AWS IoT services provide a managed cloud platform that lets connected devices interact with cloud applications and other devices easily and securely. In this session, we will discuss how constrained devices can leverage AWS IoT Core to send data to the cloud and receive commands back to the device using the protocol of their choice. AWS Greengrass is software that lets you run local compute, messaging and data caching for connected devices in a secure way. AWS IoT Device Management is a service that makes it easy to securely onboard, organize, monitor, and remotely manage IoT devices at scale. With AWS IoT Analytics, you can run sophisticated analytics on massive volumes of IoT data without having to worry about the cost and complexity typically required to build your own IoT analytics platform.
IoT Building Blocks: From Edge Devices to Analytics in the Cloud - SRV204 - A...Amazon Web Services
In this session, we explore features and functions of AWS IoT services. First we will cover AWS IoT fundamentals, review best practices for IoT solutions, and look at some common architectural patterns. Then we will dive deep into AWS IoT Analytics. We will explain how AWS IoT Analytics runs sophisticated analytics on massive volumes of IoT data and helps operationalize analyses without requiring you to build an IoT analytics platform from the ground up. You will hear from TensorIoT, an AWS IoT Analytics partner, about how they are using AWS IoT Analytics. Leave this session with an understanding of how to start building IoT applications with AWS IoT.
IoT Building Blocks: From Edge Devices to Analytics in the Cloud - SRV204 - A...Amazon Web Services
In this session, we explore the features and functions of AWS IoT services. We first cover AWS IoT fundamentals and our AWS Partner Network (APN) ecosystem. Then we discuss AWS IoT services in greater detail, review best practices for IoT solutions, and examine common architectural patterns. With this foundation in place, we explore a use case for IoT applications. You gain an understanding of how to start building IoT applications with AWS IoT.
How To Deliver a 5-Star Experience for IoT-Enabled ServicesAppDynamics
The document discusses delivering a 5-star experience for IoT-enabled services. It provides an overview of IoT, breaks down the components of an IoT service, and discusses the challenges of understanding issues that impact customer experience when multiple third parties are involved. It argues that application intelligence solutions are needed to gain end-to-end visibility across business transactions, infrastructure, applications, databases and third parties to quickly identify and resolve issues affecting customer experience.
This session covers the most recent AWS IoT announcements at re:Invent. Learn about trends and use cases for the Internet of Things (IoT). Hear about how AWS customers are using AWS IoT to connect their devices to the cloud and solve business challenges with IoT.
The document discusses Amazon Web Services (AWS) Internet of Things (IoT) architecture and services. It describes AWS IoT Core for securely connecting devices, routing data, and enabling offline device interactions. It also discusses AWS Greengrass for local device intelligence and actions, and AWS IoT Device Management for onboarding, managing, and updating fleets of devices at scale. The document promotes AWS IoT as providing secure connectivity, device management and security capabilities through services like AWS IoT Device Defender, as well as tools for generating insights and value from IoT data.
The document discusses Amazon Web Services (AWS) Internet of Things (IoT) solutions for connecting, managing and gaining insights from IoT devices. It provides an overview of the AWS IoT platform and services, including AWS IoT Core for device connectivity, AWS IoT Device Management for device onboarding and updates, AWS IoT Device Defender for security, and using AWS services like analytics for extracting value from device data.
How to use AWS IoT Analytics to unlock the value from IoT dataAmazon Web Services
Level: Intermediate
If you could solve real-world problems with IoT data, what would you tackle first?
To answer this question, we'll show you how to use AWS IoT Analytics to analyse massive volumes of IoT data without having to worry about the cost and complexity of building your own IoT analytics platform. The solution makes it easy to run analytics and derive insights from IoT data that will help you make better, more accurate decisions on IoT applications and machine learning use cases, for example, predictive maintenance.
Who Should Attend: Developers, Coders, Engineers, System Administrators, IT Managers, Solutions Architects and Product Heads.
