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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: IBM     Published Date: Sep 02, 2014
Advanced analytics strategies yield the greatest benefits in terms of improving patient and business outcomes when applied across the entire healthcare ecosystem. But the challenge of collaborating across organizational boundaries in order to share information and insights is daunting to many stakeholders. In this worldwide survey of 555 healthcare providers, payers and life sciences organizations, you will learn the importance of implementing collaborative analytics strategies that: Manage, integrate and interpret data generated at all stages of the healthcare value chain Achieve the right balance of skills in order to translate data into actionable insights Focus on executive sponsorship and enterprise-wide adoption with metrics to measure and track success Position yourself to harness data, create and share insights, make informed decisions, and improve the performance of the entire healthcare ecosystem in which you operate.
Tags : ibm, analytics acrosss ecosystem
     IBM
By: IBM     Published Date: May 20, 2015
According to our global study of more than 800 cloud decision makers and users are becoming increasingly focused on the business value cloud provides. Cloud is integral to mobile, social and analytics initiatives – and the big data management challenge that often comes with them and it helps power the entire suite of game-changing technologies. Enterprises can aim higher when these deployments are riding on the cloud. Mobile, analytics and social implementations can be bigger, bolder and drive greater impact when backed by scalable infrastructure. In addition to scale, cloud can provide integration, gluing the individual technologies into more cohesive solutions. Learn how companies are gaining a competitive advanatge with cloud computing.
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     IBM
By: IBM     Published Date: Sep 16, 2015
Building applications for handling big data requires laser-like focus on solutions that allow you to deliver scalable, reliable and flexible infrastructure for fast-growing analytics environments. This paper provides 6 best practices for selecting the “right” infrastructure—one that is optimized for performance, flexibility and long-term value.
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     IBM
By: Impetus     Published Date: Mar 15, 2016
Streaming analytics platforms provide businesses a method for extracting strategic value from data-in-motion in a manner similar to how traditional analytics tools operate on data-at rest. Instead of historical analysis, the goal with streaming analytics is to enable near real-time decision making by letting companies inspect, correlate and analyze data even as it flows into applications and databases from numerous different sources. Streaming analytics allows companies to do event processing against massive volumes of data streaming into the enterprise at high velocity.
Tags : impetus, guide to stream analytics, real time streaming analytics, streaming analytics, real time analytics, big data analytics
     Impetus
By: Dell and Intel®     Published Date: Jun 18, 2015
The rapid evolution of big data technology in the past few years has changed forever the pursuit of scientific exploration and discovery. Along with traditional experiment and theory, computational modeling and simulation is a third paradigm for science. Its value lies in exploring areas of science in which physical experimentation is unfeasible and insights cannot be revealed analytically, such as in climate modeling, seismology and galaxy formation. More recently, big data has been called the “fourth paradigm" of science. Big data can be observed, in a real sense, by computers processing it and often by humans reviewing visualizations created from it. In the past, humans had to reduce the data, often using techniques of statistical sampling, to be able to make sense of it. Now, new big data processing techniques will help us make sense of it without traditional reduction
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     Dell and Intel®
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: 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: Apr 02, 2015
In this Guide we have delivered the case for the benefits of big data technology applied to the needs of the manufacturing industry. In demonstrating the value of big data, we included: • An overview of how manufacturing can benefit from the big data technology stack • An overview of how manufacturing can benefit from the big data technology stack • A high-level view of common big data pain points for manufacturers • A detailed analysis of big data technology for manufacturers • A view as to how manufacturers are going about big data adoption • A proven case study with: Omneo • Dell PowerEdge servers with Intel® Xeon® processors
Tags : dell, intel, big data, manufacturing, technology stack, pain points, big data adoption, omneo
     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
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: Cask     Published Date: Jun 28, 2016
A recent Gartner survey on Hadoop cited the two biggest challenges in working with Hadoop: “Skills gaps continue to be a major adoption inhibitor for 57% of respondents, while deciding how to get value from Hadoop was cited by 49% of respondents.” Cask is the company that makes building and deploying big data apps easy, allowing for 5 times faster time to value. To find out more, read about Cask Hydrator, a self-service, open source framework that lets data scientists easily develop and operate data pipelines using a graphical interface.
Tags : cask hydrator, hadoop, gartner survey, self-service data lakes
     Cask
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: Adaptive Computing     Published Date: Feb 27, 2014
Big data applications represent a fast-growing category of high-value applications that are increasingly employed by business and technical computing users. However, they have exposed an inconvenient dichotomy in the way resources are utilized in data centers. Conventional enterprise and web-based applications can be executed efficiently in virtualized server environments, where resource management and scheduling is generally confined to a single server. By contrast, data-intensive analytics and technical simulations demand large aggregated resources, necessitating intelligent scheduling and resource management that spans a computer cluster, cloud, or entire data center. Although these tools exist in isolation, they are not available in a general-purpose framework that allows them to inter operate easily and automatically within existing IT infrastructure.
