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By: Equinix     Published Date: Mar 26, 2015
Enterprises grapple with a host of challenges that are spurring the creation of hybrid clouds: collections of computing infrastructure spread across multiple data centers and multiple cloud providers. This new concept often provokes uncertainty, which must be addressed head on. As more applications and computing resources move to the cloud, enterprises will become more dependent on cloud vendors, whether the issue is access, hosting, management, or any number of other services. Cloud consumers want to avoid vendor lock-in—having only one cloud provider. They want to know that they will have visibility into data and systems across multiple platforms and providers. They want to be able to move servers and storage around without a negative impact on application availability. The good news is that more solutions become available every day, but with a learning curve and numerous management challenges and considerations. This CITO Research paper provides advice for managers about how to c
Tags : hybrid cloud, computing infrastructure, enterprises, storage, application availability, it management, data center
     Equinix
By: Fujitsu     Published Date: Dec 22, 2015
This whitepaper reveals the benefits of software defined storage, and hyper-scale data management in particular.
Tags : software defined storage, storage, data management, hyper-scale sds, sds
     Fujitsu
By: IBM Software     Published Date: Jul 28, 2010
See how plans, financial reports and scorecards can help you manage performance across all data sources.
Tags : ibm software, ibm cognos, performance manager demo, financial report, sales performance, sales force, pipeline, customer behavior
     IBM Software
By: IBM Software     Published Date: Jul 29, 2010
See how plans, financial reports and scorecards can help you manage performance across all data sources.
Tags : ibm software, ibm cognos, performance manager demo, financial report, sales performance, sales force, pipeline, customer behavior
     IBM Software
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: IBM     Published Date: Dec 24, 2014
Organizations and intelligence agencies from a variety of industries and sectors face the same challenges when it comes to big data – the need to uncover actionable insights, with limited resources, with critical speed. But with the right intelligence solution, overwhelming data won’t be a challenge, rather, it becomes your resource to smarter, more effective decision making.
Tags : ibm, big data, insight analysis, big data analysis, intelligence solutions, advanced analytics, business decision making, it management
     IBM
By: Group M_IBM Q1'18     Published Date: Jan 04, 2018
IBM® InfoSphere® Big Match for Hadoop helps you analyze massive volumes of structured and unstructured customer data to gain deeper customer insights. It can enable fast, efficient linking of data from multiple sources to provide complete and accurate customer information—without the risks of moving data from source to source. The solution supports platforms running Apache Hadoop such as IBM Open Platform, IBM BigInsights, Hortonworks and Cloudera.
Tags : hadoop, infosphere, data, customer insights
     Group M_IBM Q1'18
By: IBM     Published Date: Feb 11, 2015
IBM® Operational Decision Manager Advanced brings together data from different sources to recognize meaningful trends and patterns. It empowers business users to define, manage and automate repeatable operational decisions. As a result, organizations can create and shape customer-centric business moments.
Tags : ibm, customer-centric business, operational manager, decision manager, business policies, it management, enterprise applications, data management
     IBM
By: IBM     Published Date: Oct 26, 2017
Many organizations face access management chaos. As applications and resources have spread across on-premise data centers and multiple cloud providers, users are often accessing these resources from anywhere and on multiple devices. These simultaneous trends have left access management systems fragmented and access polices inconsistent, resulting in an environment that is expensive to maintain and challenging to secure.
Tags : access management, integrated platform, cloud security, enterprise security, data security
     IBM
By: IBM     Published Date: May 30, 2008
Not all data is created equal, however, and deriving business value from information dispersed over many different sources means integrating, analyzing and optimizing heterogeneous types and sources of information throughout its lifecycle. Find out how, when deployed together in the same environment, IBM TotalStorage Productivity Center, IBM System Storage SAN Volume Controller and IBM Tivoli Storage Manager deliver the core technologies need to help customers tier their storage based on classes of service.