Customer Showcase for AWS IoT Analytics (IOT219) - AWS re:Invent 2018Amazon Web Services
The document discusses AWS IoT Analytics, a service that processes, enriches, stores, analyzes, and visualizes IoT data. It provides an overview of the key components of AWS IoT Analytics including channels to ingest data from multiple sources, pipelines to filter, transform and enrich data, data stores to store raw and processed data, data sets to query the data stores using SQL, and Jupyter notebooks and containers to build and run machine learning models on the data. It also provides examples of how customers in energy/oil and gas, consumer products, and manufacturing are using AWS IoT Analytics for applications like predictive maintenance, anomaly detection, device telemetry analysis, and quality control.
IoT Building Blocks: From Edge Devices to Analytics in the Cloud - SRV204 - A...Amazon Web Services
In this session, we explore features and functions of AWS IoT services. First we will cover AWS IoT fundamentals, review best practices for IoT solutions, and look at some common architectural patterns. Then we will dive deep into AWS IoT Analytics. We will explain how AWS IoT Analytics runs sophisticated analytics on massive volumes of IoT data and helps operationalize analyses without requiring you to build an IoT analytics platform from the ground up. You will hear from TensorIoT, an AWS IoT Analytics partner, about how they are using AWS IoT Analytics. Leave this session with an understanding of how to start building IoT applications with AWS IoT.
IoT Building Blocks: From Edge Devices to Analytics in the Cloud - SRV204 - A...Amazon Web Services
In this session, we explore the features and functions of AWS IoT services. We first cover AWS IoT fundamentals and our AWS Partner Network (APN) ecosystem. Then we discuss AWS IoT services in greater detail, review best practices for IoT solutions, and examine common architectural patterns. With this foundation in place, we explore a use case for IoT applications. You gain an understanding of how to start building IoT applications with AWS IoT.
How To Deliver a 5-Star Experience for IoT-Enabled ServicesAppDynamics
The document discusses delivering a 5-star experience for IoT-enabled services. It provides an overview of IoT, breaks down the components of an IoT service, and discusses the challenges of understanding issues that impact customer experience when multiple third parties are involved. It argues that application intelligence solutions are needed to gain end-to-end visibility across business transactions, infrastructure, applications, databases and third parties to quickly identify and resolve issues affecting customer experience.
This session covers the most recent AWS IoT announcements at re:Invent. Learn about trends and use cases for the Internet of Things (IoT). Hear about how AWS customers are using AWS IoT to connect their devices to the cloud and solve business challenges with IoT.
The document discusses Amazon Web Services (AWS) Internet of Things (IoT) architecture and services. It describes AWS IoT Core for securely connecting devices, routing data, and enabling offline device interactions. It also discusses AWS Greengrass for local device intelligence and actions, and AWS IoT Device Management for onboarding, managing, and updating fleets of devices at scale. The document promotes AWS IoT as providing secure connectivity, device management and security capabilities through services like AWS IoT Device Defender, as well as tools for generating insights and value from IoT data.
The document discusses Amazon Web Services (AWS) Internet of Things (IoT) solutions for connecting, managing and gaining insights from IoT devices. It provides an overview of the AWS IoT platform and services, including AWS IoT Core for device connectivity, AWS IoT Device Management for device onboarding and updates, AWS IoT Device Defender for security, and using AWS services like analytics for extracting value from device data.
How to use AWS IoT Analytics to unlock the value from IoT dataAmazon Web Services
Level: Intermediate
If you could solve real-world problems with IoT data, what would you tackle first?
To answer this question, we'll show you how to use AWS IoT Analytics to analyse massive volumes of IoT data without having to worry about the cost and complexity of building your own IoT analytics platform. The solution makes it easy to run analytics and derive insights from IoT data that will help you make better, more accurate decisions on IoT applications and machine learning use cases, for example, predictive maintenance.
Who Should Attend: Developers, Coders, Engineers, System Administrators, IT Managers, Solutions Architects and Product Heads.
