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analytic workload

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Published By: Citrix Systems     Published Date: Nov 13, 2018
Discover why ninety-four percent of organizations surveyed are already modifying, overhauling, or reassessing their network infrastructure to facilitate application delivery in hybrid- and multi-cloud environments. Read this e-book to learn why you should re-architect your network infrastructure to optimize application delivery: 1. Ensure end-to-end network visibility for your operations 2. Gain real-time analytics for application optimization and uptime 3. Scale your application infrastructure according to workload demand Read the e-book today to find out all six must-haves for application delivery in the cloud.
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Citrix Systems
Published By: Hewlett Packard Enterprise     Published Date: Aug 02, 2017
In midsize and large organizations, critical business processing continues to depend on relational databases including Microsoft® SQL Server. While new tools like Hadoop help businesses analyze oceans of Big Data, conventional relational-database management systems (RDBMS) remain the backbone for online transaction processing (OLTP), online analytic processing (OLAP), and mixed OLTP/OLAP workloads.
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database usage, database management, server usage, data protection
    
Hewlett Packard Enterprise
Published By: Dell Server     Published Date: Aug 07, 2018
Today’s digital businesses are managed using critical business analyses that provide far greater insight into the business and how to maximize results. However, these high-value applications that use the latest software tools demand far more from IT infrastructure, as they utilize an order of magnitude more data and demand more compute resources than legacy applications. Legacy systems are no longer capable of meeting the present and future needs of the organization. Forward-thinking IT organizations are developing new infrastructure strategies to better support high-value analytics workloads with Dell EMC PowerEdge Servers powered by Intel® Xeon® Platinum processor.
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Dell Server
Published By: TIBCO Software APAC     Published Date: May 31, 2018
With data the new competitive battleground, businesses that take advantage of their data will be the leaders; those that do not will fall behind. But gaining an advantage is a more difficult technical challenge than ever because your business requirements are ever-changing, your analytic workloads are exploding, and your data is now widely-distributed across on-premises, big data, the Internet of Things, and the Cloud. TIBCO® Data Virtualization is data virtualization software that lets you integrate data at big data scale with breakthrough speed and cost effectiveness. With TIBCO Data Virtualization, you can build and manage virtualized views / data services that access, transform, and deliver the data your business requires to accelerate revenue, reduce costs, lessen risk, improve compliance, and more.
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TIBCO Software APAC
Published By: CA Technologies     Published Date: Jul 20, 2017
e-book which lays out the case for machine learning and artificial intelligence for mainframe operational analytics. The mainframe is now part of a highly complex connected ecosystem driving trillions of mobile and web transactions critical to the functioning of the application economy. The emergence of new workloads and apps on the mainframe means that the status quo isn’t enough when it comes to Mainframe management. IT professionals alone – whether mainframe skilled or not – simply can’t keep up with the onslaught of performance alerts, false alarms. Machine learning deliver mainframe intelligence a more proactive and automated approach to handle this challenge.
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CA Technologies
Published By: TIBCO Software APAC     Published Date: Aug 13, 2018
Despite being knowledgeable about their industry and experienced in running their organizations, the majority of business users lack expertise in analytics and visualization techniques—but that doesn't stop them from wanting to have a go. But making tools easier and more widely accessible is only part of the answer. A better approach is to work both sides of the gap. To make tools that can empower business users to discover and unlock value in their data—and that extend capabilities for experts, so they can share the analytics workload, improve efficiency, and focus on higher level work.
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TIBCO Software APAC
Published By: TIBCO Software APAC     Published Date: May 31, 2018
Ask the average business user what they know about Business Intelligence (BI) and data analytics, and most will claim to understand the concepts. Few, however, will profess to know how analytics works or to have the skills needed to put it into practice. Despite being knowledgeable about their industry and experienced in running their organizations, the majority of business users lack expertise in analytics and visualization techniques—but that doesn’t stop them from wanting to have a go. This situation has led to ease of use and accessibility becoming the main focus for recent updates from all the leading BI vendors—but making tools easier and more widely accessible is only part of the answer. A better approach is to work both sides of the gap. To make tools that can empower business users to discover and unlock value in their data—and that extend capabilities for experts, so they can share the analytics workload, improve efficiency, and focus on higher level work. Unfortunately, the
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TIBCO Software APAC
Published By: IBM     Published Date: Jul 21, 2016
IBM's recently released DB2 version 11.1 for Linux, Unix and Windows (LUW) is a hybrid database that IBM says can handle transactional and analytic workloads thanks to its BLU Acceleration technology, which features an in-memory column store for analytical workloads that can scale across a massively parallel cluster.
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ibm, db2. analytics, mpp, data wharehousing
    
IBM
Published By: IBM     Published Date: Apr 19, 2018
This paper presents a cost/benefit case for two industry-leading database platforms for analytics workloads.
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db2, data migration, ibm, oracle
    
