis and Splunk Cloud, gaining deep visibility, scalability, and the ability to monitor and troubleshoot operational issues – all while migrating to AWS.
Build Data Lakes & Analytics on AWS: Patterns & Best Practices - BDA305 - Ana...Amazon Web Services
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 ML services work together to build a successful data lake for various roles, including data scientists and business users.
The document discusses cloud data lakes and why AWS is the best solution for them. It notes that data is a strategic asset but current approaches to storing and analyzing data are too siloed, expensive, and limiting. Cloud data lakes on AWS provide a single, scalable, cost-effective data store where organizations can securely store all their data in standard formats and then analyze it in various ways using AWS's comprehensive suite of analytics services. AWS is described as the most comprehensive, secure, easy to build, and cost-effective solution for data lakes and analytics due to these services and capabilities.
Over 90% of today’s data was generated in the last 2 years, and the rate of data growth isn’t slowing down. In this session, we’ll step through the challenges and best practices on how to capture all the data that is being generated, understand what data you have, and start driving insights and even predict the future using purpose built AWS Services. We’ll frame the session and demonstrations around common pitfalls of building Data Lakes and how to successful drive analytics and insights from the data. This session will focus on the architecture patterns bringing together key AWS Services and rather than a deep dive on any single service. We’ll show how services such as Amazon S3, Amazon Glue, AWS Glue, Amazon Redshift, Amazon Athena, Amazon EMR, and Amazon Kinesis, and Amazon Machine Learning services are put together to build a successful data lake for various role including both data scientists and business users.
AWS 2019 Taipei Summit - Building Serverless Analytics Platform on AWSSteven Hsieh
This document discusses building serverless analytics solutions on AWS. It describes how serverless analytics can provide on-demand analytics on data lakes with no infrastructure to manage. Key services mentioned include Amazon S3 for storage, AWS Glue for ETL and data cataloging, Amazon Athena for interactive queries, and Amazon QuickSight for visualization. The document provides examples of using these services together for automated reporting, query monitoring with workgroups, and embedding dashboards in applications.
Build Your Own Log Analytics Solutions on AWS (ANT323-R) - AWS re:Invent 2018Amazon Web Services
With Amazon Elasticsearch Service's simplicity comes a multitude of opportunity to use it as a back end for real-time application and infrastructure monitoring. With this wealth of opportunities comes sprawl - developers in your organization are deploying Amazon Elasticsearch Service for many different workloads and many different purposes. Should you centralize into one Amazon Elasticsearch Service domain? What are the tradeoffs in scale and cost? How do you control access to the data and dashboards? How do you structure your indexes - single tenant or multi-tenant? In this session, we'll explore whether, when, and how to centralize logging across your organization to minimize cost and maximize value and learn how Autodesk has built a unified log analytics solution using Amazon Elasticsearch Service.
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.
Similar to Big Data Meets AI - Driving Insights and Adding Intelligence to Your Solutions (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.
This document discusses pitch decks and fundraising materials. It explains that venture capitalists will typically spend only 3 minutes and 44 seconds reviewing a pitch deck. Therefore, the deck needs to tell a compelling story to grab their attention. It also provides tips on tailoring different types of decks for different purposes, such as creating a concise 1-2 page teaser, a presentation deck for pitching in-person, and a more detailed read-only or fundraising deck. The document stresses the importance of including key information like the problem, solution, product, traction, market size, plans, team, and ask.
This document discusses building serverless web applications using AWS services like API Gateway, Lambda, DynamoDB, S3 and Amplify. It provides an overview of each service and how they can work together to create a scalable, secure and cost-effective serverless application stack without having to manage servers or infrastructure. Key services covered include API Gateway for hosting APIs, Lambda for backend logic, DynamoDB for database needs, S3 for static content, and Amplify for frontend hosting and continuous deployment.
This document provides tips for fundraising from startup founders Roland Yau and Sze Lok Chan. It discusses generating competition to create urgency for investors, fundraising in parallel rather than sequentially, having a clear fundraising narrative focused on what you do and why it's compelling, and prioritizing relationships with people over firms. It also notes how the pandemic has changed fundraising, with examples of deals done virtually during this time. The tips emphasize being fully prepared before fundraising and cultivating connections with investors in advance.