Customer Showcase for AWS IoT Analytics (IOT219) - AWS re:Invent 2018Amazon Web Services
The document discusses AWS IoT Analytics, a service that processes, enriches, stores, analyzes, and visualizes IoT data. It provides an overview of the key components of AWS IoT Analytics including channels to ingest data from multiple sources, pipelines to filter, transform and enrich data, data stores to store raw and processed data, data sets to query the data stores using SQL, and Jupyter notebooks and containers to build and run machine learning models on the data. It also provides examples of how customers in energy/oil and gas, consumer products, and manufacturing are using AWS IoT Analytics for applications like predictive maintenance, anomaly detection, device telemetry analysis, and quality control.
In this workshop, you learn about the different components of AWS IoT Analytics. You have the opportunity to configure AWS IoT Analytics to ingest data from AWS IoT Core, enrich the data using AWS Lambda, visualize the data using Amazon QuickSight, and perform machine learning using Jupyter Notebooks. Join us, and build a solution that helps you perform analytics on appliance energy usage in a smart building and forecast energy utilization to optimize consumption.
본 실습은 AWS IoT Edge 구성 요소인 AWS IoT Greengrass를 이용하여 산업 현장에서 활용되는 표준 통신 프로토콜(OPC-UA)을 AWS IoT 호환 프로토콜로 변환 전처리하는 과정을 실습합니다. 이렇게 수집된 데이터는 AWS IoT Analytics 을 통해 분석 및 BI에 활용될 수 있으며, 본 실습에서는 Amazon Sage Maker를 활용하여 예지 정비 모델을 작성 및 배포하고, 추가적으로 Amazon QuickSight를 통한 시각화 구현을 목표로 합니다.
Understand the State of Your Connected Devices (IOT367) - AWS re:Invent 2018Amazon Web Services
In this session, we discuss the different ways to understand the state of your operations, how to use AWS IoT services, and how to take appropriate action using AWS IoT services, like the AWS IoT Rules Engine, to improve operational efficiency.
AWS IoT Events is a new IoT-managed service that allows enterprises with large operations dependent on IoT devices to continuously monitor data from their equipment, applications, and fleets of devices for changes in operation and trigger the appropriate response when events occur. IoT Events monitors inputs from many IoT sensors and applications simultaneously; it can also combine sensor and application data with analytical results, including machine learning from AWS IoT Analytics. It helps customers reduce costs through efficiency gains, minimize downtime, and improve product quality. IoT Events is applicable to several industries, including device manufacturers, manufacturing plants, power and utilities, shipping, oil and gas, etc. Join us for this session to learn more about the customer benefits of IoT Events, and catch a demo of IoT Events in action.
AWS Simple Workflow: Distributed Out of the Box! - Morning@LohikaSerhiy Batyuk
The document provides an overview of AWS Simple Workflow (SWF) presented by Serhiy Batyuk. Some key points:
- SWF is a fully managed AWS service for coordinating work across distributed application components through the use of workflows and activities.
- It allows building scalable applications by coordinating work across components through asynchronous calls using workflows and tasks.
- The presentation demonstrates how to build a sample application in Java using the SWF APIs and SDK to coordinate preparation tasks for attending a conference.
- Key concepts covered include workflows, activities, deciders, retries, scalability, and replay of workflow executions for reliability.
The document promotes the CTIA Enterprise & Applications event happening in San Diego, focusing on business mobility solutions. Attendees will learn about new mobile solutions, explore industries and services on the exhibit floor, and connect with over 10,000 wireless and IT professionals over three days. Thought leadership stages and specialized zones on the exhibit floor will allow focused learning and networking in key areas of enterprise apps, cloud, M2M, transportation, healthcare and security.
The document describes Lastline's breach detection platform which integrates with existing security systems through APIs. It uses full-system emulation to detect evasive threats in real-time across networks, applications, and operating systems. Analysis results are presented through a web-based portal to prioritize incident response and block breach attempts.
