This document discusses using AWS services for industrial IoT and smart manufacturing applications. It provides examples of companies like Fender, Valmet and Volkswagen Group using AWS IoT, machine learning and analytics services to improve operational efficiency, enable predictive maintenance and quality, and gain insights from industrial equipment data. Edge computing solutions with AWS Greengrass are discussed as well for handling data from remote locations with unreliable internet connectivity.
This document discusses the importance of digital business and defines key terms. It explains that a digital business incorporates digital technology to create revenue and results through innovative strategies, products, processes and experiences. It also discusses how technology and business have evolved, with technology now creating new opportunities that change businesses. It outlines several key technology trends and how they present opportunities for new players but also threats. The document discusses the changing roles of various corporate leaders in a digital business environment and some of the challenges they face. It provides a value tree for a digital business that shows how investments in new digital capabilities can drive growth and efficiency through various value levers.
Future of Data and AI in Retail - NRF 2023Rob Saker
This document summarizes Rob Saker's predictions for retail data and AI in 2023. It predicts that retailers will focus on last mile optimization using real-time data and AI to consolidate orders and routing. It also predicts the use of generative AI for personalized product recommendations and images. Composable customer data platforms that integrate best of breed solutions are also predicted to see greater adoption. The document further predicts that peer-to-peer secure data sharing and localized large language models focused on specific industries will emerge.
Supply Chain Optimization with Apache KafkaKai Wähner
Supply Chain optimization leveraging Event Streaming with Apache Kafka. See real-world use cases and architectures from Walmart, BMW, Porsche, and other enterprises to improve the Supply Chain Management (SCM) processes. Automation, robustness, flexibility, real-time, decoupling, data integration, and hybrid deployments...
Video recording: https://youtu.be/dUkgungBmPs
Blog post: https://www.kai-waehner.de/apache-kafka-supply-chain-management-scm-optimization-scor-six-sigma-real-time
Next IIoT wave: embedded digital twin for manufacturing IRS srl
Next IIoT wave will be a population of digital twin. A digital twin is a real-time digital replica of a physical device. Developing an embedded digital twin allows superior device diagnostic and failure anticipation. Discover how to to implement an embedded digital twin using real-time monitoring, physical models, and machine learning
AI, or artificial intelligence, is powering a massive shift in how engineers, scientists, and programmers develop and improve products and services. 85% of executives expect to gain or strengthen their competitive advantage through the use of AI, but is AI really poised to transform your research, products, or business?
Learn how AI system can be designed to perceive its environment, make decisions, and take action. Get an overview of AI for engineers, and discover the ways in which it fits into an engineering workflow. You will also learn how MATLAB and Simulink® are giving engineers and scientists AI capabilities that were once available only to highly-specialized software developers and Data Scientists.
AI and content strategy - Elle Geraghty Content Strategy.pdfElle Geraghty
This document appears to be a presentation on content strategy and artificial intelligence. It includes:
- An introduction and biography of Elle Geraghty, the content strategist giving the presentation.
- Overviews of key topics like what content strategy and AI are, how they impact work, and potential issues with AI like bias, lack of oversight, and privacy concerns.
- Deeper dives into specific AI technologies like natural language processing, chatbots, sentiment analysis, and generative adversarial networks.
- Examples of how AI could be used in an ideal workflow to generate and optimize different types of content outputs.
Accenture migrated its analytics platform from an on-premise system to Google Cloud's Platform-as-a-Service model to address challenges around scalability, costs, and maintenance. This involved modernizing Accenture's data architecture and migrating over 400 terabytes of data and 50+ applications. The transition unlocked new analytics capabilities, increased cost savings through Google Cloud's pay-as-you-go model, and improved performance. Accenture also focused on developing its employees' cloud skills to support the new platform and drive business value from data insights.
Capability models have a long history. They came out of business schools in the 50ies. In recent years the enterprise- and business architecture communities seem to have taken over, making capabilities more an IT rather than a business modeling concept. Most capability models we've seen fail to achieve their original purpose: to enable business people to design better enterprises - ones that are fit for purpose, efficient, adaptive to change and satisfy customers.
In this webinar, Wolfgang Goebl explains the typical flaws of capability models and design patterns for next-generation capability modeling. You will learn:
practical patterns to create capability maps that foster a seamless business & IT co-design
why most capability modeling efforts fail and how to overcome the usual problems
how to connect other elements of the architecture with capabilities - how to run a broad elicitation process with all relevant stakeholders
how to use capability maps in corporate management
This document discusses the importance of digital business and defines key terms. It explains that a digital business incorporates digital technology to create revenue and results through innovative strategies, products, processes and experiences. It also discusses how technology and business have evolved, with technology now creating new opportunities that change businesses. It outlines several key technology trends and how they present opportunities for new players but also threats. The document discusses the changing roles of various corporate leaders in a digital business environment and some of the challenges they face. It provides a value tree for a digital business that shows how investments in new digital capabilities can drive growth and efficiency through various value levers.
