storage analytics

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Published By: Infinidat EMEA     Published Date: Oct 10, 2019
I Big Data e gli analytics workloads sono la nuova frontiera per le aziende. I dati vengono raccolti da fonti che non esistevano 10 anni fa. Tutti i dati dei telefoni cellulari, i dati generati dalle macchine e i dati relativi all’interazione con i siti vengono raccolti e analizzati. Inoltre, con i budget IT sempre più sotto pressione, l’impatto ambientale dei Big Data non fa che aumentare e pone grandi sfi de per i sistemi storage. Questo documento fornisce informazioni sulle problematiche che le applicazioni dei Big Data pongono sullo storage e su come scegliere le più corrette infrastrutture per ottimizzare e consolidare le applicazioni dei Big Data e degli analytics, senza prosciugare le fi nanze.
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Infinidat EMEA
Published By: Pure Storage     Published Date: Jul 03, 2019
Apache® Spark™ has become a vital technology for development teams looking to leverage an ultrafast in-memory data engine for big data analytics. Spark is a flexible open-source platform, letting developers write applications in Java, Scala, Python or R. With Spark, development teams can accelerate analytics applications by orders of magnitude.
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Pure Storage
Published By: Pure Storage     Published Date: Jul 03, 2019
Deep learning opens up new worlds of possibility in artifi cial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Advanced AI applications require a modern all-fl ash storage infrastructure that is built specifi cally to work with high-powered analytics.
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Pure Storage
Published By: Pure Storage     Published Date: Jul 03, 2019
Deep learning opens up new worlds of possibility in artificial intelligence within the Financial Services industry, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Advanced AI applications require a modern all-flash storage infrastructure that is built specifically to work with high-powered analytics.
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Pure Storage
Published By: Infinidat EMEA     Published Date: May 14, 2019
Big Data and analytics workloads represent a new frontier for organizations. Data is being collected from sources that did not exist 10 years ago. Mobile phone data, machine-generated data, and website interaction data are all being collected and analyzed. In addition, as IT budgets are already under pressure, Big Data footprints are getting larger and posing a huge storage challenge. This paper provides information on the issues that Big Data applications pose for storage systems and how choosing the correct storage infrastructure can streamline and consolidate Big Data and analytics applications without breaking the bank.
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Infinidat EMEA
Published By: Hewlett Packard Enterprise     Published Date: May 10, 2019
Nimble Secondary Flash array represents a new type of data storage, designed to maximize both capacity and performance. By adding high-performance flash storage to a capacity-optimized architecture, it provides a unique backup platform that lets you put your backup data to work. Nimble Secondary Flash array uses flash performance to provide both near-instant backup and recovery from any primary storage system. It is a single device for backup, disaster recovery, and even local archiving. By using flash, you can accomplish real work such as dev/test, QA, and analytics. Deep integration with Veeam’s leading backup software simplifies data lifecycle management and provides a path to cloud archiving.
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: May 10, 2019
Applications are the engines that drive today’s digital businesses. When the infrastructure that powers those applications is difficult to administer, or fails, businesses and their IT organizations are severely impacted. Traditionally, IT assumed much of the responsibility to ensure availability and performance. In the digital era, however, the industry needs to evolve and reset the requirements on vendors. HPE Nimble Storage has broken away from convention and transformed how storage is managed and supported with the HPE InfoSight predictive analytics platform. HPE engaged ESG to conduct a quantitative survey of the HPE Nimble Storage installed base, as well as non-HPE Nimble Storage customers, to better assess how HPE InfoSight positively impacts customer environments. To find out more download this whitepaper today.
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Hewlett Packard Enterprise
Published By: Pure Storage     Published Date: Apr 10, 2019
Deep learning opens up new worlds of possibility in artificial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Advanced AI applications require a modern all-flash storage infrastructure that is built specifically to work with high-powered analytics.
