system architecture

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Published By: IBM     Published Date: Apr 19, 2016
This white paper describes how IBM’s Pure Data System for Analytics delivers speed and simplicity to help organizations become more responsive and agile in today’s increasingly mobile and data-driven market.
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ibm, ibm pure data system, big data, data analytics, analytics architecture, data management
    
IBM
Published By: IBM     Published Date: Apr 19, 2016
Big Data has generated much interest and attention in the media of late. Indeed, several authors have recently raised the question of whether Big Data approaches, such as Hadoop, will pronounce the death sentence on the conventional data warehouse. In this survey we investigate the current state of the data warehouse and examine its recent challenger in the form of Big Data solutions as an alternative. Is the new technology really complementary or is the reign of the data warehouse nearing an end?
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ibm, ibm pure data system, big data, data analytics, analytics architecture, data warehouse, data management
    
IBM
Published By: IBM     Published Date: Apr 19, 2016
The use of analytics will define the successful midmarket business of the next decade, just as it will define the successful larger organization in this information age. The past decade has seen rapid change in the business climates with an explosion of global competition and economic uncertainty. Despite this, many midmarket companies have thrived by using their size and agility as a competitive advantage. Certainly they have fewer resources than large corporations who are able to invest large sums in IT. However, small yachts can turn and adjust their course much quicker than large cruise ships. The same came be said for midmarket companies. The most successful organizations are ones that can react the quickest to changes in the market place. Midmarket companies can take advantage of their smaller size by being more agile and quicker to change, or even reinvent themselves, to respond to the market.
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ibm, ibm pure data system, big data, data analytics, analytics architecture, competitive advantage, midmarket organization, data management
    
IBM
Published By: IBM     Published Date: Jul 05, 2016
This white paper describes how IBM’s Pure Data System for Analytics delivers speed and simplicity to help organizations become more responsive and agile in today’s increasingly mobile and data-driven market.
Tags : 
ibm, ibm pure data system, big data, data analytics, analytics architecture, knowledge management, enterprise applications, data management
    
IBM
Published By: IBM     Published Date: Jul 05, 2016
Big Data has generated much interest and attention in the media of late. Indeed, several authors have recently raised the question of whether Big Data approaches, such as Hadoop, will pronounce the death sentence on the conventional data warehouse. In this survey we investigate the current state of the data warehouse and examine its recent challenger in the form of Big Data solutions as an alternative. Is the new technology really complementary or is the reign of the data warehouse nearing an end?
Tags : 
ibm, ibm pure data system, big data, data analytics, analytics architecture, data warehouse, knowledge management, data management
    
IBM
Published By: IBM     Published Date: Jul 08, 2016
In our 21-criteria evaluation of the dynamic case management (DCM) market, we identified the 14 most significant software vendors — Appian, bpm’online, Column Technologies, DST Systems, Eccentex, IBM, Isis Papyrus, Lexmark Enterprise Software, MicroPact, Newgen Software, OnBase by Hyland, OpenText, Pegasystems, and TIBCO Software — and researched, analyzed, and scored them. The evaluation focused on providers’ adaptive, analytics, and mobile features, all critical to helping enterprises tackle increasing volumes of varied and unstructured work. This report helps enterprise architecture (EA) professionals select the best providers to meet their unique needs.
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ibm, forrester, forrester wave, dynamic case management, dcm, networking, software development, enterprise applications
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
This white paper describes how IBM’s Pure Data System for Analytics delivers speed and simplicity to help organizations become more responsive and agile in today’s increasingly mobile and data-driven market.
Tags : 
ibm, ibm pure data system, big data, data analytics, analytics architecture, enterprise applications, data management, data center
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
Big Data has generated much interest and attention in the media of late. Indeed, several authors have recently raised the question of whether Big Data approaches, such as Hadoop, will pronounce the death sentence on the conventional data warehouse. In this survey we investigate the current state of the data warehouse and examine its recent challenger in the form of Big Data solutions as an alternative. Is the new technology really complementary or is the reign of the data warehouse nearing an end?
Tags : 
ibm, ibm pure data system, big data, data analytics, analytics architecture, data warehouse, enterprise applications, data management
    
