data organization

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By: NetApp     Published Date: -
Enterprise data is growing rapidly - reaching multiple petabytes of data or even billions of files for many organizations. To maximize the business value of this data, enterprises need a storage infrastructure to store, manage, and retrieve a massive amount of data. This ebook shows you how to address large content repository challenges with object storage. You'll learn how to effectively address long-term retention policies, find and retrieve content quickly from long-term repositories and using object storage efficiently.
Tags : object storage, storage infrastructure
     NetApp
By: NetApp     Published Date: Dec 13, 2013
Despite the hype, Big Data has introduced critical challenges for modern organizations – and unprepared organizations risk getting buried beneath an avalanche of information. In this informative webcast, join industry and business intelligence (BI) expert Wayne Eckerson, as he tackles the challenges of Big Data. Uncover practical tips and tactics for driving value with your Big Data platform – watch now to learn more.
Tags : big data problems, how to get the most from your big data
     NetApp
By: NetApp     Published Date: Dec 14, 2013
Read how the NetApp Distributed Content Repository Solution is an efficient and risk-reducing active archive solution. Based on customer data, Forrester created a composite organization and concluded that the NetApp Distributed Content Repository delivered a three year ROI of 47% with a payback period of 1.3 months. The key benefits are reduced risk of losing unregulated archived data, denser storage, storage solution efficiency, and compliance for regulated data. The study also provides readers with a framework to do their own financial impact evaluation. Source: The Total Economic Impact Of The NetApp Distributed Content Repository Solution (StorageGRID On E-Series), a commissioned study conducted by Forrester Consulting on behalf of NetApp, March 2013.
Tags : forrester tei
     NetApp
By: IBM     Published Date: Sep 02, 2014
Whether in high-performance computing, Big Data or analytics, information technology has become an essential tool in today’s hyper-competitive business landscape. Organizations are increasingly being challenged to do more with less and this is fundamentally impacting the way that IT infrastructure is deployed and managed. In this short e-book, learn the top ten ways that IBM Platform Computing customers are using technologies like IBM Platform LSF and IBM Platform Symphony to help obtain results faster, share resources more efficiently, and improve the overall cost-effectiveness of their global IT infrastructure.
Tags : ibm, ibm platform computing, save money
     IBM
By: IBM     Published Date: May 20, 2015
Whether in high-performance computing, Big Data or analytics, information technology has become an essential tool in today’s hyper-competitive business landscape. Organizations are increasingly being challenged to do more with less and this is fundamentally impacting the way that IT infrastructure is deployed and managed. In this short e-book, learn the top ten ways that IBM Platform Computing customers are using technologies like IBM Platform LSF and IBM Platform Symphony to help obtain results faster, share resources more efficiently, and improve the overall cost-effectiveness of their global IT infrastructure.
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     IBM
By: IBM     Published Date: May 20, 2015
There is a lot of hype around the potential of big data and organizations are hoping to achieve new innovations in products and services with big data and analytics driving more concrete insights about their customers and their own business operations. To meet these challenges, IBM has introduced IBM® Spectrum Scale™. The new IBM Spectrum Scale storage platform has grown from GPFS, which entered the market in 1998. Clearly, IBM has put significant development into developing this mature platform. Spectrum Scale addresses the key requirements of big data storage - extreme scalability for growth, reduced overhead of data movement, easy accessibility , geographic location independence and advanced storage functionality. Read the paper to learn more!
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     IBM
By: IBM     Published Date: Sep 16, 2015
6 criteria for evaluating a high-performance cloud services providers Engineering, scientific, analytics, big data and research workloads place extraordinary demands on technical and high-performance computing (HPC) infrastructure. Supporting these workloads can be especially challenging for organizations that have unpredictable spikes in resource demand, or need access to additional compute or storage resources for a project or to support a growing business. Software Defined Infrastructure (SDI) enables organizations to deliver HPC services in the most efficient way possible, optimizing resource utilization to accelerate time to results and reduce costs. SDI is the foundation for a fully integrated environment, optimizing compute, storage and networking infrastructure to quickly adapt to changing business requirements, and dynamically managing workloads and data, transforming a s
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     IBM
By: IBM     Published Date: Sep 16, 2015
A fast, simple, scalable and complete storage solution for today’s data-intensive enterprise IBM Spectrum Scale is used extensively across industries worldwide. Spectrum Scale simplifies data management with integrated tools designed to help organizations manage petabytes of data and billions of files—as well as control the cost of managing these ever-growing data volumes.