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...Amazon Web Services
This document discusses Amazon's machine learning services for building conversational interfaces and extracting insights from unstructured text and audio. It describes Amazon Lex for creating chatbots, Amazon Comprehend for natural language processing tasks like entity extraction and sentiment analysis, and how they can be used together for applications like intelligent call centers and content analysis. Pre-trained APIs simplify adding machine learning to apps without requiring ML expertise.
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.
Durante i laboratori pratici, gli esperti AWS ti mostrano quali strumenti aiutano a sviluppare le applicazioni Serverless in locale e nel cloud AWS e ti aiuteranno a programmare i prossimi passi per iniziare ad utilizzare questa tecnologia nella tua azienda.
10. Catalog & Search
Access and search metadata
Access & User Interface
Give your users easy and secure access
DynamoDB Elasticsearch API Gateway Identity & Access
Management
Cognito
QuickSight Amazon AI EMR Redshift
Athena Kinesis RDS
Central Storage
Secure, cost-effective
Storage in Amazon S3
S3
Snowball Database Migration
Service
Kinesis Firehose Direct Connect
Data Ingestion
Get your data into S3
Quickly and securely
Protect and Secure
Use entitlements to ensure data is secure and users’ identities are verified
Processing & Analytics
Use of predictive and prescriptive
analytics to gain better understanding
Security Token
Service
CloudWatch CloudTrail Key Management
Service
Data Lake Components
Catalog & Search
Access and search metadata
Access & User Interface
Give your users easy and secure access
DynamoDB Elasticsearch API Gateway Identity & Access
Management
Cognito
QuickSight
Central Storage
Secure, cost-effective
Storage in Amazon S3
Metadata User Access
Security/Governance
Data Movement Analytics and Machine Learning
11. Catalog & Search
Access and search metadata
Access & User Interface
Give your users easy and secure access
DynamoDB Elasticsearch API Gateway Identity & Access
Management
Cognito
QuickSight Amazon AI EMR Redshift
Athena Kinesis RDS
Central Storage
Secure, cost-effective
Storage in Amazon S3
S3
Snowball Database Migration
Service
Kinesis Firehose Direct Connect
Data Ingestion
Get your data into S3
Quickly and securely
Protect and Secure
Use entitlements to ensure data is secure and users’ identities are verified
Processing & Analytics
Use of predictive and prescriptive
analytics to gain better understanding
Security Token
Service
CloudWatch CloudTrail Key Management
Service
Data Lake Components
Catalog & Search
Access and search metadata
Access & User Interface
Give your users easy and secure access
DynamoDB Elasticsearch API Gateway Identity & Access
Management
Cognito
QuickSight A
Central Storage
Secure, cost-effective
Storage in Amazon S3
Glue ETL
35. Machine Learning requires new tools and interfaces
Machine Learning/Deep Learning
Business
Reporting
Data Scientists
Data Engineer
IDE
Data
Catalog
Central
Storage
Sagemaker
We are at a big data and BI Summit, so I think most folks are familiar with Big Data, and some form of Vs. 3Vs, 5Vs, 7Vs – which represent some definition of a big data system.
You don’t have to take my word for it… reports on the growth of data are readily available most everywhere you look.
Top-Left – growth of unstructured data is vastly outpacing structured data
Top-Right – the amount of data will grow 50x between 2010 and 2020
Bottom-Left – We already have PB/day customers. We’re trending towards EB and ZB data sets
Bottom-Right – Data from sensors/connected-devices and social media are now described in multiples of the global population
Organizations that successfully generate business value from their data, will outperform their peers. An Aberdeen survey saw organizations who implemented a Data Lake outperforming similar companies by 9% in organic revenue growth. These leaders were able to do new types of analytics like machine learning over new sources like log files, data from click-streams, social media, and internet connected devices stored in the Data Lake. This helped them to identify, and act upon opportunities for business growth faster by attracting and retaining customers, boosting productivity, proactively maintaining devices, and making informed decisions.
