Perform Social Media Sentiment Analysis with Amazon Pinpoint & Amazon Compreh...Amazon Web Services
In this workshop, we show you how to easily deploy an AWS solution that ingests all Tweets from any Twitter handle, uses Amazon Comprehend to generate a sentiment score, and then automatically engages customers with a dynamic, personalized message. The intended audience is developers and marketers who want to leverage AWS to create powerful user engagement scenarios. We highlight how quickly you can deploy a machine learning marketing solution. We cover Amazon Pinpoint, the AWS user engagement service, and Amazon Comprehend, the AWS natural language processing service that uses artificail intelligence and machine learning to find insights and relationships in text.
[NEW LAUNCH!] Introducing Amazon Comprehend Medical (AIM398) - AWS re:Invent ...Amazon Web Services
The document introduces Amazon Comprehend Medical, a new machine learning service that can extract medical information from unstructured text with high accuracy. It discusses how Comprehend Medical can help analyze large amounts of clinical notes and reports by identifying entities, relationships, and protected health information. Two customer use cases are presented: Fred Hutchinson Cancer Research Center uses it to gain insights from clinical trials, and Roche Diagnostics uses it to enhance data quality and clinical decision support.
Business Intelligence in Minutes with Amazon Athena and Amazon QuickSightAmazon Web Services
Leverage Amazon S3, Amazon Athena, and Amazon QuickSight to explore and visualise data without having to manage a database or spin up a server. We will show you how to upload a dataset to a Data Lake in the AWS Cloud, optimise it in a format that enables high speed queries using SQL, and create rich web-based visualisations from those results.
Speaker: Aun Iftikhar, Solutions Architect, AWS
[NEW LAUNCH!] How to build and deploy Windows file system in AWS using Amazon...Amazon Web Services
If you have compute-intensive workloads like high performance computing, machine learning, and media processing then this is the workshop for you! Our new file storage service, Amazon FSx for Lustre, provides compute-optimized storage with fully managed Lustre file systems that can deliver hundreds of gigabytes of throughput and sub-millisecond latencies. You will learn how to spin up an FSx for Lustre file system in minutes, feed data to it from an S3 data lake, run analyses while writing results back to S3, and then spin down the file system once the workload is finished.
Searching Your Data with Amazon Elasticsearch Service (ANT384) - AWS re:Inven...Amazon Web Services
The document discusses Elasticsearch and Amazon Elasticsearch Service. It provides an overview of Elasticsearch as a popular open-source database engine for search and analysis. It then summarizes Amazon Elasticsearch Service as a fully managed service that makes it easy to deploy, manage, and scale Elasticsearch and Kibana. The document also briefly discusses how Amazon Elasticsearch Service integrates with other AWS services and supports open-source APIs and tools.
Join us to learn why Human-in-the-Loop training data should be powering your machine learning (ML) projects and how to make it happen. If you’re curious about what human-in-the-loop machine learning actually looks like, join Figure Eight CTO Robert Munro and AWS machine learning experts to learn how to effectively incorporate active learning and human-in-the-loop practices in your ML projects to achieve better results.
You'll learn:
- When to use human-in-the-loop as an effective strategy for machine learning projects
- How to set up an effective interface to get the most out of human intelligence
- How to ensure high-quality, accurate data sets
AWS 인공지능 서비스와 서버리스 서비스를 이용한 동영상 분석 서비스 구축하기 (김현수/황윤상, AWS 솔루션즈 아키텍트) :: AWS D...Amazon Web Services Korea
AWS 인공지능 서비스와 서버리스 서비스를 이용한 동영상 분석 서비스 구축하기
동영상에 포함되어 있는 다양한 정보를 쉽고 빠르게 분석하는 솔루션을 구축할 수 있습니다. VOD 동영상을 S3에 업로드하면, Lambda에서 Elemental MediaConvert를 호출하여 대량의 이미지로 분할하여 S3에 저장합니다. 대량의 이미지는 AWS Lambda를 활용하여 Rekognition 서비스를 호출하여 이미지 정보를 수집합니다. 수집 결과물은 ElasticSearch에 저장하고 Kibana를 통해 시각화 할 수 있습니다.
We Power Tech: Addressing Intersectionality in Tech (WPT203-S) - AWS re:Inven...Amazon Web Services
When diversity efforts focus only on gender, they further marginalize the marginalized. How do we make sure that we address the needs of everyone that is underrepresented in the industry? Are we reaching our marginalized customers? What can we do to provide a platform for those voices to be heard and support their efforts. In this session, we hear from technical leaders on the best ways to work with and include marginalized communities. This session is brought to you by AWS partner, Accenture.
