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By: IBM     Published Date: Nov 14, 2014
Join Gartner, Inc. and IBM Platform Computing for an informative webinar where you will learn how to combine best of breed analytic solutions to provide a low latency, shared big data infrastructure. This helps government IT departments make faster decisions by analyzing massive amounts of data, improving security, detecting fraud, enabling faster decisions and saving cost by optimizing and sharing your existing infrastructure.
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By: IBM     Published Date: Nov 14, 2014
Platform Symphony is an enterprise-class server platform that delivers low-latency, scaled-out MapReduce workloads. It supports multiple applications running concurrently so that organizations can increase utilization across all resources resulting in a high return on investment.
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By: IBM     Published Date: Nov 14, 2014
Platform HPC enables HPC customers to side-step many overhead cost and support issues that often plague open-source environments and enable them to deploy powerful, easy to use clusters.
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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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By: IBM     Published Date: Feb 13, 2015
This demonstration shows how an organization using IBM Platform Computing workload managers can easily and securely tap resources in the IBM SoftLayer public cloud to handle periods of peak demand and reduce total IT infrastructure costs.
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By: IBM     Published Date: Feb 13, 2015
To quickly and economically meet new and peak demands, Platform LSF (SaaS) and Platform Symphony (SaaS) workload management as well as Elastic Storage on Cloud data management software can be delivered as a service, complete with SoftLayer cloud infrastructure and 24x7 support for technical computing and service-oriented workloads. Watch this demonstration to learn how the IBM Platform Computing Cloud Service can be used to simplify and accelerate financial risk management using IBM Algorithmics.
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By: IBM     Published Date: Feb 13, 2015
Software defined storage is enterprise class storage that uses standard hardware with all the important storage and management functions performed in intelligent software. Software defined storage delivers automated, policy-driven, application-aware storage services through orchestration of the underlining storage infrastructure in support of an overall software defined environment.
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By: IBM     Published Date: Feb 13, 2015
IBM® has created a proprietary implementation of the open-source Hadoop MapReduce run-time that leverages the IBM Platform™ Symphony distributed computing middleware while maintaining application-level compatibility with Apache Hadoop.
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By: IBM     Published Date: Feb 13, 2015
In the age of "big data," it's essential for any organization to know how to analyze and manage their ever increasing stores of information. Packed with everything you need to know about Hadoop analytics, this handy guide provides you with a solid understanding of the critical big data concepts and trends, and suggests ways for you to revolutionize your business operations through the implementation of cost-effective, high performance Hadoop technology.
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By: IBM     Published Date: Feb 13, 2015
Organizations of all sizes need help building clusters and grids to support compute- and data-intensive application workloads. Read how the Hartree Centre is building several high-performance computing clusters to support a variety of research projects.
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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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By: IBM APAC     Published Date: Mar 06, 2019
Achieve superior control and performance across multicloud environments with IBM Multicloud Manager. With a multicloud strategy, it can become time-consuming, expensive and difficult to manage environments as you contend with scattered visibility, security and workloads across multiple Kubernetes clusters and clouds. IBM Multicloud Manager integrates all your environments in a single view that gives you optimal control over how you see, govern and automate everything.
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     IBM APAC
By: IBM APAC     Published Date: Mar 06, 2019
A multicloud world is quickly becoming the new normal for many enterprises. Learn how the multicloud world is changing the face of IT. Understanding cloud environments and making decisions about multicloud management can be complex. IBM has identified ten key pain points and related best practices that help organizations successfully navigate these transformations.
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     IBM APAC
By: IBM APAC     Published Date: Mar 06, 2019
The Forrester Study on cost savings and business benefits enabled by Watson Studio and Watson Knowledge Catalog. Watson Studio provides a suite of tools for data scientists, application developers, and subject matter experts to collaboratively and easily work with data and use that data to build, train and deploy machine learning models at scale. The Forrester provides readers a framework to evaluate the potential financial impact of the Watson Studio and Watson Knowledge Catalog investment on their organizations.