Lock, Michael (Aberdeen), Angling for Insight In Today’s Data Lake (Oct 2017), pg 7.
Amazon S3 provides object storage built to store and retrieve any amount of data.
S3 has unmatched durability, and availability, built from the ground up to deliver a customer promise of 99.999999999% of durability at Exabyte scale. Only S3 automatically replicates your data in three availability zones within a single region, giving you unmatched resilience to single data center issues like power failures. Only S3 lets you do cross region replication seamlessly without having to use a separate storage class. Finally, only S3 allows you to do cross region replication where you choose any number of specified regions to replicate to.
Amazon S3 has the best security, compliance, and audit capabilities of any storage service. It can automatically encrypt your data, and gives you three choices for key management through S3 Key Management, customer-provided keys, and with AWS Key Management Service (KMS). Only S3 gives you encryption when replicating data across regions, and lets you use separate accounts for the source and destination regions, protecting against malicious insider deletion of data. Only S3 has integration to an AI-powered security service to monitor, detect, and alert anomalies that might indicate early stages of an attack with Amazon Macie. To meet compliance regulations, you can log, and audit all account activity including how, when, and who is accessing objects in S3 through AWS CloudTrail. These features allow AWS to support security standards and compliance certifications for virtually every regulatory agency around the globe.
Amazon S3 is the only storage service that lets you operate at the object level, rather than the bucket level. This allows you to set fine-grain access controls, and security policies to restrict access to specific objects, and create lifecycle policies to automatically delete or tier groups of objects into lower-cost storage.
Amazon S3 is the only storage system that has the ability to retrieve only the subsets of data within an object that is needed with S3 Select, speeding up queries up to 400 percent, resulting in faster queries at lower costs.
AWS provides the most ways to bring data into your data lake than anywhere else. These include importing real-time, streaming data with Amazon Kinesis, establishing a dedicated network connection between your premises and AWS with AWS Direct Connect, using secure appliances to transfer large amounts of data with AWS Snowball, using a ruggedized shipping container to transfer data at Exabyte-scale with AWS Snowmobile, and migrating your databases with AWS Database Migration Service.
The Amazon S3 ecosystem has twice as many partner integrations than anyone else, with tens of thousands of consulting, systems integrator and independent software vendor partners. This means that it is easier to use S3 as primary storage, backup, archive, and disaster recovery with applications that you already own like from NetApp, EMC, Vertias, and others.
Once you have started to build your data lake, AWS provides the broadest, and diverse set of options to analyze, and extract value from your data whether it be for analytics, machine learning, or IoT use cases. You are given the tools and frameworks of your choice, with the broadest set of purpose-built services available that all run directly on the data lake, without the need to move data into a separate analytics system.
Many customers spend time and effort in analysis to find the perfect tool for their needs.
At the rate the ecosystem is evolving, that tool might no longer be the best if you’ve spent so much time in research.
Now that I know what data I have…
In the old world, you knew your schema, you got a BI tool, and you asked it questions based on the structure.
You knew exactly which questions you wanted to ask, which drove a very predictable collection and storage model
When think about data in the context of the 3 V’s, you need different tooling… and you’re going to want ask questions of data that isn’t structured.
In the new world of data analysis your questions are going to evolve and change over time.
You need to be able to collect, store and analyze data without being constrained by resources, whether compute, storage, or even the tool being used.
You want a purpose-built tool to derive the type of analysis – the type of insight – that you’re looking for.
With the rise of Big Data, the ecosystem is quite active, and the tools are rapidly changing…
You need the ability to evolve with the tools and your own needs.
Many customers spend time and effort in analysis to find the perfect tool for their needs.
At the rate the ecosystem is evolving, that tool might no longer be the best if you’ve spent so much time in research.
Our recommendation: Find a tool that meets the need, then iterate in the tooling as you learn more about your actual needs.
In order to do that, you need to have a good metadata management process, portable data formats, and easy access to the data.
Otherwise, your data is in jail.
Many customers tell us about the pain they experience when their data is locked behind a vendor-specific format for vendor-controlled interface.
Problem #1 – Many organizations don’t know what they have.