Perform Social Media Sentiment Analysis with Amazon Pinpoint & Amazon Compreh...Amazon Web Services
In this workshop, we show you how to easily deploy an AWS solution that ingests all Tweets from any Twitter handle, uses Amazon Comprehend to generate a sentiment score, and then automatically engages customers with a dynamic, personalized message. The intended audience is developers and marketers who want to leverage AWS to create powerful user engagement scenarios. We highlight how quickly you can deploy a machine learning marketing solution. We cover Amazon Pinpoint, the AWS user engagement service, and Amazon Comprehend, the AWS natural language processing service that uses artificail intelligence and machine learning to find insights and relationships in text.
[NEW LAUNCH!] Introducing Amazon Comprehend Medical (AIM398) - AWS re:Invent ...Amazon Web Services
The document introduces Amazon Comprehend Medical, a new machine learning service that can extract medical information from unstructured text with high accuracy. It discusses how Comprehend Medical can help analyze large amounts of clinical notes and reports by identifying entities, relationships, and protected health information. Two customer use cases are presented: Fred Hutchinson Cancer Research Center uses it to gain insights from clinical trials, and Roche Diagnostics uses it to enhance data quality and clinical decision support.
Business Intelligence in Minutes with Amazon Athena and Amazon QuickSightAmazon Web Services
Leverage Amazon S3, Amazon Athena, and Amazon QuickSight to explore and visualise data without having to manage a database or spin up a server. We will show you how to upload a dataset to a Data Lake in the AWS Cloud, optimise it in a format that enables high speed queries using SQL, and create rich web-based visualisations from those results.
Speaker: Aun Iftikhar, Solutions Architect, AWS
[NEW LAUNCH!] How to build and deploy Windows file system in AWS using Amazon...Amazon Web Services
If you have compute-intensive workloads like high performance computing, machine learning, and media processing then this is the workshop for you! Our new file storage service, Amazon FSx for Lustre, provides compute-optimized storage with fully managed Lustre file systems that can deliver hundreds of gigabytes of throughput and sub-millisecond latencies. You will learn how to spin up an FSx for Lustre file system in minutes, feed data to it from an S3 data lake, run analyses while writing results back to S3, and then spin down the file system once the workload is finished.
Searching Your Data with Amazon Elasticsearch Service (ANT384) - AWS re:Inven...Amazon Web Services
The document discusses Elasticsearch and Amazon Elasticsearch Service. It provides an overview of Elasticsearch as a popular open-source database engine for search and analysis. It then summarizes Amazon Elasticsearch Service as a fully managed service that makes it easy to deploy, manage, and scale Elasticsearch and Kibana. The document also briefly discusses how Amazon Elasticsearch Service integrates with other AWS services and supports open-source APIs and tools.
Join us to learn why Human-in-the-Loop training data should be powering your machine learning (ML) projects and how to make it happen. If you’re curious about what human-in-the-loop machine learning actually looks like, join Figure Eight CTO Robert Munro and AWS machine learning experts to learn how to effectively incorporate active learning and human-in-the-loop practices in your ML projects to achieve better results.
You'll learn:
- When to use human-in-the-loop as an effective strategy for machine learning projects
- How to set up an effective interface to get the most out of human intelligence
- How to ensure high-quality, accurate data sets
AWS 인공지능 서비스와 서버리스 서비스를 이용한 동영상 분석 서비스 구축하기 (김현수/황윤상, AWS 솔루션즈 아키텍트) :: AWS D...Amazon Web Services Korea
AWS 인공지능 서비스와 서버리스 서비스를 이용한 동영상 분석 서비스 구축하기
동영상에 포함되어 있는 다양한 정보를 쉽고 빠르게 분석하는 솔루션을 구축할 수 있습니다. VOD 동영상을 S3에 업로드하면, Lambda에서 Elemental MediaConvert를 호출하여 대량의 이미지로 분할하여 S3에 저장합니다. 대량의 이미지는 AWS Lambda를 활용하여 Rekognition 서비스를 호출하여 이미지 정보를 수집합니다. 수집 결과물은 ElasticSearch에 저장하고 Kibana를 통해 시각화 할 수 있습니다.
We Power Tech: Addressing Intersectionality in Tech (WPT203-S) - AWS re:Inven...Amazon Web Services
When diversity efforts focus only on gender, they further marginalize the marginalized. How do we make sure that we address the needs of everyone that is underrepresented in the industry? Are we reaching our marginalized customers? What can we do to provide a platform for those voices to be heard and support their efforts. In this session, we hear from technical leaders on the best ways to work with and include marginalized communities. This session is brought to you by AWS partner, Accenture.
