amazon web services

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Published By: Amazon Web Services     Published Date: Jan 23, 2018
SAP® customers who have long envied the many operational and cost benefts promised by cloud computing can now confdently pursue “cloud-frst” strategies. Companies that have made this move in collaboration with a leading company like Amazon Web Services (AWS) aren’t looking back. No longer bound by the constraints and overhead of legacy infrastructure, they’re pursuing new ways in which AWS-based SAP deployments can further their strategic goals and increase their competitiveness. Provided by: AWS & Intel
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sap, customers, aws, cloud, organizations, applications
    
Amazon Web Services
Published By: Amazon Web Services     Published Date: Feb 01, 2018
At Amazon, we’ve been investing deeply in AI for more than 20 years. Machine learning (ML) algorithms drive many of our internal systems, and have formed the core of our customers' experience —from the path optimization in our fulfillment centers, and Amazon.com’s recommendations engine, to Echo powered by Alexa, and our new retail experience, Amazon Go. Our mission is to share our learnings and ML capabilities as fully managed services, and put them into the hands of every executive, developer, and data scientist.
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machine learning, algorithms, interal systems, amazon
    
Amazon Web Services
Published By: Amazon Web Services     Published Date: Feb 01, 2018
Machine learning is proving its power across virtually every industry in ways that add actionable insight and efficiency. But one can look at the rise of this transformative paradigm with a more focused lens to see AI technologies as a business tool of the highest order, one that improves processes and inspires new models. AI, in other words, has a big role to play on the balance sheet. Two leading brands in very different spaces — Capital One in financial services, John Deere in agriculture — are seeing efforts that stretch back decades come to fruition with the launch of cloud-based AI platforms. Capital One is developing digital products and experiences using machine learning to help millions of customers with their financial lives; John Deere’s Precision Agriculture solution helps farmers gain precise information about their machines and crops. In both instances, AI and a cloud platform combine to enable transformation.
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digital, technologies, optimization, amazon
    
Amazon Web Services
Published By: Amazon Web Services     Published Date: Feb 01, 2018
Moving Beyond Traditional Decision Support Future-proofing a business has never been more challenging. Customer preferences turn on a dime, and their expectations for service and support continue to rise. At the same time, the data lifeblood that flows through a typical organization is more vast, diverse, and complex than ever before. More companies today are looking to expand beyond traditional means of decision support, and are exploring how AI can help them find and manage the “unknown unknowns” in our fast-paced business environment.
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predictive, analytics, data lake, infrastructure, natural language processing, amazon
    