Future of Data and AI in Retail - NRF 2023Rob Saker
This document summarizes Rob Saker's predictions for retail data and AI in 2023. It predicts that retailers will focus on last mile optimization using real-time data and AI to consolidate orders and routing. It also predicts the use of generative AI for personalized product recommendations and images. Composable customer data platforms that integrate best of breed solutions are also predicted to see greater adoption. The document further predicts that peer-to-peer secure data sharing and localized large language models focused on specific industries will emerge.
Supply Chain Optimization with Apache KafkaKai Wähner
Supply Chain optimization leveraging Event Streaming with Apache Kafka. See real-world use cases and architectures from Walmart, BMW, Porsche, and other enterprises to improve the Supply Chain Management (SCM) processes. Automation, robustness, flexibility, real-time, decoupling, data integration, and hybrid deployments...
Video recording: https://youtu.be/dUkgungBmPs
Blog post: https://www.kai-waehner.de/apache-kafka-supply-chain-management-scm-optimization-scor-six-sigma-real-time
Next IIoT wave: embedded digital twin for manufacturing IRS srl
Next IIoT wave will be a population of digital twin. A digital twin is a real-time digital replica of a physical device. Developing an embedded digital twin allows superior device diagnostic and failure anticipation. Discover how to to implement an embedded digital twin using real-time monitoring, physical models, and machine learning
AI, or artificial intelligence, is powering a massive shift in how engineers, scientists, and programmers develop and improve products and services. 85% of executives expect to gain or strengthen their competitive advantage through the use of AI, but is AI really poised to transform your research, products, or business?
Learn how AI system can be designed to perceive its environment, make decisions, and take action. Get an overview of AI for engineers, and discover the ways in which it fits into an engineering workflow. You will also learn how MATLAB and Simulink® are giving engineers and scientists AI capabilities that were once available only to highly-specialized software developers and Data Scientists.
AI and content strategy - Elle Geraghty Content Strategy.pdfElle Geraghty
This document appears to be a presentation on content strategy and artificial intelligence. It includes:
- An introduction and biography of Elle Geraghty, the content strategist giving the presentation.
- Overviews of key topics like what content strategy and AI are, how they impact work, and potential issues with AI like bias, lack of oversight, and privacy concerns.
- Deeper dives into specific AI technologies like natural language processing, chatbots, sentiment analysis, and generative adversarial networks.
- Examples of how AI could be used in an ideal workflow to generate and optimize different types of content outputs.
Accenture migrated its analytics platform from an on-premise system to Google Cloud's Platform-as-a-Service model to address challenges around scalability, costs, and maintenance. This involved modernizing Accenture's data architecture and migrating over 400 terabytes of data and 50+ applications. The transition unlocked new analytics capabilities, increased cost savings through Google Cloud's pay-as-you-go model, and improved performance. Accenture also focused on developing its employees' cloud skills to support the new platform and drive business value from data insights.
Capability models have a long history. They came out of business schools in the 50ies. In recent years the enterprise- and business architecture communities seem to have taken over, making capabilities more an IT rather than a business modeling concept. Most capability models we've seen fail to achieve their original purpose: to enable business people to design better enterprises - ones that are fit for purpose, efficient, adaptive to change and satisfy customers.
In this webinar, Wolfgang Goebl explains the typical flaws of capability models and design patterns for next-generation capability modeling. You will learn:
practical patterns to create capability maps that foster a seamless business & IT co-design
why most capability modeling efforts fail and how to overcome the usual problems
how to connect other elements of the architecture with capabilities - how to run a broad elicitation process with all relevant stakeholders
how to use capability maps in corporate management
The document discusses Siemens Digital Industries Software, which provides industrial software and automation solutions. It notes that Siemens is the #1 provider of industrial software and automation in the world. It highlights the company's focus on digital transformation and creating comprehensive digital twins to optimize performance for customers across industries like manufacturing, electronics, and energy. The document also outlines Siemens' strategy to transition software offerings to cloud-based SaaS models and build out its Xcelerator integrated development platform.
This document discusses the digital transformation of high-tech industries. It notes that profit and market value are migrating away from hardware and components towards internet platforms. It identifies trends like artificial intelligence, internet of things, cloud computing and edge processing driving changes. Few product companies have fully transformed, with internet platform companies outpacing spending on research and development. The document outlines a framework for companies to transform their core business while growing new business models in areas like connected products, living products and services, and ecosystem platforms. It emphasizes the need for digital talent and factories to drive transformation.
This document discusses Accenture's methodology for migrating enterprise data platforms to the cloud at scale. It involves establishing a transformation office, standing up the target cloud data platform, migrating data and code in waves with change management, updating skills and operating models, implementing new governance, and decommissioning legacy systems. The key steps are developing a business case and migration strategy through discovery, planning the technology architecture and migration approach, and executing the migration while validating data and code through proofs of concept and migration waves.
This document provides an architectural overview of Microsoft Dynamics AX and recommendations for sizing and configuring various components. It describes the data, application, and presentation layers of Dynamics AX. It also includes guidelines for sizing the database, Application Object Server, Enterprise Portal Server, and terminal servers. The document recommends SQL Server settings and configurations to optimize performance as well as settings for the Dynamics AX application. It stresses the importance of maintenance plans for index fragmentation and statistics.