AWS Public Datasets: Learnings from Staging Petabytes of Data for Analysis in...Amazon Web Services
AWS hosts a variety of public data sets that anyone can access for free. Previously, large datasets such as satellite imagery or genomic data have required hours or days to locate, download, customize, and analyze. When data is made publicly available on AWS, anyone can analyze any volume of data without needing to download or store it themselves. The AWS Open Data Team will share tips and tricks, patterns and anti-patterns and tools to help you most effectively stage your data for analysis in the cloud.
AWS Data-Driven Insights Learning Series ANZ Sep 2019 Part 1Amazon Web Services
AWS has been supporting companies across Australia and New Zealand to put their most innovative tools and technologies to work to achieve their business needs and goals. AWS and our ecosystem of partners has helped the likes of CP Mining, IntelliHQ, WesCEF, Oz Minerals, Woodside and many more to modernise their analytics and data architecture in order to successfully generate business value from their data.
This event series aimed to educate customers with a broader understanding of how to build next-gen data lakes and analytics platforms and make connections with AWS.
Build AWS Skills Through Community-Led User Groups (DVC202) - AWS reInvent 20...Amazon Web Services
This document discusses building AWS skills through community-led user groups. It lists panelists from various user groups and companies and provides information on joining online AWS community channels, submitting questions during a panel discussion using a specific Slido code, and finding AWS user groups worldwide.
How to Build HR Lakes on AWS to Unlock New Business Insights (DAT367) - AWS r...Amazon Web Services
In this session, learn how to create an HR data lake on AWS to develop a more wholistic view of people data to enable secure, self-service reporting for HR business partners and managers, and to use more advanced data science tools to unlock new insights to reduce retention, enhance hiring practices, and improve employee productivity. We provide examples of HR insights and the business value they can drive, walk through a reference architecture example for an HR data lake, and outline key steps and best practices as you design and launch your HR data lake project. AWS services addressed in this session include AWS Lambda, Amazon S3, AWS Glue, and Amazon Athena.
Create Advanced Text Analytics Solutions with NLP - BDA310 - Chicago AWS SummitAmazon Web Services
The document discusses Amazon Comprehend, a natural language processing service that helps analyze and organize unstructured text. It provides examples of how Comprehend is used for applications like social media analytics, customer service, and food safety. Specifically, it describes how one company used Comprehend to analyze social media data to identify potential food safety issues.
Wilson To gave a leadership session on innovation in healthcare at the HLC 2018 conference. The presentation covered how AWS is supporting healthcare through growing HIPAA-eligible services, advanced technology partners, and the AWS Healthcare Competency Center. It also discussed industry pressures and initiatives for both healthcare providers and payers, including the transition to value-based care and using data science for risk modeling. Examples were provided of customers like UPMC leveraging AWS for applications and data management.
Monetize Your Mobile App with Amazon Mobile Ads (MOB311) - AWS reInvent 2018.pdfAmazon Web Services
With the freemium model now the new norm for mobile apps, developers often supplement their revenue with ad-based monetization. Businesses utilize and depend on targeted ads for better engagement and mediation services to manage multiple ad networks to maximize ad revenue. In this workshop, we cover the latest best practices for targeted ad placement for modern apps from basic, interstitial, and incentive videos. We also discuss how targeted ad mediation plays a key role in optimizing app revenue. We then dive into creating a mobile app that is integrated with Amazon Mobile Ads to showcase the revenue possibilities and vault you directly to the bank.
The document discusses tools for designing, building, testing, and launching Alexa skills. It provides guidance on voice design principles, handling synonyms, storing persistent user data, testing skills with real users, and using the Alexa Skills Kit and tools from Pulse Labs to streamline the development process. Skill testing is emphasized as important for gathering feedback from users to iterate on the design.
The document discusses a leadership session on using cloud technologies to accelerate innovation for intelligent, connected products in the high-tech and semiconductor industries. It highlights key workloads like electronic design automation (EDA) and examples of companies innovating faster on AWS through more efficient EDA workflows, faster software testing, and reduced product development times.
통합 머신러닝 플랫폼 Amazon SageMaker 활용하기 (강지양 & 김태현, AWS 솔루션즈 아키텍트) :: AWS DevDay2018Amazon Web Services Korea
통합 머신러닝 플랫폼 Amazon SageMaker 활용하기
데이터 사이언티스트와 개발자들이 쉽고 빠르게 구성, 학습하고 어떤 규모로든 기계 학습된 모델을 배포할 수 있도록 해주는 관리형 서비스, Amazon SageMaker에 내장된 학습 기능을 사용하여 모델 훈련 Job 생성하고 예측에 사용될 수 있도록 endpoint를 생성하고 머신 러닝이 정형 데이터 (e.g. CSV 파일), 비정형 데이터 (e.g. 이미지)에 모두 적용될 수 있음을 다양한 실습 예제들을 통해 확인합니다.