Amazon Web Services
Published By: Amazon Web Services     Published Date: Apr 16, 2018
Migrating mission-critical workloads like SAP to the cloud is a vital part of any digital transformation. However, it’s now become a matter of “when,” rather than “if.” When deciding on a cloud provider, Business and IT executives are under pressure to find a solution that enables reduced costs, greater agility, and above all, the ability to innovate core business processes. But how do you execute this migration without risking downtime and productivity loss? Download our eBook on Migrating your SAP environment to AWS
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Apr 16, 2018
Since SAP introduced its in-memory database, SAP HANA, customers have significantly accelerated everything from their core business operations to big data analytics. But capitalizing on SAP HANA’s full potential requires computational power and memory capacity beyond the capabilities of many existing data center platforms. To ensure that deployments in the AWS Cloud could meet the most stringent SAP HANA demands, AWS collaborated with SAP and Intel to deliver the Amazon EC2 X1 and X1e instances, part of the Amazon EC2 Memory-Optimized instance family. With four Intel® Xeon® E7 8880 v3 processors (which can power 128 virtual CPUs), X1 offers more memory than any other SAP-certified cloud native instance available today.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Apr 16, 2018
How to be a Super Hero in the Cloud
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Apr 16, 2018
SAP and Amazon Web Services (AWS) have jointly developed a cloud-migration test program, Fast Amazon SAP Transformation (FAST), that helps you address time- and cost-related uncertainties when migrating HANA to the AWS cloud. This analyst report from Ovum explores how FAST (a four-step testing process) drastically reduces uncertainties about the time and costs involved in your HANA cloud migration. Download the report now and you’ll discover how FAST can help you: -Quickly quantify costs, risks, and time for migrating SAP ERP applications to the AWS Cloud. -Run your mission-critical applications faster and more reliably Migrate your SAP HANA database to the cloud in only a few days with minimal infrastructure cost Read the Report
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Apr 16, 2018
New and existing SAP customers can confidently deploy their mission-critical workloads on AWS knowing that AWS and SAP have worked closely to test and certify that the AWS Cloud meets the stringent performance and availability needs of SAP workloads. Hundreds of enterprise SAP customers run SAP solutions on AWS and are achieving increased flexibility, performance, and security, while simultaneously cutting their costs by migrating to AWS. Download our whitepaper: Leveraging the Cloud for Speed, Agility and ROI.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Apr 27, 2018
One of the value propositions of an Internet of Things (IoT) strategy is the ability to provide insight that was previously invisible to the business. But before a business can develop a strategy for IoT, it needs a platform that meets the foundational principles of an IoT solution. Amazon Web Services (AWS) believes in some basic freedoms that are driving organizational and economic benefits of the cloud into businesses. These freedoms are why more than a million customers already use the AWS platform to support virtually any cloud workload. These freedoms are also why AWS is proving itself as the primary catalyst to any Internet of Things strategy across commercial, consumer, and industrial solutions. This paper outlines core tenets that should be considered when developing an IoT strategy, the benefits of AWS in that strategy and how the AWS cloud platform can be the critical component supporting those core tenets.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Apr 28, 2018
Les technologies d'intelligence artificielle telles que l'apprentissage machine et le Deep Learning permettent d'obtenir des informations et de la précision à deux marques majeures dans des secteurs très différents : la santé et les assurances. Des théories sur les futures incidences de l'intelligence artificielle (IA) sur les entreprises et la société vont florissantes. Mais la réalité du terrain aujourd'hui pour les entreprises et les dirigeants appliquant des technologies comme l'apprentissage machine et l'apprentissage profond à leurs enjeux majeurs est déjà très enthousiasmante. Les modèles de fonctionnement sont refondés en se basant sur les informations obtenues de puissantes capacités cognitives. De nouveaux produits et services améliorent l'expérience client, voire la condition humaine. D'une façon très concrète et significative, l'IA change le monde pour le meilleur.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Apr 28, 2018
AI-Technologien wie Machine Learning und Deep Learning liefern zwei großen Marken in zwei sehr unterschiedlichen Branchen – Gesundheit und Versicherungen – Insights und Genauigkeit. Theorien zu den zukünftigen Auswirkungen künstlicher Intelligenz (AI) auf die Geschäftswelt und die Gesellschaft sind allgegenwärtig. Aber die Realität, wie Unternehmen sie kennen, die Technologien wie Machine Learning und Deep Learning anwenden, ist schon aufregend genug. Geschäftsmodelle werden anhand der Insights umgestaltet, die durch die leistungsstarken kognitiven Funktionen generiert werden. Neue Produkte und Dienstleistungen verbessern das Benutzererlebnis – um nicht zu sagen die menschliche Existenz. Auf sehr reale und bedeutsame Weise verbessert AI die Welt.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
What is a Data Lake? Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. Data Lakes are a new and increasingly popular way to store and analyze data that addresses many of these challenges. A Data Lakes allows an organization to store all of their data, structured and unstructured, in one, centralized repository. Since data can be stored as-is, there is no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand. Download to find out more now.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
Organizations are collecting and analyzing increasing amounts of data making it difficult for traditional on-premises solutions for data storage, data management, and analytics to keep pace. Amazon S3 and Amazon Glacier provide an ideal storage solution for data lakes. They provide options such as a breadth and depth of integration with traditional big data analytics tools as well as innovative query-in-place analytics tools that help you eliminate costly and complex extract, transform, and load processes. This guide explains each of these options and provides best practices for building your Amazon S3-based data lake.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