Industry 4.0 focuses on technologies like digital twins, 3D printing, big data, augmented reality, autonomous robots, artificial intelligence, and cloud computing. Industry 5.0 emphasizes collaborative partnerships between humans and smart systems, with each focusing on their strengths. It also aims for mass personalization of products and a bottom-up supply chain approach. The goal is a more human-centric and sustainable system that improves productivity while maintaining human roles. Industry 5.0 provides purpose and responsible application of Industry 4.0 technologies, not a revolution, with the true 5th industrial revolution involving biological technologies.
This document provides information on business composability including definitions, principles, and how organizations can transition from traditional to composable. It defines a composable business as one that is architected for real-time adaptability and resilience through a mindset of modularity. Key aspects include developing interchangeable business blocks, autonomous teams, and composable technologies and strategies to accelerate change. The document discusses expected changes in areas like strategy, customers, workforce, and operations to achieve a highly composable organization.
Industry X.0 - Realizing Digital Value in Industrial Sectorsaccenture
Industry X.0 is a new way for manufacturing to operate. At its heart are highly intelligent, interconnected products and ecosystems that create a fully digital value chain, supplemented by new core innovation competences and deep cultural change. Learn more: https://accntu.re/2wKLK4m
Azure Migration
Azure migration is the process of moving your workloads to the Azure cloud. This can include migrating your infrastructure, databases, and applications. Azure migration can help you improve your scalability, reliability, and security, while also reducing your costs. Csharptek is a trusted microsoft solution partner in Digital and Innovation (Azure)for Azure migration. We have a team of experienced and certified Azure professionals who can help you with every aspect of your migration. We offer a variety of services to meet your needs, and we're committed to helping you achieve your business goals.
GENERATIVE AI, THE FUTURE OF PRODUCTIVITYAndre Muscat
Discuss the impact and opportunity of using Generative AI to support your development and creative teams
* Explore business challenges in content creation
* Cost-per-unit of different types of content
* Use AI to reduce cost-per-unit
* New partnerships being formed that will have a material impact on the way we search and engage with content
Part 4 of a 9 Part Research Series named "What matters in AI" published on www.andremuscat.com
The document discusses cloud migration strategy and provides a framework for organizations to migrate their IT infrastructure and applications to the cloud. It begins with an introduction to cloud computing concepts. It then presents a cloud adoption model and discusses key considerations for cloud adoption strategies including business drivers, infrastructure, architecture, operations and governance. The framework provides a six step approach for cloud migration: 1) establishing a common understanding, 2) assessing current IT environment, 3) identifying competitive advantages, 4) understanding risks, 5) developing a migration plan, and 6) adopting a cloud model. The document also analyzes different cloud deployment and service models and provides tools to evaluate applications and risks for cloud migration.
Accenture Cloud Platform: Control, Manage and Govern the Enterprise Cloudaccenture
The Accenture Cloud Platform is a multi-cloud management platform that enables organizations to manage all of their enterprise cloud
resources—public and private—and automate and accelerate solution delivery.
Challenges in AI LLMs adoption in the EnterpriseGeorge Bara
The presentation "ITDays_2023_GeorgeBara" discusses challenges in adopting AI large language models (LLMs) in enterprise settings.
The presentation covers:
1. **Challenges in AI LLMs adoption**: It highlights the noise in the current AI landscape and questions the practical use of AI in real businesses.
2. **The DNA of an Enterprise**: Defines enterprise sizes and discusses the new solutions adoption process, emphasizing effective integration and minimizing disruption.
3. **Enterprise-Grade**: Lists qualities like robustness, reliability, scalability, performance, security, and support that are essential for enterprise-grade solutions.
4. **What are LLMs?**: Describes the pre-ChatGPT era with BERT, a model used for language understanding, and details its enterprise applications.
5. **LLM use-cases before ChatGPT**: Focuses on data triage, process automation, knowledge management, and the augmentation of business operations.
6. **EU Digital Decade Report**: Points out that AI adoption in Europe is slow and might not meet the 2030 targets.
7. **Adoption Challenges**: Addresses top challenges such as data security, predictability, performance, control, regulatory compliance, ethics, sustainability, and ROI.
8. **Conclusion**: Reflects on the slow adoption of AI in enterprises, suggesting that a surge might occur once the technology matures and is ready for enterprise use.
The presenter concludes by stating that despite the hype around technologies like ChatGPT, enterprises are cautious and will adopt new technologies at their own pace. He anticipates a gradual then sudden adoption pattern once LLMs are proven to be enterprise-ready.
AI Infra Day | The Generative AI Market And Intel AI Strategy and Product Up...Alluxio, Inc.
AI Infra Day
Oct. 25, 2023
Organized by Alluxio
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Jordan Plawner (Global Director of Artificial intelligence Product Management and Strategy, @Intel)
ChatGPT and other massive models represents an amazing step forward in AI, yet they do not solve real-world business problems. We will survey how the AI ecosystem has worked non-stop over this last year to take these all-purpose multi-task models and optimize them to they can be used by organizations to address domain specific problems. We will explain these new AI-for-the-real world techniques and methods such as fine tuning and how can be applied to deliver results which are highly performant with state-of-the-art accuracy while also being economical to build and deploy everywhere to enhance products and services.
