using data

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By: NetApp     Published Date: Dec 18, 2013
IT managers have indicated their two most significant challenges associated with managing unstructured data at multiple locations were keeping pace with data growth and improving data protection . Learn how the NetApp Distributed Content Repository provides advanced data protection and system recovery capabilities that can enable multiple data centers and remote offices to maintain access to data through hardware and software faults. Key benefits are: - continuous access to file data while maintaining data redundancy with no administrator intervention needed. - easily integrated and deployed into a distributed environment, providing transparent, centrally managed content storage - provision of secure multi-tenancy using security partitions. - provision effectively infinite, on-demand capacity while providing fast access to files and objects in the cloud. - secure, robust data protection techniques that enable data to persist beyond the life of the storage it resides on
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     NetApp
By: IBM     Published Date: Sep 02, 2014
Research teams using next-generation sequencing (NGS) technologies face the daunting challenge of supporting compute-intensive analysis methods against petabytes of data while simultaneously keeping pace with rapidly evolving algorithmic best practices. NGS users can now solve these challenges by deploying the Accelrys Enterprise Platform (AEP) and the NGS Collection on optimized systems from IBM. Learn how you can benefit from the turnkey IBM Application Ready Solution for Accelrys with supporting benchmark data.
Tags : ibm, accelrys, turnkey ngs solution
     IBM
By: IBM     Published Date: Sep 16, 2015
The IBM Spectrum Scale solution provided for up to 11x better throughput results than EMC Isilon for Spectrum Protect (TSM) workloads. Using published data, Edison compared a solution comprised of EMC® Isilon® against an IBM® Spectrum Scale™ solution. (IBM Spectrum Scale was formerly IBM® General Parallel File System™ or IBM® GPFS™, also known as code name Elastic Storage). For both solutions, IBM® Spectrum Protect™ (formerly IBM Tivoli® Storage Manager or IBM® TSM®) is used as a common workload performing the backups to target storage systems evaluated.
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     IBM
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: Nov 14, 2014
View this series of short webcasts to learn how IBM Platform Computing products can help you ‘maximize the agility of your distributed computing environment’ by improving operational efficiency, simplify user experience, optimize application using and license sharing, address spikes in infrastructure demand and reduce data management costs.
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     IBM
By: snowflake     Published Date: Jun 09, 2016
Check out this short Webinar: Using the Cloud For Speed-of-Thought Analytics on All Your Data
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     snowflake
By: snowflake     Published Date: Jun 09, 2016
Data and the way that data is used have changed, but data warehousing has not. Today’s premises-based data warehouses are based on technology that is, at its core, two decades old. To meet the demands and opportunities of today, data warehouses have to fundamentally change.
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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: Citrix ShareFile     Published Date: Jul 02, 2019
Get the report to find out how smart organizations are using new strategies to simplify IT infrastructures and empower employees to do their best work: • Get advice from Google and Citrix on how to manage the cloud transition strategically • Avoid common cloud work side effects such as excessive application logins, siloed data searches, and channel switching • Capture a vision for how artificial intelligence (AI) and machine learning are making work even more intuitive and personalized
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     Citrix ShareFile
By: Adobe     Published Date: Jun 26, 2019
The Digital Trends 2019 survey closed with more than 12,500 responses worldwide! The results are in for 2019 and once again, businesses have their sights set on improving customer experience. Data continues to dominate, with an understanding that smarter use will lead to greater rewards. Data ownership and compliance are top-of-mind. And technological advances are an exciting prospect for many. But some need more guidance to understand the benefits for their business. Discover what your top digital priorities for 2019 should be with the 2019 Digital Trends report by Econsultancy in association with Adobe. Key topics that you’ll read more about in this year’s report: • Optimising customer experience and delivering personalised experiences in real time. • Using data better for smarter audience segmentation and targeting. • Be wary of walled gardens. Control and own the data, and always be compliant. • Automation is the future. Understand the benefits, learn how to use it.
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     Adobe
By: Procore     Published Date: Jun 25, 2019
Did you know that more than 1.2 billion people use Microsoft Office? That’s one in 7 people. A huge portion of the world’s economy is managed through it: from small businesses all the way up to Fortune 500 corporations. Despite its popularity, Excel has its fair share of critics. What originated as rumblings among IT professionals and tech blogs, has quickly trickled into major business and technology publications. Some might think it harsh, but we want to show you the risks of using Excel in your business and help you understand how you can protect yourself, your company and your data from what Forbes refers to as ‘the most dangerous software on the planet’.
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     Procore
By: SAS     Published Date: Jun 26, 2019
To support open government initiatives and uphold the values of transparency, participation and collaboration in the US, federal agencies today make their data open, or publicly accessible. Citizens can use this open data to assess college affordability, the economy, educational issues, environmental damage, health care, taxes, agriculture, the climate and more. Governments can use APIs to pull this open data into SAS Visual Analytics as a way to identify trends and patterns and obtain all sorts of new insights. With public health surveillance, for example, governments can monitor and evaluate indicators that point to high-risk areas so they’ll know where and how to focus efforts. Such public health surveillance can serve as an early warning system for impending emergencies, document the impact of an intervention, track progress toward public health goals, and clarify health problems to inform public health policies and strategies.
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     SAS
By: SAP     Published Date: Dec 14, 2010
While your competitors sit back, download this free paper to learn how to cut costs, boost profits, build loyalty, and solve a myriad of day-to-day business challenges.
