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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
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
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
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
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
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
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
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
By: Amazon Web Services     Published Date: Aug 23, 2018
AWS supports healthcare organizations with HIPAA Eligible Services and the AWS Healthcare Compliance program. AWS products and services are being used by many customers that handle electronic patient health information (PHI) to build solutions that meet HIPAA and HITRUST regulatory requirements for cloud-based workloads. In this webinar, you’ll learn how AWS HIPAA Eligible Services can help you build secure workloads to handle PHI in compliance with HIPAA and HITRUST standards. AWS Healthcare experts will be joined in this webinar by AWS Partner Network (APN) Partners ClearDATA and Cloudticity.
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     Amazon Web Services
By: Amazon Web Services     Published Date: Sep 05, 2018
Big data alone does not guarantee better business decisions. Often that data needs to be moved and transformed so Insight Platforms can discern useful business intelligence. To deliver those results faster than traditional Extract, Transform, and Load (ETL) technologies, use Matillion ETL for Amazon Redshift. This cloud- native ETL/ELT offering, built specifically for Amazon Redshift, simplifies the process of loading and transforming data and can help reduce your development time. This white paper will focus on approaches that can help you maximize your investment in Amazon Redshift. Learn how the scalable, cloud- native architecture and fast, secure integrations can benefit your organization, and discover ways this cost- effective solution is designed with cloud computing in mind. In addition, we will explore how Matillion ETL and Amazon Redshift make it possible for you to automate data transformation directly in the data warehouse to deliver analytics and business intelligence (BI
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     Amazon Web Services
By: Amazon Web Services     Published Date: Sep 05, 2018
Amazon Redshift Spectrum—a single service that can be used in conjunction with other Amazon services and products, as well as external tools—is revolutionizing the way data is stored and queried, allowing for more complex analyses and better decision making. Spectrum allows users to query very large datasets on S3 without having to load them into Amazon Redshift. This helps address the Scalability Dilemma—with Spectrum, data storage can keep growing on S3 and still be processed. By utilizing its own compute power and memory, Spectrum handles the hard work that would normally be done by Amazon Redshift. With this service, users can now scale to accommodate larger amounts of data than the cluster would have been capable of processing with its own resources.
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     Amazon Web Services
By: Amazon Web Services     Published Date: Sep 05, 2018
AbeBooks, with Amazon Redshift, has been able to upgrade to a comprehensive data warehouse with the enlistment of Matillion ETL for Amazon Redshift. In this case study, we share AbeBooks’ data warehouse success story.
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     Amazon Web Services
By: Amazon Web Services     Published Date: Sep 05, 2018
Today’s businesses generate staggering amounts of data, and learning to get the most value from that data is paramount to success. Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on-demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Amazon Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. Organizations choose Amazon Redshift for its affordability, flexibility, and powerful feature set: • Enterprise-class relational database query and management system • Supports client connections with many types of applications, including business intelligence (BI), reporting, data, and analytics tools • Execute analytic queries in order to retrieve, compare, and evaluate large amounts of data in multiple-stage operations
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     Amazon Web Services
By: Amazon Web Services     Published Date: Sep 05, 2018
Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. It’s designed for speed and ease of use — but to realize all of its potential benefits, organizations still have to configure Redshift for the demands of their particular applications. Whether you’ve been using Redshift for a while, have just implemented it, or are still evaluating it as one of many cloud-based data warehouse and business analytics technology options, your organization needs to understand how to configure it to ensure it delivers the right balance of performance, cost, and scalability for your particular usage scenarios. Since starting to work with this technolog
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     Amazon Web Services
By: Cylance     Published Date: Jul 02, 2018
Artificial intelligence (AI) seems to be on everyone’s mind. It powers natural language recognition within voice-powered assistants like Siri and Alexa, beats world-class Go players, and enables hyper-targeted e-commerce and content recommendations across the web, as we see with Amazon and Netflix. But recently, AI has begun actively expanding its footprint within the enterprise. Executives are trying to more fully comprehend what AI is and how they can use its insights into their data to better capitalize on business opportunities. This additional information can enable engaging with customers more productively and efficiently, forming an edge against the competition. Read more in our AI survey summary.
Tags : artificial, intelligence, enterprise
     Cylance
By: Hewlett Packard Enterprise     Published Date: Nov 06, 2017
The Cloud, once a radical idea in IT, is now mainstream. Whether it’s email, backup or file sharing, most consumers probably use a cloud service or two. Similarly, most IT professionals are familiar with cloud service providers such as Amazon, Google and Microsoft Azure, and many companies have moved at least some of their information technology processes into the cloud. In fact, the cloud has become so popular it’s easy to assume that running IT applications on-premises is not cost competitive with a cloud based service. In this report Evaluator Group will test the validity of that assumption with a TCO (Total Cost of Ownership) model analyzing a hyperconverged appliance solution from HPE and a comparable cloud service from Amazon Web Services (AWS).