Capgemini Cloud Assessment - A Pathway to Enterprise Cloud MigrationFloyd DCosta
Capgemini Cloud Assessment offers a methodology and a roadmap for Cloud migration to reduce decision risks, promote rapid user adoption and lower TCO of IT investments. It leverages pre-built accelerators such as ROI calculators, risk models and portfolio analyzers and provides three powerful deliverables in just six to eight weeks:
Data Marketplace and the Role of Data VirtualizationDenodo
Watch full webinar here: https://bit.ly/3IS9sQS
A data marketplace is like an online shopping interface specializing in data. Ideally, it should work just like an online store, with minimal latency and maximum responsiveness. However, this does not mean that all of the data in the data marketplace needs to be stored in the same central repository.
In this session, Shadab Hussain, Americas Sales Head, Data Analytics at Wipro, a partner company with Denodo and a co-sponsor of DataFest 2021, talks about the role of data virtualization in enabling full-featured data marketplaces. Such data marketplaces provide real-time, curated access to data, even when the data is stored across many different sources throughout the organization.
You will learn:
- The main features of a data marketplace
- Why organizations need data marketplaces
- Why data marketplaces sometimes fail
- How data virtualization enables the most effective data marketplaces
- How one of Europe’s premiere public healthcare system organizations leveraged a data marketplace to improve data consumption and ease of access
A Framework for Navigating Generative Artificial Intelligence for EnterpriseRocketSource
Generative AI offers both opportunities and risks for enterprises. While it could drive significant ROI through personalized experiences, thought leadership, and faster processes, there are also concerns about job losses, overreliance on automation without oversight, and inaccurate information. Effective adoption of generative AI requires experience management strategies like understanding emotional and logical customer triggers, aligning products and services to experience channels, and building a business model around a compelling brand story. A people-first approach is important to maximize benefits and mitigate risks.
The document is a research report about digital transformation in professional services firms. It provides an introduction and overview of key findings from a survey of 136 business executives and decision-makers at professional services firms. The report finds that 73% of professional services firms have low digital maturity, with most rating themselves a 1 or 2 on a 5-point digital maturity scale. It also finds that improving client experience and operational efficiency are the top goals of digital transformation initiatives. Only 12% of surveyed firms report having completed a digital transformation.
Necessity of the Digital Twin and Digital ThreadMarc Lind
As products move to include connectivity, sensors and intelligence many people are working on the infrastructure to support the data streaming back from the field. Big data clouds, data lakes and analytics initiatives have become the focus in many cases. Yet, without accurate context – Digital Twin – time series data generated during production and ongoing operation is difficult or even impossible to understand and analyze. In addition, the ability to interpret and act upon these data often require traceability to prior information from related revisions – Digital Thread. To complicate matters further as artificial intelligence / cognitive computing is introduced the necessity becomes even greater.
Using AWS IoT for Industrial Applications - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Understand how AWS IoT can be used for Industrial Applications including predictive quality, asset condition monitoring, and predictive maintenance
- Know how features of AWS IoT Core such as the rules engine, device shadow, and message broker are used for industrial applications
- Articulate how AWS IoT Analytics supports machine learning
The document discusses Siemens Digital Industries Software, which provides industrial software and automation solutions. It notes that Siemens is the #1 provider of industrial software and automation in the world. It highlights the company's focus on digital transformation and creating comprehensive digital twins to optimize performance for customers across industries like manufacturing, electronics, and energy. The document also outlines Siemens' strategy to transition software offerings to cloud-based SaaS models and build out its Xcelerator integrated development platform.
This document discusses the digital transformation of high-tech industries. It notes that profit and market value are migrating away from hardware and components towards internet platforms. It identifies trends like artificial intelligence, internet of things, cloud computing and edge processing driving changes. Few product companies have fully transformed, with internet platform companies outpacing spending on research and development. The document outlines a framework for companies to transform their core business while growing new business models in areas like connected products, living products and services, and ecosystem platforms. It emphasizes the need for digital talent and factories to drive transformation.
This document discusses Accenture's methodology for migrating enterprise data platforms to the cloud at scale. It involves establishing a transformation office, standing up the target cloud data platform, migrating data and code in waves with change management, updating skills and operating models, implementing new governance, and decommissioning legacy systems. The key steps are developing a business case and migration strategy through discovery, planning the technology architecture and migration approach, and executing the migration while validating data and code through proofs of concept and migration waves.
This document provides an architectural overview of Microsoft Dynamics AX and recommendations for sizing and configuring various components. It describes the data, application, and presentation layers of Dynamics AX. It also includes guidelines for sizing the database, Application Object Server, Enterprise Portal Server, and terminal servers. The document recommends SQL Server settings and configurations to optimize performance as well as settings for the Dynamics AX application. It stresses the importance of maintenance plans for index fragmentation and statistics.