IBM
Published By: IBM     Published Date: Aug 08, 2018
An IBM Cloud configuration completed a big data analytics workload in less time and with greater throughput than an AWS solution
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IBM
Published By: Juniper Networks     Published Date: Feb 05, 2018
Innovative data-driven strategies are enabling organizations to connect with customers and increase operational efficiency as never before. These new initiatives are built on a multitude of applications, such as big-data analytics, supply chain, and factory automation. On average, organizations are now 53% digital as they create new ways of operating and growing their businesses, according to the Computerworld 2017 Forecast Study. As part of this transformation, enterprises rely increasingly on multivendor, multicloud environments that mix on-premise, private, and public cloud services and workloads. This shift is causing enterprises to increase network capacity; 55% of enterprises in the Computerworld study expect to add network bandwidth in the next 12 months.
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security, automation, savings, technology, cloud
    
Juniper Networks
Published By: IBM APAC     Published Date: Oct 16, 2018
Modern AI, HPC and analytics workloads are driving an ever-growing set of data intensive challenges that can only be met with accelerated infrastructure. Designed for the AI era and architected for the modern analytics and AI workloads, Power Systems AC922 delivers unprecedented speed for the AI Era like up to 5.6 times as much bandwidth, which results from The only architecture enabling NVLink between CPUs and GPUs a variety of next-generation I/O architectures: PCIe gen4, CAPI 2.0, OpenCAPI and NVLINK. Proven simplified deep-learning deployment and AI performance
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IBM APAC
Published By: Teradata     Published Date: Feb 26, 2013
This survey and research report discusses shifts in the data management landscape and the movement to align data with operational and analytical workloads creating the best possible unified data architecture platform. Read on to learn more.
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big data, survey report, data management, landscape, movement, align data, operational and analytics workloads, business intelligence, terdata, data center
    
Teradata
Published By: Vertica     Published Date: Aug 16, 2010
The Vertica Analytic Database is the only database built from scratch to handle today's heavy business intelligence workloads. In customer benchmarks, Vertica has been shown to manage terabytes of data running on extraordinarily low-cost hardware and answers queries 50 to 200 times faster than competing row-oriented databases and specialized analytic hardware. This document summarizes the key aspects of Vertica's technology that enable such dramatic performance benefits, and compares the design of Vertica to other popular relational systems.
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vertica, ec2, elastic, cloud computing, workflow, benchmark, projections, ad-hoc, business intelligence, cloud, cloudbased applications, analytic, saas, dbms, mpp, business analytics, linux, application integration, analytical applications, data integration
    
Vertica
Published By: Vertica     Published Date: Feb 20, 2010
For over a decade, IT organizations have been plagued by high data warehousing costs, with millions of dollars spent annually on specialized, high-end hardware and DBA personnel overhead for performance tuning. The root cause: using data warehouse database management (DBMS) software, like Oracle and SQLServer that were designed 20-30 years ago to handle write-intensive OLTP workloads, not query-intensive analytic workloads.
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vertica, ec2, cdr, elastic, saas, cloud computing, data management, ad-hoc, business intelligence, cloud, cloudbased applications, analytic, saas, dbms, mpp, best practices, business analytics, linux, application integration, analytical applications
    
Vertica
Published By: Amazon Web Services     Published Date: Nov 28, 2018
Financial institutions run on data: collecting it, analyzing it, delivering meaningful insights, and taking action in real time. As data volumes increase, organizations demand a scalable analytics platform that can meet the needs of data scientists and business users alike. However, managing an on-premises analytics environment for a large and diverse user base can become time-consuming, costly, and unwieldy. Tableau Server on Amazon Web Services (AWS) is helping major Financial Services organizations shift data visualization and analytics workloads to the cloud. The result is fewer hours spent on manual work and more time to ask deeper questions and launch new data analyses, with easily-scalable support for large numbers of users. In this webinar, you’ll hear how one major asset management company made the shift to cloud data visualization with Tableau Server on AWS. Discover lessons learned, best practices tailored to Financial Services organizations, and starting tactics for scalable analytics on the cloud.
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Amazon Web Services
Published By: IBM     Published Date: Nov 06, 2012
In this Research Report, Clabby Analytics describes why we believe that firms need to focus first and foremost on organization data - while, at the same time, designing a support infrastructure that can address user QoS needs to scale to meet needs.
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ibm, integrated infrastructure, business analytics, qos, infrastructure, analytic workload, data management, data center
    
IBM
Published By: IBM     Published Date: May 07, 2013
Knowing the potential benefits of cloud computing, IBM implemented this technology for six workloads—development and test, analytics, storage, collaboration, desktop and production application. And the results have yielded significant financial and operational improvements. IBM shares some key insights through this report, learned after a successful move to cloud, including different ways in which each workload benefited. It also reveals how adopting cloud enabled significant improvements in efficiency, innovation, service and support levels. Download: Success in the cloud: Why workload matters.
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success, cloud, improvements, efficiency, innovation, service, support
    