Tags : information lifecycle, information management, tivoli, storage management, leveraging information, ibm, ibm li, li campaign
     IBM
By: IBM Corporation     Published Date: Jun 30, 2011
The demonstrations included in this menu interface show how IBM Tivoli Provisioning Manager solutions can help you manage the complete life cycle of your data center and distributed resources from initial provisioning to patching and configuration maintenance to resource re-purposing or end of life.
Tags : energy management, tivoli, disaster prevention, infrastructure, bms, building management system, ecosystem, opc
     IBM Corporation
By: IBM     Published Date: Apr 18, 2014
For many enterprises System z is central to modern analytics because of the vast quantities or rich data stored upon it – not to mention excellent qualities of service. Carl Olofson, an IDC analyst looks, at the role of the mainframe in relation to big data, how it has become a hub for modern day analytics, its ability to integrate information from other sources to enhance business decisions and how it is positioned for the future. Download this paper and learn.
Tags : ibm, mainframe, platform, big data, analytics, big data and analytics, bda, big data technology
     IBM
By: Hewlett Packard Enterprise     Published Date: Jul 25, 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: 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: Group M_IBM Q119     Published Date: Jan 04, 2019
Digital transformation is poised to change the supply chain more profoundly than any other functional area and more dramatically than at any point in its history in terms of driving efficiency and resiliency to disruption. In the context of the challenges facing supply chains, both now and in the future, it becomes clear that the old ways of working will not suffice and that even best-in-class performance today is unlikely to be good enough in the future. It is the view of IDC that the supply chain must become a "thinking" supply chain, one that is intimately connected to all data sources, enabled with comprehensive and fast analytics, openly collaborative through cloud-based commerce networks, conscious of cyberthreats, and cognitively interwoven. According to IDC supply chain research, technology is emerging as a prime driver of change, particularly artificial intelligence, blockchain, and the Internet of Things (IoT).
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     Group M_IBM Q119
By: IBM     Published Date: Jan 19, 2017
The outcome of any big data analytics project, however, is only as good as the quality of the data being used. As big data analytics solutions have matured and as organizations have developed greater expertise with big data technologies he quality and trustworthiness of the data sources themselves are emerging as key concerns. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
Tags : ibm, analytics, ecm, data, big data, information governance, enterprise applications, data management
     IBM
By: HP and Intel ®     Published Date: May 02, 2013
It is very clear that datacenter managers need, in addition to server virtualization, the virtualization, pooling, and management of all the other resources that interoperate with their VMs. They require virtualized network interconnects and storage. They also need the tools to manage and automate these converged IT assets as an integrated datacenter system. This more agile system is the key to enabling the shift to a cloud-based infrastructure IT delivery model. Solution providers like HP are now addressing the need for more optimized and agile IT solutions. They are delivering virtualized storage, virtual application network (VAN) infrastructure, and the orchestration software to manage and automate all these ingredients as a single system. Read this whitepaper to learn more.
Tags : data center, virtualization, data center management, automation, agile, storage, van, virtual application network
     HP and Intel ®
By: Cisco     Published Date: Sep 15, 2015
IDC finds that leveraging data analytics in business decisions is becoming a top priority for an increasing number of companies. This in turn is placing new demands on IT organizations; the need is twofold: to manage new streams of unstructured data from sources such as social media and to speed response times to deliver real-time analytics.
Tags : sap, analytics, data, real-time, it management, enterprise applications
     Cisco
By: Exablox     Published Date: Jan 27, 2015
When it comes to the increasingly complex task of managing data storage, many small and midsize organizations face even greater challenges than large, global enterprises. Small and midsize companies have ever-increasing volumes of information to manage and secure, and they are confronting a number of difficulties when it comes to storage. Among the biggest hurdles: ›› Scaling storage as the business grows rapidly ›› Meeting the rising expense of data storage capacity ›› Dealing with the complexity of management and architecture ›› Devoting precious staff time managing storage and data backup Whereas larger organizations have significant IT budgets and staff to handle storage-related challenges, small and midsize companies lack the IT resources to dedicate to storage management. Fortunately, there are new approaches to data storage on the market that can help such companies address their data storage needs without requiring dedicated storage management resources, while at the same ti
Tags : scaling storage, data storage capacity, data backup, data protection, data management, exablox, oneblox
     Exablox
By: SAS     Published Date: Apr 25, 2017
Physicians and their patients, medical policy makers and licensing boards, pharmaceutical companies and pharmacies all must work together to stem the opioid epidemic and achieve the fundamental objectives of reducing addiction and deaths. With so many players and data sources, today’s information is partial, fragmented, and often not actionable. We don’t have the data to understand what’s happening, to adjust policy, and to motivate physicians and patients to change their behaviors. Better data and analytics can help develop better treatment protocols, both for pain in the first place and for remediation when patients are becoming dependent on the drugs.