This document describes an intelligent, unified platform for managing applications and infrastructure across multiple clouds, containers, and on-premise environments. The platform provides complete visibility from the end user experience to infrastructure, and is powered by machine learning for anomaly detection, clustering, prediction, and correlation. It offers a suite of services including discovery and monitoring, configuration and compliance, automation and orchestration, and analytics and planning. The platform is designed to provide greater agility, increased efficiency, and fewer outages for managing applications and infrastructure at scale.
Enterprise IT Uncertainty Around Big Data Initiatives in 2015SnapLogic
Recent data from SnapLogic and TechValidate suggests IT leaders are excited about big data’s ability to power sharper analytics and other modern applications, but struggle with limited skills and resources. For this survey, SnapLogic and TechValidate queried more than 100 IT leaders from large enterprises nationwide between December 15 and December 31, 2014.
While the survey shows there’s a lot of indecision right now when it comes to big data plans and technologies, SnapLogic customers tell us that the ability to easily connect with other systems is essential to the success of their big data initiatives.
You can also learn how the SnapLogic Elastic Integration Platform can help with big data integration by going to www.SnapLogic.com/big-data.
TIBCO Big Data Platform - Andreas GerstSlawomir Zak
The document discusses TIBCO's software platform. It focuses on understanding big data, anticipating patterns and trends in real-time, and acting on opportunities or threats. The platform includes capabilities for real-time event processing, customer loyalty models, analytics and more. All information in the document is considered confidential and proprietary to TIBCO Software.
Internet of Things e Machine Learning: i principali casi d'usoAmazon Web Services
In questa sessione, approfondiremo i principali casi d'uso di organizzazioni e aziende che hanno reso l'Internet of Things e il Machine Learning elementi centrali delle proprie attività e processi quotidiani. Vedremo come queste aziende hanno ottenuto un maggior livello di efficienza operativa e produttività, analizzando ciascun caso d'uso in termini di: sfide aziendali, metriche per il successo, ritorno dell'investimento (ROI), risorse e competenze.
SRV304 IoT Building Blocks From Edge Devices to Analytics in the Cloud Amazon Web Services
AWS IoT is a set of fully managed services spanning the edge to the cloud that enables you to sense and act locally on devices, store data and manage devices in the cloud, and perform sophisticated analytics to derive useful insights. In this session, we explore features and functions of AWS IoT services. First, we cover AWS IoT fundamentals and our partner ecosystem. Next, we discuss AWS IoT services in greater detail, review best practices for IoT solutions, and look at some common architectural patterns. With this foundation in place, we explore a use case for IoT in industrial applications. You leave this session with an understanding of how to start building IoT applications with AWS IoT.
The data that your business collects is constantly growing, making it increasingly difficult for traditional systems to keep up with resource demands. Understanding your big data can help you serve your customers better, improve product quality, and grow your revenue, but you need a platform that can handle the strain.
In hands-on tests in our datacenter, the Scalable Modular Server DX2000 from NEC processed big data quickly and scaled nearly linearly as we added server nodes. In our k-means data cluster analysis test, a DX2000 solution running Apache Spark and Red Hat Enterprise Linux OpenStack Platform processed 100GB in approximately 2 minutes. We also saw that as we doubled the number of server nodes, the DX2000 solution cut analysis time in half when processing the same amount of data, producing excellent scalability.
The Scalable Modular Server DX2000 by NEC is a good choice when you’re ready to put big data to work for you.
The document discusses security challenges in cloud virtualization. It outlines an agenda covering new challenges and Oracle answers, security responsibilities, identity as the new center of cyber defense, maximizing intelligence-driven automation, and a quick peek into the security operations center. The document emphasizes that users have become the new perimeter and that identity provides security intelligence to prevent, detect, predict, and respond to threats. It also discusses how machine learning and a unified data platform can power automated preventative and corrective actions.