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Pure Storage
Published By: Pure Storage     Published Date: Apr 10, 2019
Pure Storage, a pioneer in block-based flash arrays, has developed a technology called FlashBlade, designed specifically for file and object storage environments. With FlashBlade, IT teams now have a simple-to-manage shared storage solution that delivers the performance and capacity needed to bring Spark deployments on premise. To help gain a deeper understanding of the storage challenges related to Spark and how FlashBlade addresses them, Brian Gold of Pure Storage sat down with veteran technology journalist Al Perlman of TechTarget for a far-reaching discussion on Spark trends and opportunities.
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Pure Storage
Published By: Pure Storage     Published Date: Apr 10, 2019
Deep learning opens up new worlds of possibility in artificial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly, and legacy storage systems are not keeping up. Advanced AI applications require a modern all-flash storage infrastructure that is built specifically to work with high-powered analytics.
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Pure Storage
Published By: Oracle     Published Date: Jan 28, 2019
For more than a decade, Oracle has developed and enhanced its ZFS Storage Appliance, giving its users a formidable unified and enterprise-grade storage offering. The latest release, ZS7-2, boasts upgraded hardware and software and is a timely reminder that more users might do well to evaluate this offering. It has a trifecta of advantages: (1) It’s notable performance, price-performance, and flexibility are all improved in this new release (2) There is a surprisingly inclusive set of functionalities, including excellent storage analytics that were developed even before analytics became a contemporary “must-have” (3) There’s a compelling group of “better together” elements that make ZFS Storage Appliance a particularly attractive choice for both Oracle Database environments and users that want to seamlessly integrate a cloud component into their IT infrastructure. Given the proven abilities of Oracle’s prior models, it’s also safe to assume that the new ZS7-2 will outperform other m
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Oracle
Published By: Pure Storage     Published Date: Dec 05, 2018
Deep learning opens up new worlds of possibility in artificial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Read this MIT Technology Review custom paper to learn how advanced AI applications require a modern all-flash storage infrastructure that is built specifically to work with high-powered analytics, helping to accelerate business outcomes for data driven organizations.
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Pure Storage
Published By: Pure Storage     Published Date: Dec 05, 2018
Data is the new currency. Is your organization capitalizing on the full potential of data analytics? In this big data primer, you will learn about the 3 key challenges facing organizations today: managing overwhelming amounts of data, leveraging new complex tools/technologies, and developing the necessary skills and infrastructure. And since storage is where your organization's data lives, it’s a pivotal part of the infrastructure jigsaw puzzle. Thus with a “tuned for everything” storage solution that is purpose-built for modern analytics, you can confidently harness the power of your data to drive your enterprise forward.
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Pure Storage
Published By: Dell EMC Storage     Published Date: Nov 28, 2018
Powerful data protection in a converged appliance that is easy to deploy and manage — at the lowest cost-to-protect. The integrated appliance brings together protection storage and software, search, and analytics — plus simplified system management and cloud readiness. And, the IDPA System Manager, with its clean, intuitive interface, provides a comprehensive view of data protection infrastructure from a single dashboard.
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Dell EMC Storage
Published By: AWS     Published Date: Oct 26, 2018
Today’s organisations are tasked with analysing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organisations are finding that in order to deliver analytic insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is an architectural approach that allows you to store enormous amounts of data in a central location, so it’s readily available to be categorised, processed, analysed, and consumed by diverse groups within an organisation? Since data—structured and unstructured—can be stored as-is, there’s 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.
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data, lake, amazon, web, services, aws
    