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     Adaptive Computing
By: SendBird     Published Date: Nov 14, 2019
Why buyer-to-seller chat for marketplaces? Experts understand marketplace apps as a challenge in scaling both supply- and demand-side at the same time. Once trust and sufficient liquidity are achieved, the value of marketplaces shift to fostering transparent and efficient transactions. There’s no better way to connect buyer and seller than in-app messaging. Real-time messaging connects your marketplace’s buyers and sellers across multiple apps and platforms so they can engage and inform both supply and demand to transact more quickly. This creates more efficient transactions for the marketplace platform. Jeff Jordan, former eBay and current General Partner of Andreessen Horowitz, said that to manage a marketplace well you need to “Maintain complete transparency in the marketplace so that participants (especially buyers but sellers too) have perfect information on products and their pricing [...] Focus heavily on safety so the marketplace is as safe as possible to create the trust requi
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     SendBird
By: SendBird     Published Date: Nov 14, 2019
On-demand businesses can use this guide to design and plan user-to-user messaging to drive more engagement and gross transaction value
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     SendBird
By: Experian     Published Date: Sep 26, 2019
"We are in an age of unprecedented opportunity, where ubiquitous data and new technologies are shaping the world and dramatically changing the way consumers interact with businesses like yours. The rise of fintech companies is driving competition, e-commerce has raised the bar for digital experiences, fraud is at an all-time high, and there is pressure to grow your business. You need to meet these challenges head on and do it in a way that can scale with the increasing volume — and value — of customers. All while meeting and exceeding customer expectations. We believe rapid, sustainable growth can be fuelled by acquiring the right customers and delivering customer experiences that align with their expectations. To succeed you need a comprehensive, unified view into your customers and their needs. As a business leader, how do you achieve these objectives? What can you do to attract and acquire new customers? What tools do you need to quickly act on insights and to make consistent, relev
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     Experian
By: Corrigo     Published Date: Nov 01, 2019
PropTech is disrupting the facilities management and real estate industries – from big data and IoT to artificial intelligence and augmented reality. The latest advances in PropTech are accelerating change in facilities management like never before, driving bottom line value and helping future-proof FM operations. The promise of PropTech is why our Corrigo team is investing so heavily in frictionless, self-learning platforms to help our clients use technology to truly transform their businesses. But as we amplify FM ops with new technology, we are just as passionate about helping our clients optimize their current processes. Why? Because making even small changes today can mean huge savings for their bottom line. In fact, 80% of organizations are leaking more FM value right now than they could immediately gain with new, emerging tech strategies. That’s no small leak – it’s a staggering loss for organizations of all sizes. After analyzing 700 million facilities management transactions a
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     Corrigo
By: Corrigo     Published Date: Nov 01, 2019
Think about all the ways your life today is different than it was ten years ago. Think about how you shop, how you get around, how you plan travel, and how you stay in touch. So many things that used to be a hassle are now almost effortless. If your life feels different, it’s because you’re living in a new era – what experts are calling the 4th Industrial Revolution. You’ve probably heard some of the more catch-phrased components – big data, artificial intelligence, deep analytics. Some of these still seem like science fiction, but they are very real, very active, and crucial parts of what we at Corrigo call the Intelligence Economy. In the Intelligence Economy, data is collected, crunched, and activated to solve problems and create greater value for customers, partners, and employees. It’s the information, insights, and automations that enhance experiences, predict needs, strengthen connections, and deliver the right info or action at the right time, in the right way. And the Intellig
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     Corrigo
By: KPMG     Published Date: Oct 15, 2019
Consumers have become more educated about the value of data and cyber risks associated with it. As consumer awareness increases so does their expectations of trust and digital security. Read now KPMG's report Trust in the time of disruption to understand the cybersecurity gap that exists between consumers and organisations, and what asset management and financial services firms as a whole can do to close the trust gap.
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     KPMG
By: ServiceNow     Published Date: Oct 23, 2019
The quality of data that your Configuration Management Database (CMDB) relies on is critical to helping you track the software assets coming into an organization from the point of inception to the point of disposition. That’s where Software Asset Management (SAM) can help.Download this whitepaper to understand how to use SAM to build a CMDB that helps you track the value of IT services, improve compliance, and scale to meet changing service demands.
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     ServiceNow
By: ServiceNow     Published Date: Oct 23, 2019
"ITAM teams are uniquely placed to provide a holistic view of the IT landscape through their people, processes, and tools. This holistic view improves strategic decision-making, helps break down silos, and identifies opportunities for innovationand service improvement. This whitepaper provides a roadmap to enable ITAM teams to gain seniority and contribute enhanced business value through effective stakeholder engagement."
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     ServiceNow
By: Intel     Published Date: Nov 14, 2019
Infrastructure considerations for IT leaders By 2020, deep learning will have reached a fundamentally different stage of maturity. Deployment and adoption will no longer be confined to experimentation, becoming a core part of day-to-day business operations across most fields of research and industries. Why? Because advancements in the speed and accuracy of the hardware and software that underpin deep learning workloads have made it both viable and cost-effective. Much of this added value will be generated by deep learning inference – that is, using a model to infer something about data it has never seen before. Models can be deployed in the cloud or data center, but more and more we will see them on end devices like cameras and phones. Intel predicts that there will be a shift in the ratio between cycles of inference and training from 1:1 in the early days of deep learning, to well over 5:1 by 2020¹. Intel calls this the shift to ‘inference at scale’ and, with inference also taking up
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     Intel
By: Intel     Published Date: Nov 14, 2019
-memory databases have moved from being an expensive option for exceptional analytics workloads, to delivering on a far broader set of goals. Using real-world examples and scenarios, in this guide we look at the component parts of in-memory analytics, and consider how to ensure such capabilities can be deployed to maximize business value from both the technology and the insights generated.
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     Intel
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