business data

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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 19, 2013
SAP HANA enables real-time access to mission-critical, business data and thus, revolutionizes the way existing information can be utilized to address ever changing business requirements. This whitepaper describes both the business and technical benefits of implementing the Cisco UCS with NetApp Storage for SAP HANA solution.
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     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
Every day, the world creates 2.5 quintillion bytes of data and businesses are realizing tangible results from investments in big data analytics. IBM Spectrum Scale (GPFS) offers an enterprise class alternative to Hadoop Distributed File System (HDFS) for building big data platforms and provides a range of enterprise-class data management features. Spectrum Scale can be deployed independently or with IBM’s big data platform, consisting of IBM InfoSphere® BigInsights™ and IBM Platform™ Symphony. This document describes best practices for deploying Spectrum Scale in such environments to help ensure optimal performance and reliability.
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     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: 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: 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: 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: TIBCO     Published Date: Sep 02, 2014
In this Guide you will learn how predictive analytics helps your organization predict with confidence what will happen next so that you can make smarter decisions and improve business outcomes. It is important to adopt a predictive analytics solution that meets the specific needs of different users and skill sets from beginners, to experienced analysts, to data scientists.
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     TIBCO
By: IBM     Published Date: Nov 14, 2014
Every day, the world creates 2.5 quintillion bytes of data and businesses are realizing tangible results from investments in big data analytics. IBM Spectrum Scale (GPFS) offers an enterprise class alternative to Hadoop Distributed File System (HDFS) for building big data platforms and provides a range of enterprise-class data management features. Spectrum Scale can be deployed independently or with IBM’s big data platform, consisting of IBM InfoSphere® BigInsights™ and IBM Platform™ Symphony. This document describes best practices for deploying Spectrum Scale in such environments to help ensure optimal performance and reliability.
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     IBM
By: Intel     Published Date: Sep 16, 2014
In this Guide, we take a look at what Lustre on infrastructure AWS delivers for a broad community of business and commercial organizations struggling with the challenge of big data and demanding storage growth.
Tags : intel, lustre, big data solutions in the cloud
     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
New technologies help decision makers gain insights from all types of data - from traditional databases to high-visibility social media sources. Big data initiatives must ensure data is cost-effectively managed, shared by systems across the enterprise, and quickly and securely made available for analysis and action by line-of-business teams. In this article, learn how Dell working with Intel® helps IT leaders overcome the challenges of IT and business alignment, resource constraints and siloed environments through a comprehensive big data portfolio based on choice and flexibility, redefined economics and connected intelligence.
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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
This business-oriented white paper summarizes the wide-ranging benefits of the Hadoop platform, highlights common data processing use cases and explores examples of specific use cases in vertical industries. The information presented here draws on the collective experiences of three leaders in the use of Hadoop technologies—Dell and its partners Cloudera® and Intel®.
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     Dell and Intel®
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: 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: Hewlett Packard Enterprise     Published Date: Jul 29, 2019
Learn about the HPE Intelligent Data Platform and the new IT realities it addresses. With digital transformation underway in many organizations, more dynamic business models are becoming the key to success. This means infrastructure modernization and the introduction of technologies such as solid state storage, artificial intelligence and machine learning, software-defined infrastructure, and the cloud. At the same time, it means IT infrastructure management becomes much more complex. Enter HPE’s Intelligent Data Platform. With comprehensive coverage and AI/ML-driven real-time optimization that enables intelligent management of the entire data life cycle, the HPE Intelligent Data Platform enables an organization to get the most out of its IT resources while also meeting its evolving needs over time.
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     Hewlett Packard Enterprise
By: Aberdeen     Published Date: Jun 17, 2011
Download this paper to learn the top strategies leading executives are using to take full advantage of the insight they receive from their business intelligence (BI) systems - and turn that insight into a competitive weapon.
Tags : aberdeen, michael lock, data-driven decisions, business intelligence, public sector, analytics, federal, state
     Aberdeen
By: Dell SB     Published Date: Jul 31, 2019
Take back control of your infrastructure projects and build the business case using your own data with Dell EMC’s Live Optics. We can help create a defensible proposal, unique to your environment, using your Live Optics data. Take the guess work out of your projects and build a new infrastructure based on your actual needs. When can we set up a call to discuss?
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     Dell SB
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