Industry 4.0 focuses on technologies like digital twins, 3D printing, big data, augmented reality, autonomous robots, artificial intelligence, and cloud computing. Industry 5.0 emphasizes collaborative partnerships between humans and smart systems, with each focusing on their strengths. It also aims for mass personalization of products and a bottom-up supply chain approach. The goal is a more human-centric and sustainable system that improves productivity while maintaining human roles. Industry 5.0 provides purpose and responsible application of Industry 4.0 technologies, not a revolution, with the true 5th industrial revolution involving biological technologies.
This document provides information on business composability including definitions, principles, and how organizations can transition from traditional to composable. It defines a composable business as one that is architected for real-time adaptability and resilience through a mindset of modularity. Key aspects include developing interchangeable business blocks, autonomous teams, and composable technologies and strategies to accelerate change. The document discusses expected changes in areas like strategy, customers, workforce, and operations to achieve a highly composable organization.
Industry X.0 - Realizing Digital Value in Industrial Sectorsaccenture
Industry X.0 is a new way for manufacturing to operate. At its heart are highly intelligent, interconnected products and ecosystems that create a fully digital value chain, supplemented by new core innovation competences and deep cultural change. Learn more: https://accntu.re/2wKLK4m
Azure Migration
Azure migration is the process of moving your workloads to the Azure cloud. This can include migrating your infrastructure, databases, and applications. Azure migration can help you improve your scalability, reliability, and security, while also reducing your costs. Csharptek is a trusted microsoft solution partner in Digital and Innovation (Azure)for Azure migration. We have a team of experienced and certified Azure professionals who can help you with every aspect of your migration. We offer a variety of services to meet your needs, and we're committed to helping you achieve your business goals.
GENERATIVE AI, THE FUTURE OF PRODUCTIVITYAndre Muscat
Discuss the impact and opportunity of using Generative AI to support your development and creative teams
* Explore business challenges in content creation
* Cost-per-unit of different types of content
* Use AI to reduce cost-per-unit
* New partnerships being formed that will have a material impact on the way we search and engage with content
Part 4 of a 9 Part Research Series named "What matters in AI" published on www.andremuscat.com
The document discusses cloud migration strategy and provides a framework for organizations to migrate their IT infrastructure and applications to the cloud. It begins with an introduction to cloud computing concepts. It then presents a cloud adoption model and discusses key considerations for cloud adoption strategies including business drivers, infrastructure, architecture, operations and governance. The framework provides a six step approach for cloud migration: 1) establishing a common understanding, 2) assessing current IT environment, 3) identifying competitive advantages, 4) understanding risks, 5) developing a migration plan, and 6) adopting a cloud model. The document also analyzes different cloud deployment and service models and provides tools to evaluate applications and risks for cloud migration.
Accenture Cloud Platform: Control, Manage and Govern the Enterprise Cloudaccenture
The Accenture Cloud Platform is a multi-cloud management platform that enables organizations to manage all of their enterprise cloud
resources—public and private—and automate and accelerate solution delivery.
Challenges in AI LLMs adoption in the EnterpriseGeorge Bara
The presentation "ITDays_2023_GeorgeBara" discusses challenges in adopting AI large language models (LLMs) in enterprise settings.
The presentation covers:
1. **Challenges in AI LLMs adoption**: It highlights the noise in the current AI landscape and questions the practical use of AI in real businesses.
2. **The DNA of an Enterprise**: Defines enterprise sizes and discusses the new solutions adoption process, emphasizing effective integration and minimizing disruption.
3. **Enterprise-Grade**: Lists qualities like robustness, reliability, scalability, performance, security, and support that are essential for enterprise-grade solutions.
4. **What are LLMs?**: Describes the pre-ChatGPT era with BERT, a model used for language understanding, and details its enterprise applications.
5. **LLM use-cases before ChatGPT**: Focuses on data triage, process automation, knowledge management, and the augmentation of business operations.
6. **EU Digital Decade Report**: Points out that AI adoption in Europe is slow and might not meet the 2030 targets.
7. **Adoption Challenges**: Addresses top challenges such as data security, predictability, performance, control, regulatory compliance, ethics, sustainability, and ROI.
8. **Conclusion**: Reflects on the slow adoption of AI in enterprises, suggesting that a surge might occur once the technology matures and is ready for enterprise use.
The presenter concludes by stating that despite the hype around technologies like ChatGPT, enterprises are cautious and will adopt new technologies at their own pace. He anticipates a gradual then sudden adoption pattern once LLMs are proven to be enterprise-ready.
AI Infra Day | The Generative AI Market And Intel AI Strategy and Product Up...Alluxio, Inc.
AI Infra Day
Oct. 25, 2023
Organized by Alluxio
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Jordan Plawner (Global Director of Artificial intelligence Product Management and Strategy, @Intel)
ChatGPT and other massive models represents an amazing step forward in AI, yet they do not solve real-world business problems. We will survey how the AI ecosystem has worked non-stop over this last year to take these all-purpose multi-task models and optimize them to they can be used by organizations to address domain specific problems. We will explain these new AI-for-the-real world techniques and methods such as fine tuning and how can be applied to deliver results which are highly performant with state-of-the-art accuracy while also being economical to build and deploy everywhere to enhance products and services.