IoT Building Blocks_ From Edge Devices to Analytics in the Cloud Amazon Web Services
In this session, we explore features and functions of AWS IoT services. We first cover AWS IoT fundamentals and our partner ecosystem. Then we discuss AWS IoT services in greater detail, review best practices for IoT solutions, and look at some common architectural patterns. With this foundation in place, we explore a use case for IoT applications. Leave this session with an understanding of how to start building IoT applications with AWS IoT.
This document discusses the integration of smart technologies and big data analytics in future healthcare. It outlines several key trends and technologies that will drive disruption in healthcare, including precision medicine, quantifiable self-tracking, adoption of smart devices, wearable technologies, robotic healthcare, cognitive computing, neurosynaptic chips, and use of big data and collaboration. The document argues that these technologies will enable a paradigm shift toward preventative healthcare focused on population health rather than symptomatic treatment of individuals.
This document discusses the integration of smart technologies and big data analytics in future healthcare. It outlines several key trends that will drive disruption in healthcare, including precision medicine, quantifiable self-tracking, increased adoption of smart devices, wearable technologies, robotic healthcare assistants, cognitive computing, and the use of big data and neurosynaptic chips to advance medical research and treatment. The document argues that these disruptive technologies will help transform healthcare from treating sickness to keeping populations healthy through personalized prevention and care.
NLP in a Bank: Automated Document Reading: Yevgen Kolesnyk / Patrik Zatko / D...Vienna Data Science Group
Despite the fast pace of digitalization happening in the modern world, core processes in the banking area are still based on printed documents to a large extent. Document processing, therefore, consumes a significant amount of manpower and processing time, as well as an increasing operating risk level of the bank by being prone to human errors. In this session, you will learn how automated document processing can create a great opportunity to modernize and simplify the way modern banks work, reduce associated operation risk level, as well as reduce time and costs spent within a given process area.
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.
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In this workshop, you learn about the different components of AWS IoT Analytics. You have the opportunity to configure AWS IoT Analytics to ingest data from AWS IoT Core, enrich the data using AWS Lambda, visualize the data using Amazon QuickSight, and perform machine learning using Jupyter Notebooks. Join us, and build a solution that helps you perform analytics on appliance energy usage in a smart building and forecast energy utilization to optimize consumption.
본 실습은 AWS IoT Edge 구성 요소인 AWS IoT Greengrass를 이용하여 산업 현장에서 활용되는 표준 통신 프로토콜(OPC-UA)을 AWS IoT 호환 프로토콜로 변환 전처리하는 과정을 실습합니다. 이렇게 수집된 데이터는 AWS IoT Analytics 을 통해 분석 및 BI에 활용될 수 있으며, 본 실습에서는 Amazon Sage Maker를 활용하여 예지 정비 모델을 작성 및 배포하고, 추가적으로 Amazon QuickSight를 통한 시각화 구현을 목표로 합니다.
Understand the State of Your Connected Devices (IOT367) - AWS re:Invent 2018Amazon Web Services
In this session, we discuss the different ways to understand the state of your operations, how to use AWS IoT services, and how to take appropriate action using AWS IoT services, like the AWS IoT Rules Engine, to improve operational efficiency.
AWS IoT Events is a new IoT-managed service that allows enterprises with large operations dependent on IoT devices to continuously monitor data from their equipment, applications, and fleets of devices for changes in operation and trigger the appropriate response when events occur. IoT Events monitors inputs from many IoT sensors and applications simultaneously; it can also combine sensor and application data with analytical results, including machine learning from AWS IoT Analytics. It helps customers reduce costs through efficiency gains, minimize downtime, and improve product quality. IoT Events is applicable to several industries, including device manufacturers, manufacturing plants, power and utilities, shipping, oil and gas, etc. Join us for this session to learn more about the customer benefits of IoT Events, and catch a demo of IoT Events in action.