When you accumulate such a diversity of data, you need mechanisms to understand what data you have, where it is located, and what format.
This is metadata management. And if not managed properly (or at all), the data is essentially lost. It is taking up space, but you have no means to put it to use.
A common issue, regardless of whether it is on-prem or in the cloud, is the lack of a metadata management approach from the onset.
The Financial Industry Regulatory Authority (FINRA) oversees more than 3,900 securities firms with approximately 640,000 brokers.
FINRA processes approximately 6 terabytes of data and 37 billion records on an average day to build a complete, holistic picture of market trading in the U.S. On busy days, the stock markets can generate 75 billion+ records.
The way they’re able to make all this data useful, whether to data scientists or business users or others, is through a metadata system they developed and open sourced, called HERD.
This is the same platform that is used by LinkedIn, for example.
But most organizations don’t actually go off and built their own tooling.
Ivy Tech is a community college - 60,000 online and in-person course sections, 8,300 on staff, 170,000 students, and130 locations.
Ivy Tech uses metadata capabilities provided by AWS to manage their information.
These are the main components of Glue.
Glue comprises of a data catalog which is a central metadata repository, an ETL engine that can auto-generate Python code, and a flexible scheduler that handles dependency resolution, job monitoring and retries. Together, these automate much of the heavy lifting involved with discovering, categorizing, cleaning, enriching, and moving data, so you can spend more time analyzing your data.
Glue automatically discovers your data, determines the schema, and builds your data catalog. The Glue data catalog provides out-of-box integration with Amazon Athena, Amazon EMR, and Amazon Redshift Spectrum.
The ETL code Glue generates is just Python code that is entirely customizable, reusable, and portable. You can edit this code using your favorite IDE or notebook and share it with others using GitHub.
And finally, Glue is serverless. There are no resources to manage and you only pay for the resources your jobs consume while they run.
Glue includes a feature called the AWS Glue crawlers. These crawlers allow you to discover your metadata for the catalog automatically. These can operate over obth your relational databases and data warehouses, but also your data lakes on S3. when crawling sources such as S3, it will first identify the format of the data, for example, is the dataset CSV, JSON, Parquet, Avro, etc, and then it will determine fields and type of each field within the data.
It really does a great job, but you can also go in and modify the outputs. It can also identify both hive compliant as well as non-compliant partitioning of data.
<21-28 to be screenshot heavy>
OK – I’m jazzed… I know the pitfalls. Now… What do I do?
Netflix data pipeline
~500 billion events and ~1.3 PB per day
~8 million events and ~24 GB per second during peak demand
There are several hundred event streams flowing through the pipeline. For example:
Video viewing activities
UI activities
Error logs
Performance events
Troubleshooting & diagnostic events
We see netflix started with a batch analytics. Collecting their data using apache Chukwa and saving it in an S3 backed data lake.
After they built this, they needed to start doing real-time analytics on the data. They easily pushed the new version out branching off and creating a Kafka based backend.
To improve the reliability, and scale, they shifted from the Chukwa front-end pushing to Kafka to having Kafka publishing and routing specific messages to the consumer kafka topics.
They shifted and built the log analytics on Kinesis Data Streams.
built on Amazon Kinesis enables us to identify ways to increase efficiency, reduce costs, and improve resiliency for the best customer experience
Zillow Group increases machine-learning calculation performance and
scalability and delivers near-real-time home-valuation data to customers
using AWS. The company houses a portfolio of the largest online real-estate
and home-related brands. Zillow Group runs the Zestimate, its machine
learning–based home-valuation tool, on Amazon Kinesis and Apache Spark
on Amazon EMR.
Zillow uses Kinesis Streams to collect public record data and MLS listings, and then update home value estimates in near real-time so home buyers and sellers can get the most up to date home value estimates. Zillow also sends the same data to its S3 data lake using Kinesis Firehose, so that all the applications can work with the most recent information. Using structured data, unstructured data like image, etc.