Capgemini Cloud Assessment - A Pathway to Enterprise Cloud MigrationFloyd DCosta
Capgemini Cloud Assessment offers a methodology and a roadmap for Cloud migration to reduce decision risks, promote rapid user adoption and lower TCO of IT investments. It leverages pre-built accelerators such as ROI calculators, risk models and portfolio analyzers and provides three powerful deliverables in just six to eight weeks:
Data Marketplace and the Role of Data VirtualizationDenodo
Watch full webinar here: https://bit.ly/3IS9sQS
A data marketplace is like an online shopping interface specializing in data. Ideally, it should work just like an online store, with minimal latency and maximum responsiveness. However, this does not mean that all of the data in the data marketplace needs to be stored in the same central repository.
In this session, Shadab Hussain, Americas Sales Head, Data Analytics at Wipro, a partner company with Denodo and a co-sponsor of DataFest 2021, talks about the role of data virtualization in enabling full-featured data marketplaces. Such data marketplaces provide real-time, curated access to data, even when the data is stored across many different sources throughout the organization.
You will learn:
- The main features of a data marketplace
- Why organizations need data marketplaces
- Why data marketplaces sometimes fail
- How data virtualization enables the most effective data marketplaces
- How one of Europe’s premiere public healthcare system organizations leveraged a data marketplace to improve data consumption and ease of access
A Framework for Navigating Generative Artificial Intelligence for EnterpriseRocketSource
Generative AI offers both opportunities and risks for enterprises. While it could drive significant ROI through personalized experiences, thought leadership, and faster processes, there are also concerns about job losses, overreliance on automation without oversight, and inaccurate information. Effective adoption of generative AI requires experience management strategies like understanding emotional and logical customer triggers, aligning products and services to experience channels, and building a business model around a compelling brand story. A people-first approach is important to maximize benefits and mitigate risks.
The document is a research report about digital transformation in professional services firms. It provides an introduction and overview of key findings from a survey of 136 business executives and decision-makers at professional services firms. The report finds that 73% of professional services firms have low digital maturity, with most rating themselves a 1 or 2 on a 5-point digital maturity scale. It also finds that improving client experience and operational efficiency are the top goals of digital transformation initiatives. Only 12% of surveyed firms report having completed a digital transformation.
Necessity of the Digital Twin and Digital ThreadMarc Lind
As products move to include connectivity, sensors and intelligence many people are working on the infrastructure to support the data streaming back from the field. Big data clouds, data lakes and analytics initiatives have become the focus in many cases. Yet, without accurate context – Digital Twin – time series data generated during production and ongoing operation is difficult or even impossible to understand and analyze. In addition, the ability to interpret and act upon these data often require traceability to prior information from related revisions – Digital Thread. To complicate matters further as artificial intelligence / cognitive computing is introduced the necessity becomes even greater.
Using AWS IoT for Industrial Applications - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Understand how AWS IoT can be used for Industrial Applications including predictive quality, asset condition monitoring, and predictive maintenance
- Know how features of AWS IoT Core such as the rules engine, device shadow, and message broker are used for industrial applications
- Articulate how AWS IoT Analytics supports machine learning
IoT World 2019 Keynote: A Story of Transformational IoT: Do machines actually...Amazon Web Services
This document discusses transforming businesses through internet of things (IoT) technology. It provides 4 insights from a customer's IoT success: 1) organizational buy-in is critical, 2) technology should be at the core, 3) operate at the edge with modern tools, and 4) data is key to enabling intelligence. It outlines AWS IoT services that can collect, analyze, and react to data from edge devices. Modern digital businesses are described as customer-obsessed, organized for value, having technology at their core, and making strategic use of data through a test-and-learn culture.
The document discusses how AWS IoT services can be used to build IoT applications. It begins by explaining how IoT data can transform industries by enabling new business models, services, and outcomes. It then provides examples of how IoT is used in various sectors like healthcare, transportation, manufacturing and more. The document also discusses challenges of digital transformation and provides a framework for how organizations can evolve their products, operations and business models. It provides examples of companies like Bayer Crop Science and Valmet that are using AWS IoT services to drive operational efficiency and analytics. Finally, it discusses how IoT can enable new "as-a-service" business models focused on outcomes rather than product sales.
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.
AWS를 활용한 Digital Manufacturing 실현 방법 및 사례 소개 - Douglas Bellin, 월드와이드 제조 솔루션 담...Amazon Web Services Korea
AWS를 활용한 Digital Manufacturing 실현 방법 및 사례 소개
Douglas Bellin, 월드와이드 제조 솔루션 담당 디렉터, AWS
장대기 대리, GS Caltex
제조업의 디지털 혁신을 위해 오퍼레이션 및 고객 데이터 등을 분석하고, 이를 경영 전략에 활용하는 것이 점점 중요해 지고 있습니다. 본 세션에서는 제조업 현장에서 클라우드를 도입하는 다양한 해외 사례를 소개하고, 이의 구현을 위한 아키텍쳐를 소개합니다. 이어 AWS 고객사인 GS Caltex 의 정유 산업에서의 혁신 사례가 소개됩니다.