AWS Simple Workflow: Distributed Out of the Box! - Morning@LohikaSerhiy Batyuk
The document provides an overview of AWS Simple Workflow (SWF) presented by Serhiy Batyuk. Some key points:
- SWF is a fully managed AWS service for coordinating work across distributed application components through the use of workflows and activities.
- It allows building scalable applications by coordinating work across components through asynchronous calls using workflows and tasks.
- The presentation demonstrates how to build a sample application in Java using the SWF APIs and SDK to coordinate preparation tasks for attending a conference.
- Key concepts covered include workflows, activities, deciders, retries, scalability, and replay of workflow executions for reliability.
The document promotes the CTIA Enterprise & Applications event happening in San Diego, focusing on business mobility solutions. Attendees will learn about new mobile solutions, explore industries and services on the exhibit floor, and connect with over 10,000 wireless and IT professionals over three days. Thought leadership stages and specialized zones on the exhibit floor will allow focused learning and networking in key areas of enterprise apps, cloud, M2M, transportation, healthcare and security.
The document describes Lastline's breach detection platform which integrates with existing security systems through APIs. It uses full-system emulation to detect evasive threats in real-time across networks, applications, and operating systems. Analysis results are presented through a web-based portal to prioritize incident response and block breach attempts.
This document describes an intelligent, unified platform for managing applications and infrastructure across multiple clouds, containers, and on-premise environments. The platform provides complete visibility from the end user experience to infrastructure, and is powered by machine learning for anomaly detection, clustering, prediction, and correlation. It offers a suite of services including discovery and monitoring, configuration and compliance, automation and orchestration, and analytics and planning. The platform is designed to provide greater agility, increased efficiency, and fewer outages for managing applications and infrastructure at scale.
Enterprise IT Uncertainty Around Big Data Initiatives in 2015SnapLogic
Recent data from SnapLogic and TechValidate suggests IT leaders are excited about big data’s ability to power sharper analytics and other modern applications, but struggle with limited skills and resources. For this survey, SnapLogic and TechValidate queried more than 100 IT leaders from large enterprises nationwide between December 15 and December 31, 2014.
While the survey shows there’s a lot of indecision right now when it comes to big data plans and technologies, SnapLogic customers tell us that the ability to easily connect with other systems is essential to the success of their big data initiatives.
You can also learn how the SnapLogic Elastic Integration Platform can help with big data integration by going to www.SnapLogic.com/big-data.
TIBCO Big Data Platform - Andreas GerstSlawomir Zak
The document discusses TIBCO's software platform. It focuses on understanding big data, anticipating patterns and trends in real-time, and acting on opportunities or threats. The platform includes capabilities for real-time event processing, customer loyalty models, analytics and more. All information in the document is considered confidential and proprietary to TIBCO Software.
Internet of Things e Machine Learning: i principali casi d'usoAmazon Web Services
In questa sessione, approfondiremo i principali casi d'uso di organizzazioni e aziende che hanno reso l'Internet of Things e il Machine Learning elementi centrali delle proprie attività e processi quotidiani. Vedremo come queste aziende hanno ottenuto un maggior livello di efficienza operativa e produttività, analizzando ciascun caso d'uso in termini di: sfide aziendali, metriche per il successo, ritorno dell'investimento (ROI), risorse e competenze.
SRV304 IoT Building Blocks From Edge Devices to Analytics in the Cloud Amazon Web Services
AWS IoT is a set of fully managed services spanning the edge to the cloud that enables you to sense and act locally on devices, store data and manage devices in the cloud, and perform sophisticated analytics to derive useful insights. In this session, we explore features and functions of AWS IoT services. First, we cover AWS IoT fundamentals and our partner ecosystem. Next, we discuss AWS IoT services in greater detail, review best practices for IoT solutions, and look at some common architectural patterns. With this foundation in place, we explore a use case for IoT in industrial applications. You leave this session with an understanding of how to start building IoT applications with AWS IoT.