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     IBM
By: Storiant     Published Date: Mar 16, 2015
Read this new IDC Report about how today's enterprise datacenters are dealing with new challenges that are far more demanding than ever before. Foremost is the exponential growth of data, most of it unstructured data. Big data and analytics implementations are also quickly becoming a strategic priority in many enterprises, demanding online access to more data, which is retained for longer periods of time. Legacy storage solutions with fixed design characteristics and a cost structure that doesn't scale are proving to be ill-suited for these new needs. This Technology Spotlight examines the issues that are driving organizations to replace older archive and backup-and-restore systems with business continuity and always-available solutions that can scale to handle extreme data growth while leveraging a cloudbased pricing model. The report also looks at the role of Storiant and its long-term storage services solution in the strategically important long-term storage market.
Tags : storiant, big data, analytics implementations, cloudbased pricing model, long-term storage services solution, long-term storage market
     Storiant
By: RedPoint     Published Date: Nov 10, 2014
Adoption of Hadoop by data-driven organizations is exploding. Hadoop’s potential cost effectiveness and facility for accepting unstructured data is making it central to modern, “Big Data” architectures. The advancements in Hadoop 2.0 increase the technology’s promise to an even greater extent. But with these opportunities also come challenges and adoption hurdles that make getting the most out of Hadoop easier said than done. Read on as we review some Hadoop basics, highlight some of the adoption challenges that exist and explain how RedPoint Data Management for Hadoop helps organizations accelerate their work with Hadoop.
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     RedPoint
By: EMC     Published Date: Jun 13, 2016
A Data Lake can meet the storage needs of your Modern Data Center. Check out the Top 10 Reasons your organization should adopt scale-out data lake storage for Hadoop Analytics on EMC Isilon.
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     EMC
By: IBM     Published Date: Sep 04, 2013
This white paper outline the vale of the big data that continues to accumulate within your organization. It show how by making this data more accessible to relevant stakeholders you can unlock the value and insights, while minimizing risk.
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     IBM
By: IBM     Published Date: Feb 13, 2015
In the age of "big data," it's essential for any organization to know how to analyze and manage their ever increasing stores of information. Packed with everything you need to know about Hadoop analytics, this handy guide provides you with a solid understanding of the critical big data concepts and trends, and suggests ways for you to revolutionize your business operations through the implementation of cost-effective, high performance Hadoop technology.
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     IBM
By: Intel     Published Date: Aug 06, 2014
Around the world and across all industries, high-performance computing is being used to solve today’s most important and demanding problems. More than ever, storage solutions that deliver high sustained throughput are vital for powering HPC and Big Data workloads. Intel® Enterprise Edition for Lustre* software unleashes the performance and scalability of the Lustre parallel file system for enterprises and organizations, both large and small. It allows users and workloads that need large scale, high- bandwidth storage to tap into the power and scalability of Lustre, but with the simplified installation, configuration, and monitoring features of Intel® Manager for Lustre* software, a management solution purpose-built for the Lustre file system.Intel ® Enterprise Edition for Lustre* software includes proven support from the Lustre experts at Intel, including worldwide 24x7 technical support. *Other names and brands may be claimed as the property of others.
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     Intel
By: Dell and Intel®     Published Date: Sep 17, 2014
According to the 2014 IDG Enterprise Big Data research report, companies are intensifying their efforts to derive value through big data initiatives with nearly half (49%) of respondents already implementing big data projects or in the process of doing so in the future. Further, organizations are seeing exponential growth in the amount of data managed with an expected increas of 76% within the next 12-18 months. With growth there are opportunities as well as challenges. Among those facing the big data challenge are finance executives, as this extraordinary growth presents a unique opportunity to leverage data assets like never before. * Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and/or other countries.
Tags : dell and intel, big data for finance
     Dell and Intel®
By: Dell and Intel®     Published Date: Aug 24, 2015
Many enterprises are embracing Hadoop because of the unique business benefits it provides. But, until now, this rapidly evolving big data technology hadn’t always met enterprise security needs. In order to protect big data today, organizations must have solutions that address four key areas: authentication, authorization, audit and lineage, and compliant data protection.
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     Dell and Intel®
By: Dell and Intel®     Published Date: Aug 24, 2015
Business need: Merkle needed a scalable, cost-effective way to capture and analyze large amounts of structured and unstructured consumer data for use in developing better marketing campaigns for clients. Solution: The company deployed a Dell and HadoopTM cluster based on Dell and Intel® technologies to support a new big data insight solution that gives clients a unified view of customer data. Benefits: [bullets for the below points] • Partnership with Dell and Intel® leads to new big data solution • Cluster supports the Foundational Marketing Platform, a new data insight solution • Merkle can find patterns in big data and create analytical models that anticipate consumer behavior • Organization cuts costs by 60 percent and boosts processing speeds by 10 times • Solution provides scalability and enables innovation
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     Dell and Intel®
By: Dell and Intel®     Published Date: Aug 24, 2015
In today’s digitally driven world, the success of a business is increasingly tied to its ability to extract value from data. Exploiting the untapped value of your data is now the pathway to success. By putting data-driven decision making at the heart of the business, your organization can harness a wealth of information to gain an unparalleled competitive advantage. In a future-ready enterprise, you must make a fundamental shift from a focus on technology to a strategic business focus. Data-driven insights can guide everything from the formulation of top-level corporate strategies to connected devices that monitor and enable immediate critical decisions, to the creation of personalized customer interactions. Data is the foundation for enabling business transformation and innovation.