Level: Introductory
The infinite computing power of cloud is creating new business models and driving operational efficiencies in every sector. But how can you extend cloud capabilities to the edge? Join this webinar for real-world examples of how AWS customers are exploiting both IoT data and the power of the cloud. We'll also discuss how you can deploy analytics and machine learning at the edge through AWS building blocks such as AWS Greengrass and Amazon Sagemaker.
Customer use cases to be explored include:
- Nokia optimises communications to oil platforms by processing data nearer to the source
- Stanley Black&Decker performs predictive maintenance by identifying faulty parts before they fail
- Pentair overcomes intermittent connectivity issues to automate its water filtration plants
Who Should Attend: Business Directors, Business Leaders, Project Managers, IT Managers, Business Consultants, Heads of Innovation, Data Scientists and Product Marketeers.
Securing the edge with AWS IoT services - FND330 - AWS re:Inforce 2019 Amazon Web Services
Edge computing is one of the most important enablers of the future. It saves lives, democratizes resources, and reduces costs in scenarios where near real-time action is required. This session covers how to keep edge computing secure. We dive deep into how AWS IoT Greengrass authenticates and encrypts device data for local and cloud communications so that data is never exchanged without proven identity. You can leverage hardware-secured, end-to-end encryption for messages exchanged between devices, an AWS IoT Greengrass core, and the AWS Cloud, and for messages between an AWS IoT Greengrass core and other local devices using the AWS IoT device SDK.
Why customers run SAP on AWS for Industry 4.0::Douglas Bellin::제조업 이노베이션 데이 S...Amazon Web Services Korea
The document discusses Industry 4.0 and how cloud computing can enable smart factories and smart products through connectivity, data collection/analytics, and machine learning. It provides examples of companies like Valmet and Wärtsilä that are using AWS services like IoT Analytics and Greengrass to improve operations and predictive maintenance. The document also discusses how running SAP applications on AWS can provide benefits like reduced costs, increased agility, scalability, and faster deployment times compared to on-premises data centers.
This document discusses how AWS can help improve manufacturing operations through digital transformation and industrial IoT. It begins by outlining key industry trends and challenges facing manufacturing, such as emerging markets, complex supply chains, demanding customers, and workforce issues. It then provides examples of how manufacturers are using AWS services like IoT, machine learning and analytics to gain insights from data, optimize operations, improve quality and efficiency, and protect intellectual property. Specific use cases discussed include predictive maintenance, quality control, and asset monitoring. The reference architecture shows how AWS services integrate with existing IT and OT systems to securely connect devices at the edge to applications in the cloud.
The document discusses a presentation in Taipei on predictive maintenance and smart IoT applications using AWS. It provides an overview of digital transformation and Industry 4.0 in manufacturing. It then summarizes Softchef's IoT cloud management platform and how it can help companies accelerate IoT solution development. Finally, it introduces Taikkiso as a supplier of rotating equipment and discusses how IoT and data analytics can help address industrial clients' needs.
Industrial IoT Applications: Making the Connection and Extracting Value (IOT3...Amazon Web Services
Industrial IoT applications are rapidly emerging across industries such as oil and gas, manufacturing, and agriculture. In this chalk talk, we help you architect end-to-end solutions that will deliver value like predictive maintenance, manufacturing quality, and process monitoring. In this interactive session, we help you understand how to connect greenfield and brownfield infrastructure with AWS that leverages both AWS Greengrass (on premises) and other AWS Cloud services. Along the way, we show how the AWS Industrial IoT Reference Architecture is incorporated to build your industrial application.
Using AWS IoT & Amazon SageMaker to Improve Manufacturing Operations - SVC204...Amazon Web Services
Predictive maintenance holds great promise for improving industrial operations across many industries, including mining, manufacturing, oil and gas, and commercial agriculture. Industrial companies want to reap the benefits of IoT applications, but there is a lot to learn before getting started. In this session, we discuss how you can improve manufacturing plant efficiency with predictive maintenance and asset condition monitoring using AWS services, including AWS IoT Core, AWS IoT Greengrass, and Amazon SageMaker. We'll also be joined on stage with Reliance Steel & Aluminum Co., the largest metals service center operator in North America, is improving their manufacturing plant efficiency with preventative maintenance and asset management using AWS services including AWS IoT Core, AWS IoT Greengrass, and Amazon SageMaker.
The document discusses challenges in the oil and gas industry with legacy equipment and the need for scalable IoT solutions. It proposes that AWS IoT architecture can address issues of security, scalability and integrating old and new devices by connecting things at the edge to analytics and computing resources in the cloud. Examples are given of how Ambyint has used high-resolution sensor data and machine learning on AWS to develop autonomous solutions for well optimization, improving productivity and reducing costs.