Tags : sap, data strategy, competitive data, reduce costs, increase profits, employee improvement, business performance
     SAP
By: Upsite Technologies     Published Date: Sep 18, 2013
The average computer room today has cooling capacity that is nearly four times the IT heat load. Using data from 45 sites reviewed by Upsite Technologies, this white paper will show how you can calculate, benchmark, interpret, and benefit from a simple and practical metric called the Cooling Capacity Factor (CCF). Calculating the CCF is the quickest and easiest way to determine cooling infrastructure utilization and potential gains to be realized by AFM improvements.
Tags : ccf, upsite technologies, cooling capacity factor, energy costs, cooling, metrics, practical, benchmark
     Upsite Technologies
By: Zynapse     Published Date: Sep 10, 2010
A 14-page whitepaper on how to achieve lower material costs and optimized inventory using Material Master Data Management
Tags : zynapse, erp projects, data information, data management, governance, mdm, master data management, odm, mmdm, material
     Zynapse
By: SAP     Published Date: Mar 09, 2017
Learn how CIOs can set up a system infrastructure for their business to get the best out of Big Data. Explore what the SAP HANA platform can do, how it integrates with Hadoop and related technologies, and the opportunities it offers to simplify your system landscape and significantly reduce cost of ownership.
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     SAP
By: Cisco     Published Date: Mar 22, 2019
Artificial intelligence (AI) and machine learning (ML) are emerging technologies that will transform organizations faster than ever before. In the digital transformation era, success will be based on using analytics to discover the insights locked in the massive volume of data being generated today. Historically, these insights were discovered through manually intensive data analytics—but the amount of data continues to grow, as does the complexity of data. AI and ML are the latest tools for data scientists, enabling them to refine the data into value faster.
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     Cisco
By: Zaloni     Published Date: Apr 23, 2019
Although data and analytics are highlighted throughout the popular press as well as in trade publications, too many managers think the value of this data processing is limited to a few numerically intensive fields such as science and finance. In fact, big data and the insights that emerge from analyzing it will transform every industry, from “precision farming” to manufacturing and construction. Governments must also be alert to the value of data and analytics as the enabler for smart cities. Institutions that master available data will leap ahead of their less statistically adept competitors through many advantages: finding hidden opportunities for efficiency, using data to become more responsive to clients, and developing entirely new and unanticipated product lines. The average time spent by most companies on the S&P 500 Index has decreased from an average of 60 to 70 years to only 22 years. There are winners and losers in the changes that come with the evolution of both technology
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     Zaloni
By: Hewlett Packard Enterprise     Published Date: Jul 18, 2018
"Principled Technologies executed four typical deployment and management scenarios using both HPE Synergy and Cisco UCS. They found that HPE Synergy saved 71.5 minutes and 86 steps, and used four fewer tools compared to Cisco UCS. In a hypothetical 200-node datacenter, that’s a total of 9 work weeks, or just over 2 months’ time savings on routine tasks."
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     Hewlett Packard Enterprise
By: Hewlett Packard Enterprise     Published Date: Jan 31, 2019
The bar for success is rising in higher education.  University leaders and IT administrators are aware of the compelling benefits of digital transformation overall—and artificial intelligence (AI) in particular. AI can amplify human capabilities by using machine learning, or deep learning, to convert the fast-growing and plentiful sources of data about all aspects of a university into actionable insights that drive better decisions. But when planning a transformational strategy, these leaders must prioritize operational continuity. It’s critical to protect the everyday activities of learning, research, and administration that rely on the IT infrastructure to consistently deliver data to its applications.
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     Hewlett Packard Enterprise
By: SAP     Published Date: Nov 17, 2016
Culture has become one of the most important business topics of 2016. CEOs and HR leaders now recognize that culture drives people's behavior, innovation, and customer service: 82 percent of survey respondents believe that "culture is a potential competitive advantage." Knowing that leadership behavior and reward systems directly impact organizational performance, customer service, employee engagement, and retention, leading companies are using data and behavioral information to manage and influence their culture.
Tags : sap, human resources, employee, deloitte, culture
     SAP
By: Hewlett Packard Enterprise     Published Date: May 10, 2019
Nimble Secondary Flash array represents a new type of data storage, designed to maximize both capacity and performance. By adding high-performance flash storage to a capacity-optimized architecture, it provides a unique backup platform that lets you put your backup data to work. Nimble Secondary Flash array uses flash performance to provide both near-instant backup and recovery from any primary storage system. It is a single device for backup, disaster recovery, and even local archiving. By using flash, you can accomplish real work such as dev/test, QA, and analytics. Deep integration with Veeam’s leading backup software simplifies data lifecycle management and provides a path to cloud archiving.
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     Hewlett Packard Enterprise
By: SAP     Published Date: May 18, 2014
From its conception, this special edition has had a simple goal: to help SAP customers better understand SAP HANA and determine how they can best leverage this transformative technology in their organization. Accordingly, we reached out to a variety of experts and authorities across the SAP ecosystem to provide a true 360-degree perspective on SAP HANA.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
Download this whitepaper to learn the results of this latest exploration of the emerging world of in-memory database technologies.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
This TDWI Checklist Report presents requirements for analytic DBMSs with a focus on their use with big data. Along the way, the report also defines the many techniques and tool types involved. The requirements checklist and definitions can assist users who are currently evaluating analytic databases and/or developing strategies for big data analytics.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
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