Creating Rich, Interactive Business Dashboards in Amazon QuickSight (ANT339) ...Amazon Web Services
Are you ready to move past static email reports, Excel spreadsheets, and one-time queries? In this session, learn to build a rich and interactive business dashboard in Amazon QuickSight that allows your business stakeholders to filter, slice and dicem and deep dive on their own. We’ll demonstrate some advanced QuickSight capabilities such as creating on sheet filter controls, parameters, custom URLs, and table calculations to create powerful, easy-to-use, and interactive executive dashboards.
Supercell – Scaling Mobile Games (GAM301) - AWS re:Invent 2018Amazon Web Services
This document discusses Supercell's approach to scaling their mobile games and analytics infrastructure. Supercell has 5 games with hundreds of millions of active users. They use a microservices architecture and sharding to scale their games across thousands of EC2 instances. Their analytics pipeline collects terabytes of data daily, storing it in S3 and processing it with EMR. They have transitioned to separating compute and storage to better scale their analytics capabilities.
Get Started with Real-Time Streaming Data in Under 5 Minutes - AWS Online Tec...Amazon Web Services
Learning Objectives:
- Identify common problems that streaming data can help solve
- Understand the AWS services that are used to solve these problems, including Amazon Kinesis
- Try out one of 5+ different solutions powered by Amazon Kinesis through AWS CloudFormation templates
Amazon Cloud Directory Deep Dive (DAT364) - AWS re:Invent 2018Amazon Web Services
Learn how companies like FocusCura and Clouden have on-boarded hierarchical data at scale using Amazon Cloud Directory, a highly available, fully managed, serverless, hierarchical datastore. It’s well-suited for such use cases as human resources applications, course catalogs, device registry, network topology, and any application that needs fine-grained permissions (authorization). We do a deep dive into the internals of Cloud Directory and discuss best practices.
A data lake is an architectural approach that allows you to store massive amounts of data into a central location, so it's readily available to be categorized, processed, analyzed and consumed by diverse groups within an organization.In this session, we will introduce the Data Lake concept and its implementation on AWS.We will explain the different roles our services play and how they fit into the Data Lake picture.
ML Workflows with Amazon SageMaker and AWS Step Functions (API325) - AWS re:I...Amazon Web Services
The document discusses how Cox Automotive combined Amazon SageMaker and AWS Step Functions to improve collaboration between their data science and software engineering teams. It describes how SageMaker is used to build, train, and deploy machine learning models, and how Step Functions allows the creation of serverless workflows with less code. Cox Automotive built a workflow that uses Step Functions to automate SageMaker model deployment and add manual review steps to ensure quality models are delivered with minimal human intervention.
AWS Welcome and Opening - Startup Day Toronto 2018 - Jim RouthAmazon Web Services
The document discusses how startups have evolved over time and how AWS has helped enable faster development. It notes that in 2010 it would take months and a team of engineers to develop an idea, while in 2018 it can take weeks and a single engineer. Startups using AWS in 2010 had to focus on infrastructure setup in the early days, while 2018 startups can focus on product from day one as AWS provides automated scalable infrastructure. It highlights specific AWS services like Lambda, API Gateway, ECS, and Kinesis that help startups build and scale applications quickly.
ABD209_Accelerating the Speed of Innovation with a Data Sciences Data & Analy...Amazon Web Services
"Historically, silos of data, analytics, and processes across functions, stages of development, and geography created a barrier to R&D efficiency. Gathering the right data necessary for decision-making was challenging due to issues of accessibility, trust, and timeliness. In this session, learn how Takeda is undergoing a transformation in R&D to increase the speed-to-market of high-impact therapies to improve patient lives. The Data and Analytics Hub was built, with Deloitte, to address these issues and support the efficient generation of data insights for functions such as clinical operations, clinical development, medical affairs, portfolio management, and R&D finance. In the AWS hosted data lake, this data is processed, integrated, and made available to business end users through data visualization interfaces, and to data scientists through direct connectivity. Learn how Takeda has achieved significant time reductions—from weeks to minutes—to gather and provision data that has the potential to reduce cycle times in drug development. The hub also enables more efficient operations and alignment to achieve product goals through cross functional team accountability and collaboration due to the ability to access the same cross domain data.
Session sponsored by Deloitte"
by Marie Yap, Enterprise Solutions Architect and Karthik Odapally, Solutions Architect, AWS
We'll take a look at the fast, cloud-powered business analytics service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data. We'll show how you can use Amazon QuickSight to easily connect to your data, perform advanced analysis, and create stunning visualizations and rich dashboards that can be accessed from any browser or mobile device.