DigitalGlobe went all in on AWS to meet the growing demand for commercial geo-intelligence, migrating its entire 17-year imagery archive to the cloud. DigitalGlobe is one of the world’s leading providers of high-resolution earth imagery, data, and analysis. The company used AWS Snowmobile to move 100 petabytes of data to the cloud, allowing it to move away from large file-transfer protocols and delivery workflows. DigitalGlobe also uses Amazon SageMaker to handle machine learning at scale. Dr. Walter Scott, CTO and founder at DigitalGlobe, spoke at re:Invent 2017.
Cache rate improved by more than a factor of 2. Went up to 83% sometimes trending to 90%
Stripe uses Athena
Amazon.com uses DyanmoDB and a suite of other servlerless services in Herd.
rocessing delays decrease from 1 second to 100 milliseconds;
Herd controls the business logic for processing all Amazon.com customer orders worldwide, orchestrating more than 1,300 workflows for everything from order processing to fulfillment-center operations to coordinating parts of the Amazon Alexa backend. A mission-critical system used by more than 300 Amazon engineering teams, Herd executes more than 4 billion workflows on peak days.
Requests from Alexa, the Amazon.com sites, and the Amazon fulfillment centers totaled 3.34 trillion, peaking at 12.9 million per second. According to the team, the extreme scale, consistent performance, and high availability of DynamoDB let them meet needs of Prime Day without breaking a sweat.
DynamoDB is used by Lyft to store GPS locations for all their rides, Tinder to store millions of user profiles and make billions of matches, Redfin to scale to millions of users and manage data for hundreds of millions of properties, Comcast to power their XFINITY X1 video service running on more than 20 million devices, BMW to run its car-as-a-sensor service that can scale up and down by two orders of magnitude within 24 hours, Nordstrom for their recommendations engine reducing processing time from 20 minutes to a few seconds, Under Armour to support its connected fitness community of 200 million users, Toyota Racing to make real time decisions on pit-stops, tire changes, and race strategy, and another 100,000+ AWS customers for a wide variety of high-scale, high-performance use cases.
You simply put your Data in S3 and submit SQL against it
Why is AI/ML often talked about side by side with Data conferences.
Data really fuels AI/ML. AI/ML is all about finding patterns in the data and using that patterns to make predictions, recognitions images,create speech and provide other intelligent capabilities.
This in turn creates a flywheel effect where these new intelligent capabilities in tern increases user base and customer usage which create more data that allows organizations to better under their users drive analytics and new intelligent systems.
“By using Amazon SageMaker, DigitalGlobe cache rate improved by more than a factor of two, often times being around 83% and sometimes trending to 90% cache hit. This allowed them to also cut their cloud storage cost in half by better utilizing their S3 Optimized cache and retrieving less from their 100+ PB Archive.”
Purpose: showcase the power of ML to identify data utility
The blue dots represent what humans decided to cache (almost the whole world) and the orange dots represent what our customers requested access to over a three month period. We were missing the mark by a long shot.
http://blog.digitalglobe.com/industry/using-machine-learning-to-save-money-on-cloud-data-storage/
Digital Globe: 2 different use cases –
As the world’s leading provider of high-resolution Earth imagery, data and analysis, DigitalGlobe works with enormous amounts of data every day.
Use Case 1:
As more and more imagery is collected from their growing constellation of satellites it is critical for DG to predict and cache only the most relevant imagery at any given point in time, allowing them to take advantage of AWS’ tiered storage products to optimize their costs. They are relying on machine learning as the business grows. By analyzing 17 years of changing access patterns to this imagery data, they can predict how long to keep the data readily available in Amazon S3 before moving it to cold archive in Amazon Glacier, by example. With Amazon SageMaker’s machine learning algorithms, they can identify and predict exactly what imagery is going to be used and requested in real-time, to drive down the cost of managing petabytes of data at-scale – and the engineers that are using SageMaker to do this knew nothing about Machine Learning when they started!
Use Case 2:
DigitalGlobe is making it easier for people to find, access, and run compute against their entire data archive in the cloud in order to apply deep learning to satellite imagery. They plan to use Amazon SageMaker to train models against petabytes of earth observation imagery datasets using hosted Jupyter notebooks, so DigitalGlobe's Geospatial Big Data Platform (GBDX) users can just push a button, create a model, and deploy it all within one scalable distributed environment at scale.