The data that your business collects is constantly growing, making it increasingly difficult for traditional systems to keep up with resource demands. Understanding your big data can help you serve your customers better, improve product quality, and grow your revenue, but you need a platform that can handle the strain.
In hands-on tests in our datacenter, the Scalable Modular Server DX2000 from NEC processed big data quickly and scaled nearly linearly as we added server nodes. In our k-means data cluster analysis test, a DX2000 solution running Apache Spark and Red Hat Enterprise Linux OpenStack Platform processed 100GB in approximately 2 minutes. We also saw that as we doubled the number of server nodes, the DX2000 solution cut analysis time in half when processing the same amount of data, producing excellent scalability.
The Scalable Modular Server DX2000 by NEC is a good choice when you’re ready to put big data to work for you.
The document discusses security challenges in cloud virtualization. It outlines an agenda covering new challenges and Oracle answers, security responsibilities, identity as the new center of cyber defense, maximizing intelligence-driven automation, and a quick peek into the security operations center. The document emphasizes that users have become the new perimeter and that identity provides security intelligence to prevent, detect, predict, and respond to threats. It also discusses how machine learning and a unified data platform can power automated preventative and corrective actions.
IoT Building Blocks_ From Edge Devices to Analytics in the Cloud Amazon Web Services
In this session, we explore features and functions of AWS IoT services. We first cover AWS IoT fundamentals and our partner ecosystem. Then we discuss AWS IoT services in greater detail, review best practices for IoT solutions, and look at some common architectural patterns. With this foundation in place, we explore a use case for IoT applications. Leave this session with an understanding of how to start building IoT applications with AWS IoT.
This document discusses the integration of smart technologies and big data analytics in future healthcare. It outlines several key trends and technologies that will drive disruption in healthcare, including precision medicine, quantifiable self-tracking, adoption of smart devices, wearable technologies, robotic healthcare, cognitive computing, neurosynaptic chips, and use of big data and collaboration. The document argues that these technologies will enable a paradigm shift toward preventative healthcare focused on population health rather than symptomatic treatment of individuals.
This document discusses the integration of smart technologies and big data analytics in future healthcare. It outlines several key trends that will drive disruption in healthcare, including precision medicine, quantifiable self-tracking, increased adoption of smart devices, wearable technologies, robotic healthcare assistants, cognitive computing, and the use of big data and neurosynaptic chips to advance medical research and treatment. The document argues that these disruptive technologies will help transform healthcare from treating sickness to keeping populations healthy through personalized prevention and care.
NLP in a Bank: Automated Document Reading: Yevgen Kolesnyk / Patrik Zatko / D...Vienna Data Science Group
Despite the fast pace of digitalization happening in the modern world, core processes in the banking area are still based on printed documents to a large extent. Document processing, therefore, consumes a significant amount of manpower and processing time, as well as an increasing operating risk level of the bank by being prone to human errors. In this session, you will learn how automated document processing can create a great opportunity to modernize and simplify the way modern banks work, reduce associated operation risk level, as well as reduce time and costs spent within a given process area.
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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.
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.
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.
21. Easily analyze IoT data
AWS IoT Analytics
Channels DatasetsPipelines Data stores Jupyter notebooks
& templates
AWS IoT Analytics is a service that processes, enriches, stores, analyzes,
and visualizes IoT data for manufacturers and enterprises.