AWS
Published By: Pure Storage     Published Date: Oct 09, 2018
Apache® Spark™ has become a vital technology for development teams looking to leverage an ultrafast in-memory data engine for big data analytics. Spark is a flexible open-source platform, letting developers write applications in Java, Scala, Python or R. With Spark, development teams can accelerate analytics applications by orders of magnitude
Tags : 
    
Pure Storage
Published By: Cohesity     Published Date: Oct 02, 2018
The University of California, Santa Barbara (UCSB) is a public research university and one of the 10 campuses of the University of California system. Its secondary storage was a combination of multiple point solutions. The UI/setup and maintenance was complex. Maintaining multiple licensing and maintenance agreements negatively impacted the administrative cost. The skyrocketing cost for additional backup capacity limited the team’s ability to expand their backup protection to many critical systems. With Cohesity's unified hyperconverged secondary storage platform, the IT team provided a single solution for all 13 departments to consolidate their backups on one platform, and scale-out as required. Read the case study and get details on how UCSB consolidated everything from backup to recovery, analytics to monitoring and alerting.
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case, study, ucsb, consolidates, data, protection, cohesity, hyperconverged
    
Cohesity
Published By: TIBCO Software     Published Date: Sep 21, 2018
BUSINESS CHALLENGE “Vestas is a global market leader in manufacturing and servicing wind turbines,” explains Sven Jesper Knudsen, Ph.D., senior data scientist. “Turbines provide a lot of data, and we analyze that data, adapt to changing needs, and work to create a best-in-class wind energy solution that provides the lowest cost of energy. “To stay ahead, we have created huge stacks of technologies—massive amounts of data storage and technologies to transform data with analytics. That comes at a cost. It requires maintenance and highly skilled personnel, and we simply couldn’t keep up. The market had matured, and to stay ahead we needed a new platform. “If we couldn’t deliver on time, we would let users and the whole business down, and start to lose a lot of money on service. For example, if we couldn’t deliver a risk report on time, decisions would be made without actually understanding the risk landscape.
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data solution, technology solution, data science, streaming data, fast data platform, self-service analytics
    
TIBCO Software
Published By: Hewlett Packard Enterprise     Published Date: Aug 23, 2018
Learn how predictive analytics and machine learning can help optimize application performance and meet the needs of the business with Nimble Storage Infosight. This ESG report highlights: • Optimal application performance and delivery is difficult to achieve in complex environments. • Many IT infrastructure and operations teams are stretched to the breaking point. • Predictive analytics and machine learning can be applied to great effect.
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: Aug 23, 2018
Nimble Storage: Redefining the standard for system availability - How Nimble Storage uses predictive analytics to achieve more than six nines availability across its entire installed base.
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: Aug 23, 2018
HPE Nimble Storage has broken away from convention and transformed how storage is managed and supported with the HPE InfoSight predictive analytics platform. HPE engaged ESG to conduct a quantitative survey of the HPE Nimble Storage installed base, as well as non-HPE Nimble Storage customers, to better assess how HPE InfoSight positively impacts customer environments. Both HPE InfoSight telemetry data and ESG’s quantitative survey data show that the benefit delivered to HPE Nimble Storage customers is significant, driving: • 79% lower IT operational expenses. • 73% fewer trouble tickets in the environment, which are resolved faster. • 85% less time spent resolving storage-related trouble tickets. • 69% faster time to resolution for events that necessitate level 3 support. • The ability to manage and troubleshoot the entire infrastructure environment from a single, intelligent platform.
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: Aug 23, 2018
"This research by Nimble Storage, a Hewlett Packard Enterprise Company, outlines the top five causes of application delays. The report analyzes more than 12,000 anonymized cases of downtime and slow performance. Read this report and find out: -Top 5 causes of downtime and poor performance across the infrastructure stack -How machine learning and predictive analytics can prevent issues -Steps you can take to boost performance and availability
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Hewlett Packard Enterprise
Published By: TIBCO Software     Published Date: Aug 15, 2018
Expanding analytic capabilities are critical to digitizing the business, optimizing costs, accelerating innovation, and surviving digital disruption Historically, manufacturers were almost solely focused on reducing costs by applying automation and analytics to engineering, R&D, manufacturing operations, and quality organizations. Even though the strategies used within these areas are still needed, they are not sufficient to ensure business survival and continuity in the age of Industry 4.0 and the IoT. Today, it is paramount that smart manufacturers broaden their scope because disruptive innovations in data acquisition, storage, and analytics technology have enabled an entirely new degree of automation and virtualization, promising a complete 360-degree high-fidelity virtual data-driven integrated views of all operations—from suppliers and supply chains, through equipment, processes, and manufacturing practices, to final product testing and customer satisfaction. Download this paper
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TIBCO Software
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
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