IBM
Published By: Oracle     Published Date: Jan 28, 2019
Oracle Engineered Systems are architected to work as a unified whole, so organizations can hit the ground running after deployment. Organizations choose how they want to consume the infrastructure: on-premises, in a public cloud, or in a public cloud located inside the customer’s data center and behind their firewall using Oracle’s “Cloud at Customer” offering. Oracle Exadata and Zero Data Loss Recovery Appliance (Recovery Appliance) offer an attractive alternative to do-it-yourself deployments. Together, they provide an architecture designed for scalability, simplified management, improved cost of ownership, reduced downtime, zero-data loss, and an increased ability to keep software updated with security and patching. Download this whitepaper to discover ten capabilities to consider for protecting your Oracle Database Environments.
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Oracle
Published By: EMC Corporation     Published Date: May 27, 2014
Explore three key Cloud computing models—integrated infrastructure systems, reference architectures, and “build your own” solutions. See how EMC gives you the freedom to chose the optimal path to your private Cloud—and the solutions to support your deployment.
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emc, cloud computing, hybrid cloud, private cloud, cloud infrastructure, itaas, it-as-a-service, it services
    
EMC Corporation
Published By: HP-Intel®     Published Date: Jul 22, 2013
The Virtual Server Environment Reference Architecture described in this white paper centers around the HP-UX 11i v2 operating environments
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intel, ost, linux, operation systems, internal architecture, architecture, epic software, unix/risc architectures
    
HP-Intel®
Published By: MarkLogic     Published Date: Nov 08, 2016
In this report, learn to: 1. Do more with your structured and unstructured data 2. Combine disparate data sources without the limits of relational systems 3. Build applications faster within an agile data architecture Download now!
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MarkLogic
Published By: MarkLogic     Published Date: Nov 15, 2016
In this report, learn to: 1. Do more with your structured and unstructured data 2. Combine disparate data sources without the limits of relational systems 3. Build applications faster within an agile data architecture Download now!
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MarkLogic
Published By: MuleSoft     Published Date: Jan 25, 2016
IT used to be so simple. Companies owned their own technology equipment and purchased enterprise licenses for many of the applications anybody in the organization might care to use. But then the cloud emerged, and mobile, and social media, and IoT; the world of IT has never been the same. Today's businesses are software-driven enterprises with technology capability distributed throughout the company, utilizing countless third-party cloud-based applications. This new organization requires an cultural shift in the IT organization. Read this whitepaper to learn: -How businesses can reorganize themselves into lightweight, agile, modular businesses able to respond to innovations in SaaS, mobile, and analytics -How to build a technological architecture that can accommodate new technology yet still extract value from on-premises systems -The advantages of an API-led connected architecture vs. old SOA approaches
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technology, enterprise applications, best practices, business optimization, technology architecture, service oriented architecture, content management system, project management
    
MuleSoft
Published By: IBM     Published Date: Jul 05, 2016
The use of analytics will define the successful midmarket business of the next decade, just as it will define the successful larger organization in this information age. The past decade has seen rapid change in the business climates with an explosion of global competition and economic uncertainty. Despite this, many midmarket companies have thrived by using their size and agility as a competitive advantage. Certainly they have fewer resources than large corporations who are able to invest large sums in IT. However, small yachts can turn and adjust their course much quicker than large cruise ships. The same came be said for midmarket companies. The most successful organizations are ones that can react the quickest to changes in the market place. Midmarket companies can take advantage of their smaller size by being more agile and quicker to change, or even reinvent themselve
Tags : 
ibm, ibm pure data system, big data, data analytics, analytics architecture, competitive advantage, midmarket organization, knowledge management
    
IBM
Published By: Red Hat     Published Date: Jan 02, 2018
Microservices architecture is a new architectural style for creating loosely coupled but autonomous services. Emerging trends in technology—such as DevOps, Platform-as-a-Service (PaaS), containers, and continuous integration and delivery (CI/CD) methods—let organizations create and manage these modular systems on an unprecedented scale that exceeds earlier approaches like service-oriented architecture (SOA). But organizations that refactor monolithic applications into microservices experience widely varying degrees of success. The key to using microservices effectively is a solid understanding of how and why organizations should use microservices to build applications.
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Red Hat
Published By: Tricentis     Published Date: Aug 19, 2019
The way that we develop and deliver software has changed dramatically in the past 5 years—but the metrics we use to measure quality remain largely the same. Despite seismic shifts in business expectations, development methodologies, system architectures, and team structures, most organizations still rely on quality metrics that were designed for a much different era. Every other aspect of application delivery has been scrutinized and optimized as we transform our processes for DevOps. Why not put quality metrics under the microscope as well? Are metrics like number of automated tests, test case coverage, and pass/fail rate important in the context of DevOps, where the goal is immediate insight into whether a given release candidate has an acceptable level of risk? What other metrics can help us ensure that the steady stream of updates don’t undermine the very user experience that we’re working so hard to enhance? To provide the DevOps community an objective perspective on what quality
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Tricentis
Published By: Systemware     Published Date: Sep 07, 2018
Five key trends are shaping the enterprise content management (ECM) space. New business objectives, new market imperatives, and new cloud-based platforms compel technology and business decision makers to take a fresh look at their strategy and underlying platforms. This report will help enterprise architecture (EA) professionals make informed decisions about their content management agenda.
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systemware, content management, digital transformation, content cloud, top key trends, intelligent information, data storage, enterprise content management
    