22. AWS IoT Architecture
Secure device
connectivity
and messaging
Endpoints
Fleet onboarding,
management, and
SW updates
Fleet
audit and
protection
IoT data
analytics and
intelligence
Things
Sense & Act
Cloud
Storage & Compute
Secure local
triggers, actions,
and data sync
AWS IoT Core
Gateway
AWS Greengrass
AWS IoT Device
Management
AWS IoT Device
Defender
Intelligence
Insights & Logic → Action
a:FreeRTOS
a:FreeRTOS
AWS IoT
Analytics
23. Sense & Act
Things
Secure device
connectivity
and messaging
AWS IoT Core
Fleet onboarding,
management, and
SW updates
Fleet
audit and
protection
IoT data
analytics and
intelligence
AWS IoT Device
Management
AWS IoT Device
Defender
GatewayEndpoints
AWS Greengrass
AWS IoT 1-Click
AWS IoT
Analytics
Amazon
FreeRTOS
Storage & Compute & Learn
Cloud
Secure local
triggers, actions,
and data sync
Intelligence
Insights & Logic → Action
AWS IoT Services Suite
24. Easily Trigger Actions in the Cloud
AWS IoT 1-Click
AWS IoT 1-Click makes it easy for simple devices to
trigger actions such as Lambda functions with one click
Acquire device Configure & deploy Extract reports
31. Problem
Nokia saw a need in industrial IoT to analyze
video streams at the edge and send the data
to remote centers only when anomalies are
detected.
Solution
Deploying AWS Greengrass on Nokia Multi-
access Edge Computing platform and
combining it with Nokia private mobile
network solutions. This joint solution makes
it possible for the oil industry to pair real-
time drilling data with production data
of nearby wells.
Impact
Due to the high cost of bandwidth being, this
solution enables Nokia to optimize the data
that is sent to other wells and to the cloud
based on rules and alerts set up on
the locally processed data.
32. Problem
Valmet produces complex equipment with
multiple dependent processes running in parallel.
Valmet customers need visibility into the state of
these processes to control quality and avoid
downtime.
Solution
Valmet is building a new digital twin capability to
allow paper mill operators to view equipment
and process data during production runs. AWS
IoT Analytics is at the core of this solution
training ML models for paper quality forecasting
and scheduling metrics generation for digital
twin view-generation.
Impact
AWS IoT Analytics allows Valmet to combine
historical models of equipment performance
with live data from current operations to glean
insights that help them learn how to make their
paper better and stronger.
33. Problem
Wärtsilä needed to accurately predict when the
marine engines they manufactured needed to
get serviced. Understanding and predicting the
service schedule is vital for Wärtsilä to increase
their service and parts revenue.
Solution
Accenture worked with AWS account SAs, AoD
SAs, and Salesforce SAs to architect an IoT
solution using Salesforce and AWS IoT Core to
collect data and build predictive models. The
solution they developed is scalable and
extensible beyond just this use case, as Wärtsilä
has 14,000 ships with 35,000 engines installed.
There are great possibilities for sensor-driven IoT
use cases.
Impact
The entire solution should result in an increase
in parts and service sales for Wärtsilä and higher
customer retention.
34. Problem
With the launch of the new X8 architecture,
the first of his kind to be connected, Kemppi
was looking at a platform that could provide
development agility and cost reduction
Solution
Kemppi chose AWS not least because of
maturity of the services such as AWS
Lambda. Adopting AWS IoT reduced the
requirement on the devices and provides a
reliable communication channel to the rest
of the platform, even from remote places
such as oil rigs.
Impact
Adopting AWS, Kemppi reduced the product
release cycle from one year to six months,
and at the same time reduced the planned
downtime. AWS IoT and other managed
services allows them to spend less time on
managing infrastructure, reducing the cost of
deliveries.
35. Problem
Rio Tinto has connectivity challenges at some
of the mine locations where large, expensive
machinery is in play. Rio was looking for a
way to still leverage the cloud to predict and
prevent equipment failures, wear and tear,
and learn about potential hazards in their
surrounding environment.
Solution
Rio is using AWS Greengrass to run locally
and collect data from its fleet of large
hauling trucks. The data is collected from
sensors on haul trucks and stored for on-site
analysis to calculate road roughness.
An online heat map of the rough roads helps
maintenance crews repair roads and reduce
premature damage of their machinery.
Impact
Greengrass allows for real-time alerts and
machine-to-machine communication even
when not connected to the cloud. Operating
locally has helped Rio manage its fleet of
trucks saving millions of dollars.