In this session, we will focus on the data architecture of the application. Enabling different personas in the organization, (e.g., senior management, data scientists, data engineer, etc.), the ability to access relevant data points and produce valuable insights. We will understand key concepts and architectural components of a data lake architecture as well as how to build speed layer and batch layer data processing flows.
The first step towards knowing your customer is to collect and extract insights and actionable information from your data. Learn how AWS enables you to cost efficiently store any amount of data and build an agile approach to data mining and visualization - helping you to make efficient business decisions and targeted offerings.
AWS Public Datasets: Learnings from Staging Petabytes of Data for Analysis in...Amazon Web Services
AWS hosts a variety of public data sets that anyone can access for free. Previously, large datasets such as satellite imagery or genomic data have required hours or days to locate, download, customize, and analyze. When data is made publicly available on AWS, anyone can analyze any volume of data without needing to download or store it themselves. The AWS Open Data Team will share tips and tricks, patterns and anti-patterns and tools to help you most effectively stage your data for analysis in the cloud.
AWS Data-Driven Insights Learning Series ANZ Sep 2019 Part 1Amazon Web Services
AWS has been supporting companies across Australia and New Zealand to put their most innovative tools and technologies to work to achieve their business needs and goals. AWS and our ecosystem of partners has helped the likes of CP Mining, IntelliHQ, WesCEF, Oz Minerals, Woodside and many more to modernise their analytics and data architecture in order to successfully generate business value from their data.
This event series aimed to educate customers with a broader understanding of how to build next-gen data lakes and analytics platforms and make connections with AWS.
Build AWS Skills Through Community-Led User Groups (DVC202) - AWS reInvent 20...Amazon Web Services
This document discusses building AWS skills through community-led user groups. It lists panelists from various user groups and companies and provides information on joining online AWS community channels, submitting questions during a panel discussion using a specific Slido code, and finding AWS user groups worldwide.
How to Build HR Lakes on AWS to Unlock New Business Insights (DAT367) - AWS r...Amazon Web Services
In this session, learn how to create an HR data lake on AWS to develop a more wholistic view of people data to enable secure, self-service reporting for HR business partners and managers, and to use more advanced data science tools to unlock new insights to reduce retention, enhance hiring practices, and improve employee productivity. We provide examples of HR insights and the business value they can drive, walk through a reference architecture example for an HR data lake, and outline key steps and best practices as you design and launch your HR data lake project. AWS services addressed in this session include AWS Lambda, Amazon S3, AWS Glue, and Amazon Athena.
Create Advanced Text Analytics Solutions with NLP - BDA310 - Chicago AWS SummitAmazon Web Services
The document discusses Amazon Comprehend, a natural language processing service that helps analyze and organize unstructured text. It provides examples of how Comprehend is used for applications like social media analytics, customer service, and food safety. Specifically, it describes how one company used Comprehend to analyze social media data to identify potential food safety issues.
Wilson To gave a leadership session on innovation in healthcare at the HLC 2018 conference. The presentation covered how AWS is supporting healthcare through growing HIPAA-eligible services, advanced technology partners, and the AWS Healthcare Competency Center. It also discussed industry pressures and initiatives for both healthcare providers and payers, including the transition to value-based care and using data science for risk modeling. Examples were provided of customers like UPMC leveraging AWS for applications and data management.
Monetize Your Mobile App with Amazon Mobile Ads (MOB311) - AWS reInvent 2018.pdfAmazon Web Services
With the freemium model now the new norm for mobile apps, developers often supplement their revenue with ad-based monetization. Businesses utilize and depend on targeted ads for better engagement and mediation services to manage multiple ad networks to maximize ad revenue. In this workshop, we cover the latest best practices for targeted ad placement for modern apps from basic, interstitial, and incentive videos. We also discuss how targeted ad mediation plays a key role in optimizing app revenue. We then dive into creating a mobile app that is integrated with Amazon Mobile Ads to showcase the revenue possibilities and vault you directly to the bank.
The document discusses tools for designing, building, testing, and launching Alexa skills. It provides guidance on voice design principles, handling synonyms, storing persistent user data, testing skills with real users, and using the Alexa Skills Kit and tools from Pulse Labs to streamline the development process. Skill testing is emphasized as important for gathering feedback from users to iterate on the design.
The document discusses a leadership session on using cloud technologies to accelerate innovation for intelligent, connected products in the high-tech and semiconductor industries. It highlights key workloads like electronic design automation (EDA) and examples of companies innovating faster on AWS through more efficient EDA workflows, faster software testing, and reduced product development times.
