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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: Dell APAC     Published Date: May 30, 2019
To out-innovate and out-pace their competition, organizations must be on a consistent path to keep their infrastructure modern. IT is under constant pressure to deliver optimized infrastructure for new business initiatives and supporting applications all while trying to contain or even reduce costs.
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     Dell APAC
By: Dell APAC     Published Date: May 30, 2019
To out-innovate and out-pace their competition, organizations must be on a consistent path to keep their infrastructure modern. IT is under constant pressure to deliver optimized infrastructure for new business initiatives and supporting applications all while trying to contain or even reduce costs.
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     Dell APAC
By: Dell APAC     Published Date: May 30, 2019
To out-innovate and out-pace their competition, organizations must be on a consistent path to keep their infrastructure modern. IT is under constant pressure to deliver optimized infrastructure for new business initiatives and supporting applications all while trying to contain or even reduce costs.
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     Dell APAC
By: Dell APAC     Published Date: May 30, 2019
To out-innovate and out-pace their competition, organizations must be on a consistent path to keep their infrastructure modern. IT is under constant pressure to deliver optimized infrastructure for new business initiatives and supporting applications all while trying to contain or even reduce costs.
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     Dell APAC
By: Larsen & Toubro Infotech(LTI)     Published Date: Jul 11, 2019
One of the largest consumer product goods conglomerates wanted their entire platform to be re-hosted, and also enhance its storage and stability. The LTI-developed Cloud Native app on Azure PaaS also helped drive the business value for sourcing through the integration of S2P transformation. Download full case study
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     Larsen & Toubro Infotech(LTI)
By: Akamai Technologies     Published Date: Jul 02, 2019
In today’s markets, customer identities and the personal data associated with them are among the most critical and valuable assets of any enterprise. Managing these digital identities — from first registration and login to the later stages of the customer relationship — and extracting business value from the associated data are complex tasks, commonly referred to as customer identity and access management (CIAM). When implementing a system to collect, manage, and utilize digital identity and customer data, companies have two basic choices: in-house development or buying a dedicated solution from a vendor specialized in CIAM (i.e., build vs. buy). Read this white paper for an in-depth analysis of CIAM implementation options, including: ? Must-haves for a successful, enterprise-grade CIAM system ? Pros and cons of implementation options, ranging from in-house software development to commercial off-the-shelf solutions ? A real-world case study that illustrates the ROI of an effective CI
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     Akamai Technologies
By: Pure Storage     Published Date: Jul 03, 2019
Apache® Spark™ has become one of the most rapidly adopted open source platforms in history. Demand is predicted to grow at a compound annual rate of 67% per year between 2017 and 2020, with the cumulative Spark market valued at more than $9 billion during that period, according to the research firm MarketAnalysis.com.
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     Pure Storage
By: Schneider Electric     Published Date: Jul 01, 2019
As water is increasingly being recognized as a high-value commodity, aging assets present a major threat to organizations that treat and deliver it. Improving asset performance is one of the most effective strategies water and wastewater plants and networks can implement to reduce costs and protect quality.
Tags : water, plant, pump
     Schneider Electric
By: HERE Technologies     Published Date: May 22, 2019
Operational readiness depends on rich location data. When managing logistics and tracking high-value assets, there is no room for error and our new data-driven world demands richer, smarter advanced mapping and navigation services. The 2018 Counterpoint Research Location Ecosystems Update compared 16 location platform vendors—including Google, TomTom and Mapbox—and it named HERE the “undisputed leader” in location based services. Counterpoint recognized HERE for its integrated analytical capability and commitment to open partnerships, allowing for custom operational requirements and a truly mobile location intelligence platform. See how HERE provides the industry leading tools and expertise to process that data—streamlining the logistics supply chain, boosting responsiveness, and guaranteeing mission success.
Tags : mapping, defence, location data.
     HERE Technologies
By: Black Duck Software     Published Date: Feb 17, 2009
"Agile" software development is an increasingly popular development process for producing software in a flexible and iterative manner that can deliver value to the enterprise faster, reduce project risk and allow adaptation to changes more quickly.
Tags : black duck software, open source, platform, sap, multi-source, code, source, agile development
     Black Duck Software
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