IBM
Published By: IBM     Published Date: May 02, 2014
These traditional analytical systems are often based on a classic pattern where data from multiple operational systems is captured, cleaned, transformed and integrated before loading it into a data warehouse.
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ibm, big data platform, architecting big data, analytics, intelligent business strategies, data complexity, data types, workload growth, workload complexity, big data analytic applications, operational decisions, multi-structured data, querying data, scalable data management, analytical ecosystem, hadoop solutions, it management, data management, best practices, business intelligence
    
IBM
Published By: Cisco     Published Date: Jul 11, 2016
Today's datacenter networks must better adapt to and accommodate business-critical application workloads. Datacenters will have to increasingly adapt to virtualized workloads and to the ongoing enterprise transition to private and hybrid clouds. Pressure will mount on datacenters not only to provide increased bandwidth for 3rd Platform applications such as cloud and data analytics but also to deliver the agility and dynamism necessary to accommodate shifting traffic patterns (with more east-west traffic associated with server-to-server flows, as opposed to the traditional north-south traffic associated with client/server computing). Private cloud and legacy applications will also drive daunting bandwidth and connectivity requirements. This Technology Spotlight examines the increasing bandwidth requirements in enterprise datacenters, driven by both new and old application workloads, cloud and noncloud in nature. It also looks at how Cisco is meeting the bandwidth challenge posed by 3rd
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Cisco
Published By: IBM     Published Date: Jan 09, 2014
In this Advisory, Clabby Analytics looks more closely at the importance of implementing an integrated infrastructure — and its relationship to business analytics. The paper will examine the business analytics workloads, discuss how these workloads put different demands on the underlying systems and infrastructure, and provide guidance designing an integrated business analytics environment that will provide organizations with high performance, resiliency, and a scalable growth path.
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analytics, power 7, big data, power systems, virtualization, ibm, ibm power systems, infrastructure, storage, integrated infrastructure, clabby analytics, three maxims, buying criteria, analytics buying, system storage, analytical applications, cloud computing, power and cooling
    
IBM
Published By: IBM     Published Date: Apr 18, 2014
This IDC paper discusses the critical role of hardware infrastructure in business analytics deployments, citing best practices, the IDC's decision framework, and four client case studies - Wellpoint, Vestas, AXTEL, and Miami-Dade County. IDC's recommendation is that "infrastructure cannot — and should not — be an afterthought". Hardware infrastructure and software requirements must be determined in parallel to maximize the success of business analytics projects.
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ibm, business analytics, deployment, hardware, infrastructure, business analytics solutions, workload, server hardware
    
IBM
Published By: IBM     Published Date: Jul 07, 2014
In this Advisory, Clabby Analytics looks more closely at the importance of implementing an integrated infrastructure — and its relationship to business analytics. The paper will examine the business analytics workloads, discuss how these workloads put different demands on the underlying systems and infrastructure, and provide guidance designing an integrated business analytics environment that will provide organizations with high performance, resiliency, and a scalable growth path.
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ibm, business analytics, integrated infrastructure, workload, infrastructure, business analytics environment, integrated business analytics, resiliency, scalability, business intelligence
    
IBM
Published By: Cisco     Published Date: Dec 21, 2016
Today's datacenter networks must better adapt to and accommodate business-critical application workloads. Datacenters will have to increasingly adapt to virtualized workloads and to the ongoing enterprise transition to private and hybrid clouds. Pressure will mount on datacenters not only to provide increased bandwidth for 3rd Platform applications such as cloud and data analytics but also to deliver the agility and dynamism necessary to accommodate shifting traffic patterns (with more east-west traffic associated with server-to-server flows, as opposed to the traditional north-south traffic associated with client/server computing). Private cloud and legacy applications will also drive daunting bandwidth and connectivity requirements. This Technology Spotlight examines the increasing bandwidth requirements in enterprise datacenters, driven by both new and old application workloads, cloud and noncloud in nature. It also looks at how Cisco is meeting the bandwidth challenge posed by 3rd
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Cisco
Published By: NEC     Published Date: Aug 12, 2014
NEC has introduced the Express5800/A2000 Series Servers to accommodate enterprise application demands with peak server reliability, availability, and serviceability. The new server architecture and NEC engineering functionality align well with many of the most important IT priorities in 2014, including virtualization, big data and advanced data analytics. With the Express5800/A2000 Servers, NEC has the opportunity to educate application owners and work with system integrators to drive awareness and ultimately investment in its new server platform, which will help drive customer value. In this white paper, you will learn how these next-generation servers from NEC are ready to accommodate some of today’s demanding workloads.
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servers, virtualization, customer value, analytics, application owners, system integrators, big data, reliability, enterprise, availability, serviceability, processor, architecture, express, stress, data management, productivity
    
NEC
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