통합 머신러닝 플랫폼 Amazon SageMaker 활용하기 (강지양 & 김태현, AWS 솔루션즈 아키텍트) :: AWS DevDay2018Amazon Web Services Korea
통합 머신러닝 플랫폼 Amazon SageMaker 활용하기
데이터 사이언티스트와 개발자들이 쉽고 빠르게 구성, 학습하고 어떤 규모로든 기계 학습된 모델을 배포할 수 있도록 해주는 관리형 서비스, Amazon SageMaker에 내장된 학습 기능을 사용하여 모델 훈련 Job 생성하고 예측에 사용될 수 있도록 endpoint를 생성하고 머신 러닝이 정형 데이터 (e.g. CSV 파일), 비정형 데이터 (e.g. 이미지)에 모두 적용될 수 있음을 다양한 실습 예제들을 통해 확인합니다.
Creating Rich, Interactive Business Dashboards in Amazon QuickSight (ANT339) ...Amazon Web Services
Are you ready to move past static email reports, Excel spreadsheets, and one-time queries? In this session, learn to build a rich and interactive business dashboard in Amazon QuickSight that allows your business stakeholders to filter, slice and dicem and deep dive on their own. We’ll demonstrate some advanced QuickSight capabilities such as creating on sheet filter controls, parameters, custom URLs, and table calculations to create powerful, easy-to-use, and interactive executive dashboards.
Supercell – Scaling Mobile Games (GAM301) - AWS re:Invent 2018Amazon Web Services
This document discusses Supercell's approach to scaling their mobile games and analytics infrastructure. Supercell has 5 games with hundreds of millions of active users. They use a microservices architecture and sharding to scale their games across thousands of EC2 instances. Their analytics pipeline collects terabytes of data daily, storing it in S3 and processing it with EMR. They have transitioned to separating compute and storage to better scale their analytics capabilities.
Get Started with Real-Time Streaming Data in Under 5 Minutes - AWS Online Tec...Amazon Web Services
Learning Objectives:
- Identify common problems that streaming data can help solve
- Understand the AWS services that are used to solve these problems, including Amazon Kinesis
- Try out one of 5+ different solutions powered by Amazon Kinesis through AWS CloudFormation templates
Amazon Cloud Directory Deep Dive (DAT364) - AWS re:Invent 2018Amazon Web Services
Learn how companies like FocusCura and Clouden have on-boarded hierarchical data at scale using Amazon Cloud Directory, a highly available, fully managed, serverless, hierarchical datastore. It’s well-suited for such use cases as human resources applications, course catalogs, device registry, network topology, and any application that needs fine-grained permissions (authorization). We do a deep dive into the internals of Cloud Directory and discuss best practices.
A data lake is an architectural approach that allows you to store massive amounts of data into a central location, so it's readily available to be categorized, processed, analyzed and consumed by diverse groups within an organization.In this session, we will introduce the Data Lake concept and its implementation on AWS.We will explain the different roles our services play and how they fit into the Data Lake picture.
ML Workflows with Amazon SageMaker and AWS Step Functions (API325) - AWS re:I...Amazon Web Services
The document discusses how Cox Automotive combined Amazon SageMaker and AWS Step Functions to improve collaboration between their data science and software engineering teams. It describes how SageMaker is used to build, train, and deploy machine learning models, and how Step Functions allows the creation of serverless workflows with less code. Cox Automotive built a workflow that uses Step Functions to automate SageMaker model deployment and add manual review steps to ensure quality models are delivered with minimal human intervention.
AWS Welcome and Opening - Startup Day Toronto 2018 - Jim RouthAmazon Web Services
The document discusses how startups have evolved over time and how AWS has helped enable faster development. It notes that in 2010 it would take months and a team of engineers to develop an idea, while in 2018 it can take weeks and a single engineer. Startups using AWS in 2010 had to focus on infrastructure setup in the early days, while 2018 startups can focus on product from day one as AWS provides automated scalable infrastructure. It highlights specific AWS services like Lambda, API Gateway, ECS, and Kinesis that help startups build and scale applications quickly.
ABD209_Accelerating the Speed of Innovation with a Data Sciences Data & Analy...Amazon Web Services
"Historically, silos of data, analytics, and processes across functions, stages of development, and geography created a barrier to R&D efficiency. Gathering the right data necessary for decision-making was challenging due to issues of accessibility, trust, and timeliness. In this session, learn how Takeda is undergoing a transformation in R&D to increase the speed-to-market of high-impact therapies to improve patient lives. The Data and Analytics Hub was built, with Deloitte, to address these issues and support the efficient generation of data insights for functions such as clinical operations, clinical development, medical affairs, portfolio management, and R&D finance. In the AWS hosted data lake, this data is processed, integrated, and made available to business end users through data visualization interfaces, and to data scientists through direct connectivity. Learn how Takeda has achieved significant time reductions—from weeks to minutes—to gather and provision data that has the potential to reduce cycle times in drug development. The hub also enables more efficient operations and alignment to achieve product goals through cross functional team accountability and collaboration due to the ability to access the same cross domain data.
