big data

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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: Intel     Published Date: Aug 06, 2014
Powering Big Data Workloads with Intel® Enterprise Edition for Lustre* software The Intel® portfolio for high-performance computing provides the following technology solutions: • Compute - The Intel® Xeon processor E7 family provides a leap forward for every discipline that depends on HPC, with industry-leading performance and improved performance per watt. Add Intel® Xeon Phi coprocessors to your clusters and workstations to increase performance for highly parallel applications and code segments. Each coprocessor can add over a teraflops of performance and is compatible with software written for the Intel® Xeon processor E7 family. You don’t need to rewrite code or master new development tools. • Storage - High performance, highly scalable storage solutions with Intel® Lustre and Intel® Xeon Processor E7 based storage systems for centralized storage. Reliable and responsive local storage with Intel® Solid State Drives. • Networking - Intel® True Scale Fabric and Networking technologies – Built for HPC to deliver fast message rates and low latency. • Software and Tools: A broad range of software and tools to optimize and parallelize your software and clusters. Further, Intel Enterprise Edition for Lustre software is backed by Intel, the recognized technical support providers for Lustre, and includes 24/7 service level agreement (SLA) coverage.
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     Intel
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: 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
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
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
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: 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: Dell and Intel®     Published Date: Sep 06, 2015
In conclusion, the retail experience has changed dramatically in recent years as there has been a power shift over to consumers. Shoppers can easily find and compare products from an array of devices, even while walking through a store. They can share their opinions about retailers and products through social media and influence other prospective customers. To compete in this new multi-channel environment, we’ve seen in this guide how retailers have to adopt new and innovative strategies to attract and retain customers. Big data technologies, specifically Hadoop, enable retailers to connect with customers through multiple channels at an entirely new level by harnessing the vast volumes of new data available today. Hadoop helps retailers store, transform, integrate and analyze a wide variety of online and offline customer data—POS transactions, e-commerce transactions, clickstream data, email, social media, sensor data and call center records—all in one central repository. Retailers can
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     Dell and Intel®
By: GridGain     Published Date: Mar 10, 2015
Software as a Service (SaaS) is a software distribution model in which applications are hosted by a vendor or service provider and made available to customers over the Internet. Instead of companies installing software on their own servers, known as the on premises distribution model, application software providers host the software in the cloud and charge customers according to the time they spend using the software, or based on a monthly or annual fee. SaaS is becoming increasingly popular, and as the industry develops, more and more companies are dropping older business models in favor of this rapidly evolving methodology.
Tags : gridgain, saas, saas perfomance and scalability, in memory computing, data fabric, paas for saas, data grid, real-time streaming, hadoop
     GridGain
By: Kx Systems     Published Date: Jan 16, 2015
?Kdb+ is a column-based relational database with extensive in-memory capabilities, developed and marketed by Kx Systems. Like all such products, it is especially powerful when it comes to supporting queries and analytics. However, unlike other products in this domain, kdb+ is particularly good (both in terms of performance and functionality) at processing, manipulating and analysing data (especially numeric data) in real-time, alongside the analysis of historical data. Moreover, it has extensive capabilities for supporting timeseries data. For these reasons Kx Systems has historically targeted the financial industry for trading analytics and black box trading based on real-time and historic data, as well as realtime risk assessment; applications which are particularly demanding in their performance requirements. The company has had significant success in this market with over a hundred major financial institutions and hedge funds deploying its technology. In this paper, however, we wa
Tags : kx systems, kdb+, relational database
     Kx Systems
By: snowflake     Published Date: Jun 09, 2016
Why Read This Report In the era of big data, enterprise data warehouse (EDW) technology continues to evolve as vendors focus on innovation and advanced features around in-memory, compression, security, and tighter integration with Hadoop, NoSQL, and cloud. Forrester identified the 10 most significant EDW software and services providers — Actian, Amazon Web Services (AWS), Hewlett Packard Enterprise (HPE), IBM, Microsoft, Oracle, Pivotal Software, SAP, Snowflake Computing, and Teradata — in the category and researched, analyzed, and scored them. This report details our findings about how well each vendor fulfills our criteria and where they stand in relation to each other to help enterprise architect professionals select the right solution to support their data warehouse platform.
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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: 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: 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: BigCommerce     Published Date: Oct 16, 2018
Businesses who have lived through the evolution of the digital age are well aware that we’ve experienced a generational shift in technology. The rise of software as a service (SaaS), cloud, mobile, big data, the Internet of Things (IoT), social media, and other technologies have disrupted industries and changed customers’ expectations. In our always-on, buy anything anywhere world, customers want their shopping experiences to be personalized, dynamic, and convenient. As a result, many businesses are trying to reinvent themselves. Success in a fast-paced economy depends on continually adapting and innovating. Companies have to move quickly to keep up; there’s no time for disjointed technologies and old systems that don’t serve the customer-obsessed mentality needed to thrive in the digital age.
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     BigCommerce
By: Cisco EMEA     Published Date: Nov 08, 2018
Digital transformation (DX) — a technology-driven business strategy — enables firms to gain or expand their competitive differentiation by embracing data-driven decision-making processes, whether for increasing operational efficiencies, developing new products and services, increasing customer satisfaction and retention, or getting a better intelligence on the market. Big Data and analytics (BDA) applications form the foundation for enterprisewide digital transformation initiatives. To find out more download this whitepaper today.
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     Cisco EMEA
By: Here Technologies     Published Date: Dec 05, 2018
Discover the four big trends in fleet management being powered by location services. Trends to help you differentiate your solutions and enable transportation companies to overcome their logistical challenges and increase asset utilization. Discover what’s making the biggest impact, together with how, by integrating some of these trends into your solutions, you can position yourself as the service provider of choice in fleet and transportation management solutions. And find out how HERE is delivering features, from comprehensive mapping capabilities and real-time location data, to truck-specific attributes, to help you do just that. Download the eBook now
Tags : location data, transport & logistics, location services
     Here Technologies
By: Splunk     Published Date: Nov 29, 2018
From protecting customer experience to preserving lines of revenue, IT operations teams face increasingly complex responsibilities and are responsible for preventing outages that could harm the organization. As a Splunk customer, your machine data platform empowers you to utilize machine learning to reduce MTTR. Discover how six companies utilize machine learning and AI to predict outages, protect business revenue and deliver exceptional customer experiences. Download the e-book to learn how: Micron Technology reduced number of IT incidents by more than 50% Econocom provides better customer service by centralizing once-siloed analytics, improving SLA performance and significantly reducing the number of events TransUnion combines machine data from multiple applications to create an end-to-end transaction flow
Tags : predictive it, predictive it tools, predictive analytics for it, big data and predictive analytics
     Splunk
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