Enabling Edge Processing & Surgical Suite Integration with AWS Snowball Edge and Philips HealthSuite (STG346) - AWS re:Invent 2018

The document discusses building a data lake on AWS. It describes various AWS services that can be used to ingest, store, transform, analyze and visualize data in the data lake. These services include Amazon S3 for storage, AWS Glue for ETL/data cataloging, AWS Lake Formation for governance, Amazon Athena/EMR for analytics and Amazon QuickSight for visualization. The document also covers data movement options from on-premises to the data lake and real-time streaming of data using services like Kinesis. Machine learning workloads can leverage Amazon SageMaker for training and deployment.

AWS as a Data Platform

The document summarizes a presentation given at the AWS Government, Education, and Nonprofit Symposium on June 25-26, 2015 in Washington DC. The presentation discusses AWS as a data platform, highlighting the growing size and complexity of data as well as the various AWS services that can be used to store, process, analyze and gain insights from data at different scales. These services include S3, Glacier, DynamoDB, Redshift, EMR, Kinesis and Machine Learning among others. The presentation emphasizes that AWS provides a flexible suite of tools that can be used together to effectively manage the full data lifecycle and derive value from data.

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Mohammed Chaaraoui

Azure Purview provides a unified platform for data governance across hybrid and multi-cloud environments. It enables discovery of data assets, visualization of lineage and workflows, and management of a business glossary. Key features include automated scanning and classification of data, a centralized catalog for browsing and searching data, and insights into sensitive data and metadata usage. Purview integrates with services like Azure Synapse, Power BI, and Microsoft 365 to provide enhanced governance capabilities and propagate classifications and labels.

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Puneet Kumar Bhatia (MBA, ITIL V3 Certified)

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James Serra

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Big data is driving transformative changes in traditional data warehousing. Traditional ETL processes and highly structured data schemas are being replaced with schema flexibility to handle all types of data from diverse sources. This allows for real-time experimentation and analysis beyond just operational reporting. Microsoft is applying lessons from its own big data journey to help customers by providing a comprehensive set of Apache big data tools in Azure along with intelligence and analytics services to gain insights from diverse data sources.

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James Serra

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Amazon Web Services Korea

This document summarizes Atlassian's adoption of Databricks to manage their growing data pipelines and platforms. It discusses the challenges they faced with their previous architecture around development time, collaboration, and costs. With Databricks, Atlassian was able to build scalable data pipelines using notebooks and connectors, orchestrate workflows with Airflow, and provide self-service analytics and machine learning to teams while reducing infrastructure costs and data engineering dependencies. The key benefits included reduced development time by 30%, decreased infrastructure costs by 60%, and increased adoption of Databricks and self-service across teams.

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1. The document discusses various Google Cloud Platform products and patterns for data pipelines, including virtual machines, storage, data warehousing, streaming analytics, machine learning, internet of things, and bioinformatics. 2. Demos and examples are provided of storage, virtual machines, BigQuery, Cloud Spanner, and machine learning on the Google Cloud Platform. 3. The core Google Cloud Platform products discussed for various data and analytics use cases include Cloud Storage, BigQuery, Cloud Dataflow, Compute Engine, Cloud Pub/Sub, and Bigtable.

Learn to Use Databricks for Data Science

Data scientists face numerous challenges throughout the data science workflow that hinder productivity. As organizations continue to become more data-driven, a collaborative environment is more critical than ever — one that provides easier access and visibility into the data, reports and dashboards built against the data, reproducibility, and insights uncovered within the data.. Join us to hear how Databricks’ open and collaborative platform simplifies data science by enabling you to run all types of analytics workloads, from data preparation to exploratory analysis and predictive analytics, at scale — all on one unified platform.

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At AWS, cloud security is our highest priority. All AWS customers inherit the best practices of AWS policies, architecture, and operational processes built to satisfy the requirements of the most security-sensitive organizations in the most highly-regulated industries in the world – including financial services. In this talk, AWS experts discuss the fundamentals of AWS Cloud security, best practices, and services customers can leverage in order to operate and innovate in the cloud – more securely than on premises.