Session sponsored by Deloitte"
by Marie Yap, Enterprise Solutions Architect and Karthik Odapally, Solutions Architect, AWS
We'll take a look at the fast, cloud-powered business analytics service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data. We'll show how you can use Amazon QuickSight to easily connect to your data, perform advanced analysis, and create stunning visualizations and rich dashboards that can be accessed from any browser or mobile device.
In this session, we will focus on the data architecture of the application. Enabling different personas in the organization, (e.g., senior management, data scientists, data engineer, etc.), the ability to access relevant data points and produce valuable insights. We will understand key concepts and architectural components of a data lake architecture as well as how to build speed layer and batch layer data processing flows.
The first step towards knowing your customer is to collect and extract insights and actionable information from your data. Learn how AWS enables you to cost efficiently store any amount of data and build an agile approach to data mining and visualization - helping you to make efficient business decisions and targeted offerings.
The first step towards knowing your customer is to collect and extract insights and actionable information from your data. Learn how AWS enables you to cost efficiently store any amount of data and build an agile approach to data mining and visualization - helping you to make efficient business decisions and targeted offerings.
Get to Know Your Customers - Build and Innovate with a Modern Data ArchitectureAmazon Web Services
Your customers probably want a better experience with your brand. Your different business teams want and need better insights in their decision making. Almost certainly, your finance and operations teams require this to happen at a fraction of the cost of traditional on-premises options. Modern data architectures on AWS help many of our best customers realise all of those goals. Your business data contains critical information about customer behaviours, operational decisions, and many factors that have financial impact on your organisation. Increasingly, this data sits beyond your transactional systems, and is too big, too fast, and too complex for existing systems to handle. AWS Data and Analytics services are designed from our customers' requirements to ingest, store, analyse, and consume information at record-breaking scale. In this session you will learn how these services work together to deliver business automation, enhance customer engagement and intelligence.
Using Big Data Retail to Build a Single View of Your Customer.pdfAmazon Web Services
A key challenge faced by retailers is how to form an integrated single view of their customers across multiple retail channels to better understand purchasing behaviours and patterns. In this session, we’ll present a solution that merges web analytics data with customer purchase history based on AWS API Gateway, Lambda, and S3. Learn how to track customer purchase behaviours across channels to better predict future needs and make relevant, intelligent recommendations.
AI/ML with Data Lakes: Counterintuitive Consumer Insights in Retail (RET206) ...Amazon Web Services
In this session, learn how data scientists in the retail industry, from companies like Tapestry, Coach, and Kate Spade, are finding new, counterintuitive consumer insights using AWS artificial intelligence services in a data lake. By leveraging data from various retail systems, including CRM, marketing, e-commerce, point of sale, order management, merchandising, and customer care, we show you how these consumer insights might influence new and interesting retail use cases while establishing a data-driven culture within the organization. Services referenced include Amazon S3, Amazon Machine Learning, Amazon QuickSight, Amazon SageMaker, among others.
This document provides an agenda and overview for an MLOps workshop hosted by Amazon Web Services. The agenda includes introductions to Amazon AI, MLOps, Amazon SageMaker, machine learning pipelines, and a hands-on exercise to build an MLOps pipeline. It discusses key concepts like personas in MLOps, the CRISP-DM process, microservices deployment, and challenges of MLOps. It also provides overviews of Amazon SageMaker for machine learning and AWS services for continuous integration/delivery.
[REPEAT] Better Analytics Through Natural Language Processing (AIM405-R) - AW...Amazon Web Services
Natural language processing holds the key to unlocking business value from unstructured data. Organizations that implement effective data analysis methods gain a competitive advantage through improved decision-making, risk reduction, or enhanced customer experience. In this session, learn how to easily process, analyze, and visualize data by pairing Amazon Comprehend with services like Amazon Relational Database Service (Amazon RDS), Amazon Elasticsearch Service, and Amazon Neptune. We also share real-world examples of how customers built text analytics solutions with Amazon Comprehend.
Build, train, and deploy machine learning models at scale
Machine learning often feels a lot harder than it should be to most developers because the process to build and train models, and then deploy them into production is too complicated and too slow.
Amazon SageMaker includes modules that can be used together or independently to build, train, and deploy your machine learning models.