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     Dell and Intel®
By: Dell and Intel®     Published Date: Aug 24, 2015
Organizations working at gathering insights from vast volumes of varied data types understand that they need more than traditional, structured systems, and tools. This paper discusses how the many Dell | Cloudera Hadoop solutions help organizations of all sizes, and with a variety of needs and use cases, tackle their big data requirements.
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     Dell and Intel®
By: Dell and Intel®     Published Date: Aug 24, 2015
To extract value from an ever-growing onslaught of data, your organization needs next-generation data management, integration, storage and processing systems that allow you to collect, manage, store and analyze data quickly, efficiently and cost-effectively. That’s the case with Dell| Cloudera® Apache™ Hadoop® solutions for big data. These solutions provide end-to-end scalable infrastructure, leveraging open source technologies, to allow you to simultaneously store and process large datasets in a distributed environment for data mining and analysis, on both structured and unstructured data, and to do it all in an affordable manner.
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     Dell and Intel®
By: snowflake     Published Date: Jun 09, 2016
Today’s data, and how that data is used, have changed dramatically in the past few years. Data now comes from everywhere—not just enterprise applications, but also websites, log files, social media, sensors, web services, and more. Organizations want to make that data available to all of their analysts as quickly as possible, not limit access to only a few highly-skilled data scientists. However, these efforts are quickly frustrated by the limitations of current data warehouse technologies. These systems simply were not built to handle the diversity of today’s data and analytics. They are based on decades-old architectures designed for a different world, a world where data was limited, users of data were few, and all processing was done in on-premises datacenters.
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     snowflake
By: snowflake     Published Date: Jun 09, 2016
THE CHALLENGE: DATA SOLUTIONS CAN’T KEEP PACE WITH DATA NEEDS Organizations are increasingly dependent on diff erent types of data to make successful business decisions. But as the volume, rate, and types of data expand and become less predictable, conventional data warehouses cannot consume all this data eff ectively. Big data solutions like Hadoop increase the complexity of the environment and generally lack the performance of traditional data warehouses. This makes it difficult, expensive, and time-consuming to manage all the systems and the data.
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     snowflake
By: Revolution Analytics     Published Date: May 09, 2014
As the primary facilitator of data science and big data, machine learning has garnered much interest by a broad range of industries as a way to increase value of enterprise data assets. Through techniques of supervised and unsupervised statistical learning, organizations can make important predictions and discover previously unknown knowledge to provide actionable business intelligence. In this guide, we’ll examine the principles underlying machine learning based on the R statistical environment. We’ll explore machine learning with R from the open source R perspective as well as the more robust commercial perspective using Revolution Analytics Enterprise (RRE) for big data deployments.
Tags : revolution analytics, data science, big data, machine learning
     Revolution Analytics
By: BitStew     Published Date: May 26, 2016
The heaviest lift for an industrial enterprise is data integration, the Achilles’ heel of the Industrial Internet of Things (IIoT). Companies are now recognizing the enormous challenge involved in supporting Big Data strategies that can handle the data that is generated by information systems, operational systems and the extensive networks of old and new sensors. To compound these issues, business leaders are expecting data to be captured, analyzed and used in a near real-time to optimize business processes, drive efficiency and improve profitability. However, integrating this vast amount of dissimilar data into a unified data strategy can be overwhelming for even the largest organizations. Download this white paper, by Bit Stew’s Mike Varney, to learn why a big data solution will not get the job done. Learn how to leverage machine intelligence with a purpose-built IIoT platform to solve the data integration problem.
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     BitStew
By: Dell APAC     Published Date: May 30, 2019
When it comes to effectively and efficiently protecting growing volumes of data, midsized organizations face unique challenges. That is because they live in a world of constraints that are both operational and budgetary in nature. Cloud disaster recovery offers new options for these organizations—they can optimize their data protection economics by integrating on-premises protection solutions with cloud-based backup and recovery methods. Dell EMC’s cloud-ready solutions, particularly its Integrated Data Protection Appliances with native cloud extension capabilities, along with its Data Protection Software working in conjunction with its Data Domain backup storage appliances, provide cloud disaster recovery with flexible features. These solutions enhance operational efficiency and provide midsized organizations with clear economic and operational benefits.
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     Dell APAC
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