As easy as it is to get swept up by the hype surrounding big data, it’s just as easy for organizations to become discouraged by the challenges they encounter while implementing a big data initiative. Concerns regarding big data skill sets (and the lack thereof), security, the unpredictability of data, unsustainable costs, and the need to make a business case can bring a big data initiative to a screeching halt. However, given big data’s power to transform business, it’s critical that organizations overcome these challenges and realize the value of big data. Download now to find out more.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
IDC’s research has shown the movement of most IT workloads to the cloud in the coming years. Yet, with all the talk about enterprises moving to the cloud, some of them still wonder if such a move is really cost effective and what business benefits may result. While the answers to such questions vary from workload to workload, one area attracting particular attention is that of the data warehouse. Many enterprises have substantial investments in data warehousing, with an ongoing cost to managing that resource in terms of software licensing, maintenance fees, operational costs, and hardware. Can it make sense to move to a cloud-based alternative? What are the costs and benefits? How soon can such a move pay itself off? Download now to find out more.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
Defining the Data Lake “Big data” is an idea as much as a particular methodology or technology, yet it’s an idea that is enabling powerful insights, faster and better decisions, and even business transformations across many industries. In general, big data can be characterized as an approach to extracting insights from very large quantities of structured and unstructured data from varied sources at a speed that is immediate (enough) for the particular analytics use case.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
Die Recherchen von IDC haben ergeben, dass in den nächsten Jahren die meisten IT-Workloads in die Cloud verschoben werden. Doch neben all den positiven Berichten über Unternehmen, die in die Cloud umziehen, gibt es auch Unternehmen, die sich noch immer fragen, ob ein solcher Wechsel wirklich kosteneffizient ist und welche Vorteile sich aus einem solchen ergeben. Während die Antworten auf solche Fragen von Workload zu Workload variieren, gibt es ein Element, das besondere Aufmerksamkeit auf sich zieht: das Data-Warehouse.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
Organisationen müssen heute mit immer größeren Datenmengen zurechtkommen, die aus mehr Datenquellen stammen und mehr Datentypen enthalten als jemals zuvor. Angesichts massiver, heterogener Datenmengen stellen viele Organisationen fest, dass sie eine Datenspeicher- und Analyselösung benötigen, die höhere Geschwindigkeit und mehr Flexibilität als ältere Systeme bietet, um rechtzeitig geschäftliche Erkenntnisse liefern zu können. Ein Data Lake ist eine neue und zunehmend populäre Möglichkeit zur Speicherung und Analyse von Daten, die viele dieser Herausforderungen meistert, indem sie es einer Organisation ermöglicht, alle Daten in einem zentralen Repository zu speichern. Da Daten in ihrem ursprünglichen Format gespeichert werden können, besteht kein Bedarf, sie vor der Übernahme in ein vordefiniertes Schema zu konvertieren, wodurch Sie die Möglichkeit erhalten, all Ihre Daten, sowohl strukturiert als auch unstrukturiert, mit minimaler Vorlaufzeit zu speichern.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
Qu'est-ce qu'un lac de données ? Les organisations doivent gérer de plus grands volumes de données, provenant de davantage de sources et contenant plus de types de données que jamais auparavant. Confrontées à des volumes massifs et hétérogènes de données, de nombreuses organisations ont compris que pour proposer des informations stratégiques pour l'entreprise en temps opportun, elles doivent disposer d'une solution d'analyse et de stockage des données qui offre plus de vitesse et de souplesse que les systèmes traditionnels. Un lac de données représente une solution nouvelle et de plus en plus répandue pour stocker et analyser les données. Cette solution relève la plupart de ces défis en permettant à une organisation de stocker l'ensemble de ses données au sein d'un même référentiel centralisé. Comme les données peuvent être stockées sous leur forme initiale, il n'est pas nécessaire de les convertir en un schéma prédéfini avant leur ingestion.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
Il est tout aussi facile d'être submergé par l'omniprésent Big Data qu'il l'est pour les organisations d'être découragées par les défis qu'elles rencontrent lorsqu'elles implémentent une initiative en matière de Big Data. Les préoccupations liées aux ensembles de compétences associées au Big Data (et à leur absence), à la sécurité, à l'imprévisibilité des données, aux coûts non viables et à la nécessité d'effectuer une analyse de rentabilité peuvent mettre brutalement fin à une initiative en matière de Big Data.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
La plupart des entreprises ont investi considérablement dans le stockage de leurs données, avec un coût de gestion continu en termes de licences logicielles, frais de maintenance, coûts opérationnels et matériel. Est-il plus judicieux d'opter pour une solution cloud ? Quels en sont les coûts et les avantages ? En combien de temps un tel choix est-il rentabilisé? Découvrez, dans ce document, la synthèse de l’enquête IDC sur le retour d'expérience de 8 entreprises utilisant Amazon Redshift.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Apr 11, 2018
Elastic Load Balancing distributes incoming application traffic across multiple EC2 instances, in multiple geographic areas. This increases the fault tolerance of your applications. Load Balancing
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Apr 11, 2018
It’s important to provide effective inbound and outbound network traffic control to distinguish between legitimate and illegitimate requests. Effectively managing, monitoring, controlling, and filtering network traffic are key actions that can help do so and further enable a robust cloud security infrastructure. Filtering Cloud Network Traffic and Preventing Threats
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Apr 11, 2018
Connecting your VPC and corporate data helps make the AWS Cloud a valuable extension of your data center. Using IPsec AWS managed VPN connections and secure gateways provides secure access to seamlessly connect to AWS hosted resources just like any other internally facing resource.
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Amazon Web Services
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