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     SAS
By: Dell EMC & Intel     Published Date: Sep 06, 2018
Jusqu’à présent, les améliorations du datacenter se sont limitées à la réduction des coûts et à des solutions ponctuelles. La consolidation des serveurs, le Cloud computing, la virtualisation et l’implémentation de stockage Flash ont contribué à réduire la prolifération des serveurs, ainsi que les coûts de personnel et d’installations associés. Regroupant ressources de calcul, de stockage et de réseau au sein d’une même solution, les systèmes convergés se révèlent particulièrement efficaces dans la baisse des dépenses de personnel et de fonctionnement. Ces systèmes définis par logiciel (software-defined) exigent peu d’interventions humaines. Le code intégré dans le logiciel configure le matériel et automatise de nombreux processus autrefois manuels, ce qui réduit considérablement le risque d’erreurs humaines. Ensemble, ces technologies ont permis aux entreprises d’améliorer progressivement les processus et stratégies d’engagement client et de prestation de services.
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     Dell EMC & Intel
By: TriNet     Published Date: Jul 28, 2015
The future of HR lies in technological advances and implementation for businesses of all sizes.
Tags : hr technology, hr data, technology providers, hr trends, mobility, cloud data security, hr terminology, business performance management
     TriNet
By: IBM     Published Date: Apr 03, 2017
Predictive analytics is powerful. It can help drive significant improvement to an organization’s bottom line. Look for ways to use it to grow revenue, shrink costs and improve margins. Provide a platform that enables your data scientists to work efficiently using tools and algorithms they prefer. Enhance your analyses with internal and external data, structured and unstructured data. Then make the analytics accessible in order to reap the full benefits of these valuable analyses. Stay ahead of the curve in your market with predictive analytics, and give your organization a competitive advantage and an improved bottom line.
Tags : predictive analytics, analytics, data analytics, financial marketing, market analytics, data resources
     IBM
By: Nice Systems     Published Date: Feb 26, 2019
NICE WFM 7.0’s Forecaster unlocks a high level of transparency into interaction history, allowing you to centrally forecast, schedule and manage contacts between multiple locations and ensure that site- and enterpriselevel objectives are met. With more than two thousand customers and two million users depending on its unparalleled ability to fine-tune the most precise forecasts, Forecaster allows you to plan and respond to the peaks and valleys of customer history through automatic collection of key historical data from all types of contact sources: • Automatic call distributors (ACDs) • Outbound dialers • Multi-channel routing platforms • Back-office employee desktops Download today to learn more.
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     Nice Systems
By: Attunity     Published Date: Jan 14, 2019
This whitepaper explores how to automate your data lake pipeline to address common challenges including how to prevent data lakes from devolving into useless data swamps and how to deliver analytics-ready data via automation. Read Increase Data Lake ROI with Streaming Data Pipelines to learn about: • Common data lake origins and challenges including integrating diverse data from multiple data source platforms, including lakes on premises and in the cloud. • Delivering real-time integration, with change data capture (CDC) technology that integrates live transactions with the data lake. • Rethinking the data lake with multi-stage methodology, continuous data ingestion and merging processes that assemble a historical data store. • Leveraging a scalable and autonomous streaming data pipeline to deliver analytics-ready data sets for better business insights. Read this Attunity whitepaper now to get ahead on your data lake strategy in 2019.
Tags : data lake, data pipeline, change data capture, data swamp, hybrid data integration, data ingestion, streaming data, real-time data
     Attunity
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