The Internet of Things (IoT) keeps evolving, and there’s a critical need for high-speed data processing, analytics, and reduced latency at the edge. Meeting the needs of these systems that leverage a distributed architecture to bring compute resources to the edge and the cloud is essential. A cloud-only model might not be applicable for time-sensitive operations or where network connectivity is poor. Also, connecting every device to the cloud and sending raw data over the internet can have privacy, security, and legal implications, especially for sensitive data. Learn how AWS extends AWS Greengrass to devices, so they can act locally on data and use the cloud for management, analytics, and durable storage.
The document discusses how AWS can help manufacturers with their digital transformation and Industry 4.0 initiatives. It outlines how AWS enables smart factories and smart products through connectivity, sensors, cloud computing, analytics and AI. This allows for increased efficiency, data-driven decision making, and products that improve over time. The document also provides an example of how AWS technologies like IoT, machine learning and analytics can help optimize manufacturing operations and meet business goals. Finally, it presents an AWS reference architecture for integrating manufacturing systems with the cloud.
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.
The intersection of AI and IoT presents new opportunities to create value for your business, capturing new insights from the vast amounts of IoT data available, which results in stronger customer relationships and new efficiencies. In this session, we discuss the future of operations and product development when AI and IoT meet to make autonomous decisions faster and better.
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.
17. DataDecisionInsight
BusinessValue
Humaninputtodecision
Phase of IoT Values
DATA ACQUISITION
Enhance
Knowledge
(Data Applied)
GET CONNECTED
• Define / Deploy Devices
• Real-time data collection
LIMITED DATA
• Adhoc reporting
• No historical data
INSIGHTS
How Do We Add Value
(Applied Data Insights)
GAIN INSIGHTS
• Customer scoring & Asset scoring
• Cause & effect
GAIN UNDERSTANDING
• Understand customer usage
• Correlation
INTELLIGENCE
Drive Sustainable Value to
Customers
(Insights Action)
DATA-DRIVEN INNOVATION
• Highly differentiated revenue- generating services
• Build your long term digital relationships with customers
• Remote products have autonomous actions
• Process becomes more agile and continuous
18. DataDecisionInsight
Past Present Future
Analytics Focus
BusinessValue
Descriptive Analytics
What has happened?
Humaninputtodecision
Diagnostic Analytics
Why did it happen?
Predictive Analytics
What will happen?
Prescriptive Analytics
What should I do?
How will these decisions impact?
Analytics Landscape and Maturity
19. Machine Learning Transformation Path -
Manufacture
Data Lake
Descriptive
Understand Data
Predictive
Use Historical Data
Prescriptive
Machine Learning
• Security
• Governance
• Compliancy
• Lifecycle
• ETL
• BI Reporting
• Data statistics
• Knowledge Graph
• Describe, show or
summarize data in
a meaningful way
• Demand Forecasting
• Anomaly Detection
• Fraud detection
• Predictive Maintenance
• Industry 4.0
• Raw Materials Pricing
Forecasting
• Demand / Production
Planning
• Pricing Optimization
• Worker Safety
• Security Immersion Day
• Data Migration
• 3A on Data Management:
Authentication, Authorization and
Audit
• Big Data Immersion Day
• Workshop and POC
• AWS Glue
• Amazon RDS
• Amazon EMR
• Amazon Redshift
• Amazon QuickSight
• ML Solutions Lab
• IoT Lab
• ML Discovery Workshop
• Amazon SageMaker
• Deep Lens
• AWS IoT
AWSServicesBusinessNeeds
23. NEXAIOT 新漢智能 致力於物聯網雲端整合與執行之策略夥伴
AWS : 工業雲展現數據分析與儲存應用
• AWS 雲端 AWS EC2 , S3 and DB
• AWS 雲端AWS EMR 進行數據分析
• AWS 展現3D戰情, AR眼鏡與數據
NEXAIOT 新漢智能 : OT 設備貫通
• 整合OPC.等底層設備
• 新漢智能提供3D戰情與及時信息
• Edge server 整合 AWS GG
貫通 OT 設備
新漢智能 edge server
With
• NEXAIOT : OPC,Modbus…
• Amazon : AWS GG
24. Solution
• NEXAIOT Edge server with AWS GreenGrass.
• Edge server include OPC UA Server and IOT studio.
• IoT Core reports status to the 3D Dashboard Room and saves
historical data in S3 for Data Analytics
• 3D Dashboard Room monitor and detect alerts and can take
action/control devices from remote
Smart Building & Factory Facility
3D Dashboard room
NEXAIOT Edge Server
• AWS GG
• NEXAIOT IoT Studio
Building/Factory
Facilities : 水電油氣
Control path
Data path
OPC UA
AWS Cloud
36. 智慧工廠 – 石化業
FormosaPetrol Company – Cloud/BigSCADA System
Industry Flow
Subsystem
(PLC)
DCS System
PMS
Station
Industry Ethernet
Prediction Maintenance
System
AMI SystemFactory/Process
Automation System
Safety Control
Rockwell
Automation
Vibration Monitoring
Safety
System
(SIL3)
Gateway
MMI Station CCTV
Data Server
Cloud Gateway
Gateway
DCS
Controller
Zigbee
EtherNet/IP DeviceNet
PFOFINET PROFIBUS