Systemware
Published By: Systemware     Published Date: Sep 07, 2018
How’s your digital transformation going? What processes are you focusing on? Who’s leading the transformation? What technologies are a priority? What challenges do you face? To answer these questions, tap into the Forrester Data Global Business Technographics® Business And Technology Services Survey of your peers. Digital business pros should open this infographic to see the state of digital transformation.
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systemware, content management, digital transformation, content cloud, top key trends, intelligent information, data storage, enterprise content management
    
Systemware
Published By: Domino Data Lab     Published Date: Feb 08, 2019
A data science platform is where all data science work takes place and acts as the system of record for predictive models. While a few leading model-driven businesses have made the data science platform an integral part of their enterprise architecture, most companies are still trying to understand what a data science platform is and how it fits into their architecture. Data science is unlike other technical disciplines, and models are not like software or data. Therefore, a data science platform requires a different type of technology platform. This document provides IT leaders with the top 10 questions to ask of data science platforms to ensure the platform handles the uniqueness of data science work.
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Domino Data Lab
Published By: Mist Systems     Published Date: Jun 19, 2019
With a surge of 25,000 devices and counting, Dartmouth College needed its new Wi-Fi to be fast, reliable and as smart as its students. In response, Dartmouth, based in Hanover, N.H., began deploying new campus-wide Wi-Fi from Mist Systems last summer. It expects to complete the project throughout the campus in three to five years, according to Bryan Ward, a network engineer at Dartmouth. The IT department manages the Wi-Fi through a cloudbased wireless LAN and can already see the benefits of better coverage and easier management. But the team faced difficulties when embedding the new system with Dartmouth's centuries-old campus architecture, which is less supportive of campus-wide Wi-Fi than modern architecture. The following interview has been edited for length and clarity.
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Mist Systems
Published By: Progress Software     Published Date: Feb 03, 2010
Enterprises invest in packaged applications, development systems, testing, services oriented architectures, middleware and analytics to align process automation with business cycles. When IT is successful in this alignment, cycles accelerate and we see improvements in business flexibility that we now take for granted.
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bpm, progress, cep, navigation systems, idc, middleware, analytics, application performance management
    
Progress Software
Published By: HP - Intel® Xeon® processors     Published Date: Nov 07, 2012
This ESG Lab Validation documents the hands-on testing of an HP VirtualSystem for Microsoft solution that leverages the Microsoft Private Cloud Fast Track reference architecture.
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virtualization, converged infrastructure, cloud computing, convergence, mission-critical applications, servers, cloud, it infrastructure
    
HP - Intel® Xeon® processors
Published By: FireEye     Published Date: Feb 28, 2014
Organizations face a new breed of cyber attacks that easily thwart traditional defenses. These advanced attacks are targeted. They are persistent. And they are devastatingly effective at breaching your systems and stealing your sensitive data. This paper examines: The limitations of existing security solutions; Several security architectures, including sandbox-based products; An architecture built from the ground up to truly protect against today's advanced attacks.
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fireeye, persistent threats, advanced attacks, data centers, cyber-attacks, speed of detection, accuracy of detection, small businesses
    
FireEye
Published By: HP     Published Date: Nov 05, 2014
In this ESG white paper, the capabilities and common characteristics of flash implementations are categorized as “bronze”-, “silver”-, and “gold”-type approaches, depending on the degree to which they enable fully featured storage systems. It evaluates how HP’s storage delivers the basics and follows with a series of flash-specific optimizations and advances that we’ll call “gold standard” flash capabilities, after which it hints at HP’s vision of the future for their flash storage architecture. Throughout the paper, the importance of both IT architecture and business implications is emphasized. Download this whitepaper now.
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data center, change management, data management, storage space, storage criteria, storeserv, tier-1, market report
    
HP
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