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     IBM APAC
By: IBM APAC     Published Date: Mar 06, 2019
A single environment to build, train, and deploy machine-learning and deep learning models. Take advantage of machine learning and AI to analyze your data. Catalog your data to make it easy to find. All applications are free and without time limit!
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     IBM APAC
By: IBM APAC     Published Date: Mar 06, 2019
The 2019 IBM X-Force Threat Intelligence Index looks back at the threats, tactics, and trends that emerged in 2018 based on insights from IBM X-Force Security Research Team. Deriving data and insights from security clients, incident response services and penetration testing engagements, the IBM X-Force Threat Intelligence Index 2019 report outlines the most prominent threats and provides key insights into various industries, attack tactics, and major vulnerabilities that emerged during the year.
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     IBM APAC
By: IBM APAC     Published Date: Mar 06, 2019
A cyber resilient enterprise is one that can prevent, detect, contain and recover from a myriad of serious threats against data, applications and IT infrastructure. The Ponemon Institute and IBM surveyed more than 2,848 IT and IT security professionals from around the world and released the findings of the third annual study on the importance of cyber resilience for a strong security posture.
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     IBM APAC
By: Group M_IBM Q119     Published Date: Jan 10, 2019
It is breathing life into our existing energy resources and creating new opportunities. Better use of data has visible, tangible and immediate results. It is helping energy companies become safer, more reliable and more efficient. This is good for both our wallets and our planet. For more information visit: www.ibm.com/energy or watch our webinar here
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By: Group M_IBM Q119     Published Date: Jan 10, 2019
Download Infographic Now!
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By: Group M_IBM Q119     Published Date: Feb 21, 2019
Mobile marketing platforms facilitate direct marketing on mobile devices by enabling mobile campaign management and activation. These platforms can operate as stand-alone solutions; however, they typically integrate with, or operate alongside, CRM, location/data management, and multichannel marketing hub (MMH) or email marketing platforms. Regardless of how a mobile marketing platform gets deployed, the native or third-party analytics supporting its audience targeting, campaign sequencing, personalization and performance measurement capabilities form the foundation of this technology.
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By: Group M_IBM Q119     Published Date: Feb 21, 2019
At IBM Watson Marketing, we believe deeply in this practice and have dedicated a large effort to provide some of this critical data to marketers. The newest IBM Watson Marketing annual report of marketing benchmarks is bigger and better than ever with mobile marketing metrics data in addition to email marketing metrics. This year’s report includes traditional benchmark metrics such as email marketing open, click-through and unsubscribe rates, as well as email client and device data and engagement/read rates. New this year to the report are delivery and message frequency metrics for SMS and open and clickthrough rates for mobile push messages.
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By: Group M_IBM Q119     Published Date: Mar 04, 2019
One of the biggest changes facing organizations making purchasing and deployment decisions about analytic databases — including relational data warehouses — is whether to opt for a cloud solution. A couple of years ago, only a few organizations selected such cloud analytic databases. Today, according to a 2016 IDC survey, 56% of large and midsize organizations in the United States have at least one data warehouse or mart deploying in the cloud.
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By: Group M_IBM Q119     Published Date: Mar 04, 2019
There can be no doubt that the architecture for analytics has evolved over its 25-30 year history. Many recent innovations have had significant impacts on this architecture since the simple concept of a single repository of data called a data warehouse. First, the data warehouse appliance (DWA), along with the advent of the NoSQL revolution, selfservice analytics, and other trends, has had a dramatic impact on the traditional architecture. Second, the emergence of data science, realtime operational analytics, and self-service demands has certainly had a substantial effect on the analytical architecture.
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By: Group M_IBM Q119     Published Date: Mar 11, 2019
This report explores a new breed of data warehouse that can operate in a world of legacy on-premise systems while exploiting the potential of cutting edge technologies and deployment styles
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By: Group M_IBM Q119     Published Date: Mar 11, 2019
In this report, we'll analyze the many challenges that organizations face when it comes to building and managing a modern IT infrastructure
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     Group M_IBM Q119
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