Olivier Bergeret - AWS
https://dataxday.fr/
Video available: https://www.youtube.com/watch?v=3eV4x_GR_f8
Emerging Trends in Big Data, Analytics, Machine Learning, and Internet-of-Thi...Michaela Bromfield
This presentation was delivered on March 7, 2018 at Gartner's Data and Analytics Summit in Grapevine, TX. Rahul Pathak, GM at AWS discusses Next Gen Architecture on AWS.
Your road to a Well Architected solution in the Cloud - Tel Aviv Summit 2018Amazon Web Services
The document discusses how the Well-Architected framework from AWS was used to help a customer transition their 20+ year old technology to the AWS cloud. It describes the challenges the customer faced with their on-premises infrastructure and how the Well-Architected pillars of security, reliability, performance efficiency, cost optimization, and operational excellence were applied. Examples are given for how tools like EC2, S3, CloudFormation, and Trusted Advisor can help optimize infrastructure for reliability, security, costs and operations on AWS.
We describe how to use the Well-Architected Framework to evaluate the technology solutions built by your teams. The AWS Well-Architected Framework describes best practices across five pillars (Security, Reliability, Performance, Operational Excellence, and Cost), and provides a consistent approach to review architectures against those best practices. This review process shows where your architectures can be improved, and helps you address weakness that may put your business at risk
The Theory and Math Behind Data Privacy and Security Assurance (SEC301) - AWS...Amazon Web Services
The document discusses AWS's Zelkova tool, which uses symbolic logic and satisfiability modulo theories (SMT) solving to encode identity and access management (IAM) policies as logical formulas. This allows customers to automatically check that their IAM configurations and governance rules are functioning as intended at scale. The document also describes how one enterprise customer, Bridgewater Associates, uses Zelkova to identify misconfigurations and reduce risks in their AWS environment.
Building a Data Lake for Your Enterprise, ft. Sysco (STG309) - AWS re:Invent ...Amazon Web Services
Data lakes are transforming the way enterprises store, analyze, and learn insights from their data. While data lakes are a relatively new concept, many enterprises have already generated significant business value from the insights gleaned. In this session, AWS experts and technology leaders from Sysco, a Fortune 50 company and leader in food distribution and marketing, explain why Sysco decided to evolve its data management capabilities to include data lakes and how they customized them to support diverse querying capabilities and data science use cases. They also discuss how to architect different aspects of a data lake—ingestion from disparate sources, data consumption, and usability layers—and how to track data ingestion and consumption, monitor associated costs, enforce wanted levels of user access, manage data file formats, synchronize production and non-production environments, and maintain data integrity. Services to be discussed include Amazon S3 and S3 Select, Amazon Athena, Amazon EMR, Amazon EC2, and Amazon Redshift Spectrum.
A decade ago, relational databases were used for nearly every use case. Today, new technologies are enabling a revolution in databases, creating new options for document, key: value, in-memory, search, and graph capabilities that do not use relational tables. We’ll discuss this revolution in database options and who is using them.
Level: 200
Speaker: Samir Karande - Sr. Manager, Solutions Architecture, AWS
Database Week at the San Francicso Loft
Non-Relational Revolution
A decade ago, relational databases were used for nearly every use case. Today, new technologies are enabling a revolution in databases, creating new options for document, key: value, in-memory, search, and graph capabilities that do not use relational tables. We’ll discuss this revolution in database options and who is using them.
Level: 200
Speakers:
Smitty Weygant - Solutions Architect, AWS
Karan Desai - Solutions Architect, AWS
Social Media Analytics with Amazon QuickSight (ANT370) - AWS re:Invent 2018Amazon Web Services
Realizing the value of social media analytics can bolster your business goals. This type of analysis has grown in recent years due to the large amount of available information and the speed at which it can be collected and analyzed. In this workshop, we build a serverless data processing and machine learning (ML) pipeline that provides a multi-lingual social media dashboard of tweets within Amazon QuickSight. We leverage API-driven ML services, AWS Glue, Amazon Athena and Amazon QuickSight. These building blocks are put together with very little code by leveraging serverless offerings within AWS.
Operating at Scale- Preparing for the Journey [Portuguese]Amazon Web Services
Nessa sessão nós iremos discutir as diferenças na preparação para operar na nuvem, quais precisam ser suas prioridades operacionais, como começar a projetar operações e como construir sua estrutura operacional. Você irá entender quais decisões iniciais irão ajudá-lo a fundamentar a adoção de serviços de nuvem e quais são as principais considerações para planejar sua jornada pessoal nesse ambiente. Essa sessão se destina a lideres, engenheiros de operações, gerente de serviços e qualquer outra pessoa interessada em como começar na nuvem para garantir resultados de negócios de longo prazo bem-sucedidos.
Palestrante: Glauber Gallego
What are the different options for a developer to run his DB in the Cloud? This session will look into the different options and how to choose the right DB for your workload.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images