Tags : infrastructure, cost competitive, cloud, hyper converged, amazon web services, total cost of ownership, tco
     Hewlett Packard Enterprise
By: Amazon Web Services     Published Date: Dec 15, 2017
Healthcare and Life Sciences organizations are using data to generate knowledge that helps them provide better patient care, enhances biopharma research and development, and streamlines operations across the product innovation and care delivery continuum. Next-Gen business intelligence (BI) solutions can help organizations reduce time-to-insight by aggregating and analyzing structured and unstructured data sets in real or near-real time. AWS and AWS Partner Network (APN) Partners offer technology solutions to help you gain data-driven insights to improve care, fuel innovation, and enhance business performance. In this webinar, you’ll hear from APN Partners Deloitte and hc1.com about their solutions, built on AWS, that enable Next-Gen BI in Healthcare and Life Sciences. Join this webinar to learn: How Healthcare and Life Sciences organizations are using cloud-based analytics to fuel innovation in patient care and biopharmaceutical product development. How AWS supports BI solutions f
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     Amazon Web Services
By: Amazon Web Services     Published Date: Sep 05, 2018
Big data alone does not guarantee better business decisions. Often that data needs to be moved and transformed so Insight Platforms can discern useful business intelligence. To deliver those results faster than traditional Extract, Transform, and Load (ETL) technologies, use Matillion ETL for Amazon Redshift. This cloud- native ETL/ELT offering, built specifically for Amazon Redshift, simplifies the process of loading and transforming data and can help reduce your development time. This white paper will focus on approaches that can help you maximize your investment in Amazon Redshift. Learn how the scalable, cloud- native architecture and fast, secure integrations can benefit your organization, and discover ways this cost- effective solution is designed with cloud computing in mind. In addition, we will explore how Matillion ETL and Amazon Redshift make it possible for you to automate data transformation directly in the data warehouse to deliver analytics and business intelligence (BI
Tags : 
     Amazon Web Services
By: Amazon Web Services     Published Date: Sep 05, 2018
Amazon Redshift Spectrum—a single service that can be used in conjunction with other Amazon services and products, as well as external tools—is revolutionizing the way data is stored and queried, allowing for more complex analyses and better decision making. Spectrum allows users to query very large datasets on S3 without having to load them into Amazon Redshift. This helps address the Scalability Dilemma—with Spectrum, data storage can keep growing on S3 and still be processed. By utilizing its own compute power and memory, Spectrum handles the hard work that would normally be done by Amazon Redshift. With this service, users can now scale to accommodate larger amounts of data than the cluster would have been capable of processing with its own resources.
Tags : 
     Amazon Web Services
By: Amazon Web Services     Published Date: Sep 05, 2018
AbeBooks, with Amazon Redshift, has been able to upgrade to a comprehensive data warehouse with the enlistment of Matillion ETL for Amazon Redshift. In this case study, we share AbeBooks’ data warehouse success story.
Tags : 
     Amazon Web Services
By: Dell EMC     Published Date: Aug 17, 2017
For many companies the appeal of the public cloud is very real. For tech startups, the cloud may be their only option, since many don’t have the capital or expertise to build and operate the IT systems their businesses need. Existing companies with established data centers are also looking at public clouds, to increase IT agility while limiting risk. The idea of building-out their production capacity while possibly reducing the costs attached to that infrastructure can be attractive. For most companies the cloud isn’t an “either-or” decision, but an operating model to be evaluated along with on-site infrastructure. And like most infrastructure decisions the question of cost is certainly a consideration. In this report we’ll explore that question, comparing the cost of an on-site hyperconverged solution with a comparable set up in the cloud. The on-site infrastructure is a Dell EMC VxRailTM hyperconverged appliance cluster and the cloud solution is Amazon Web Services (AWS).
Tags : public cloud, it systems, data center, it agility, hyperconverged solution, hyperconverged appliance
     Dell EMC
By: Alert Logic     Published Date: Sep 03, 2014
As more organizations consider a move to the cloud, security remains a top concern. Learn how Alert Logic’s suite of security solutions are designed to provide infrastructure and application security and compliance through a cloud-native model that takes advantage of the AWS business model and elastic scaling capabilities.
Tags : alert logic, amazon web security solutions, aws business model, security
     Alert Logic
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
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
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
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