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Modern Network Operations with no Myths on SaaS, IaaS and PaaS discusses cloud computing characteristics such as massive, abstracted infrastructure and dynamic allocation of applications. It defines cloud services as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). The document also outlines cloud architecture types including public, private, and hybrid clouds. It analyzes the cloud computing market and opportunities for enterprises and software developers in utilizing public and private cloud services.

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Big Data Tutorial | What Is Big Data | Big Data Hadoop Tutorial For Beginners...

This presentation about Big Data will help you understand how Big Data evolved over the years, what is Big Data, applications of Big Data, a case study on Big Data, 3 important challenges of Big Data and how Hadoop solved those challenges. The case study talks about Google File System (GFS), where you’ll learn how Google solved its problem of storing increasing user data in early 2000. We’ll also look at the history of Hadoop, its ecosystem and a brief introduction to HDFS which is a distributed file system designed to store large volumes of data and MapReduce which allows parallel processing of data. In the end, we’ll run through some basic HDFS commands and see how to perform wordcount using MapReduce. Now, let us get started and understand Big Data in detail. Below topics are explained in this Big Data presentation for beginners: 1. Evolution of Big Data 2. Why Big Data? 3. What is Big Data? 4. Challenges of Big Data 5. Hadoop as a solution 6. MapReduce algorithm 7. Demo on HDFS and MapReduce What is this Big Data Hadoop training course about? The Big Data Hadoop and Spark developer course have been designed to impart in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab. What are the course objectives? This course will enable you to: 1. Understand the different components of the Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark 2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management 3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts 4. Get an overview of Sqoop and Flume and describe how to ingest data using them 5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning 6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution 7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations 8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS 9. Gain a working knowledge of Pig and its components 10. Do functional programming in Spark 11. Understand resilient distribution datasets (RDD) in detail 12. Implement and build Spark applications 13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques 14. Understand the common use-cases of Spark and the various interactive algorithms 15. Learn Spark SQL, creating, transforming, and querying Data frames Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training

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Transforming Enterprise IT - Virtual Transformation Day Feb 2019

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.

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In this session, we provide IT pros and application owners with an overview of AWS options for building hybrid storage architectures or even migrating an entire data center to the AWS Cloud. AWS Storage Gateway connects existing on-premises block, file, or tape storage systems to AWS Cloud storage over the WAN in a hybrid model. The AWS Snow family of physical devices can capture, pre-process, and migrate data into and out of AWS without any network connection. Join us to learn how you can close down data centers, reduce storage footprints, and build solutions for tiering, data lakes, backup, disaster recovery, and migration.

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Everyone has logs. They’re not the most exciting data that your systems generate, but often, they are the most useful. Across the board, we see customers using Amazon Elasticsearch Service (Amazon ES) to ingest, analyze, and search their log data. In this chalk talk, we discuss how to get your data into Amazon ES, and how to use Kibana to best effect to pull the information you need from the logs you’re generating.

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As you look to modernizing your applications, you will need to consider your database options to meet the new application requirements. AWS offers a series of purpose-built databases that include relational, key value, document, graph and cache use cases to help you deliver new and enhanced functionalities. In this webinar session, we share the different modern application architectures, and how to combine different database services to meet your requirements. Understand how to modernize your relational databases through easy upgrades with Amazon Relational Database Service and learn how to migrate from one database to another with AWS Database Migration Service and AWS Schema Conversion Tool. Speaker: Blair Layton, Business Development Manager, Amazon Web Services

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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

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!

Open banking as a service

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...

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...

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 Workloads

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.

Computer Vision con AWS

Database Oracle e VMware Cloud on AWS i miti da sfatare

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 NodeJS

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.

API moderne real-time per applicazioni mobili e web

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 sfatare

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.

Tools for building your MVP 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.

How to Build a Winning Pitch Deck

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.

Building a web application without servers

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.

Fundraising Essentials

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...

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.

Introduzione a Amazon Elastic Container Service