data management

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By: IBM     Published Date: Sep 02, 2014
This book examines data storage and management challenges and explains software-defined storage, an innovative solution for high-performance, cost-effective storage using the IBM General Parallel File System (GPFS).
Tags : ibm, software storage for dummies
     IBM
By: IBM     Published Date: Sep 02, 2014
Life Sciences organizations need to be able to build IT infrastructures that are dynamic, scalable, easy to deploy and manage, with simplified provisioning, high performance, high utilization and able to exploit both data intensive and server intensive workloads, including Hadop MapReduce. Solutions must scale, both in terms of processing and storage, in order to better serve the institution long-term. There is a life cycle management of data, and making it useable for mainstream analyses and applications is an important aspect in system design. This presentation will describe IT requirements and how Technical Computing solutions from IBM and Platform Computing will address these challenges and deliver greater ROI and accelerated time to results for Life Sciences.
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     IBM
By: IBM     Published Date: Sep 02, 2014
With tougher regulations and continuing market volatility, financial firms are moving to active risk management with a focus on counterparty risk. Firms are revamping their risk and trading practices from top to bottom. They are adopting new risk models and frameworks that support a holistic view of risk. Banks recognize that technology is critical for this transformation, and are adding state-of-the-art enterprise risk management solutions, high performance data and grid management software, and fast hardware. Join IBM Algorithmics and IBM Platform Computing to gain insights on this trend and on technologies for enabling active "real-time" risk management.
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     IBM
By: IBM     Published Date: May 20, 2015
Join IBM and Nuance Communications Inc. to learn how Nuance uses IBM Elastic Storage to improve the power of their voice recognition applications by managing storage growth, cost and complexity while increasing performance and data availability. View the webcast to learn how you can: · Lower data management costs through policy driven automation and tiered storage management · Manage and increase storage agility through software defined storage Remove data related bottlenecks to deliver application performance
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     IBM
By: IBM     Published Date: May 20, 2015
Every day, the world creates 2.5 quintillion bytes of data and businesses are realizing tangible results from investments in big data analytics. IBM Spectrum Scale (GPFS) offers an enterprise class alternative to Hadoop Distributed File System (HDFS) for building big data platforms and provides a range of enterprise-class data management features. Spectrum Scale can be deployed independently or with IBM’s big data platform, consisting of IBM InfoSphere® BigInsights™ and IBM Platform™ Symphony. This document describes best practices for deploying Spectrum Scale in such environments to help ensure optimal performance and reliability.
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     IBM
By: IBM     Published Date: May 20, 2015
According to our global study of more than 800 cloud decision makers and users are becoming increasingly focused on the business value cloud provides. Cloud is integral to mobile, social and analytics initiatives – and the big data management challenge that often comes with them and it helps power the entire suite of game-changing technologies. Enterprises can aim higher when these deployments are riding on the cloud. Mobile, analytics and social implementations can be bigger, bolder and drive greater impact when backed by scalable infrastructure. In addition to scale, cloud can provide integration, gluing the individual technologies into more cohesive solutions. Learn how companies are gaining a competitive advanatge with cloud computing.
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     IBM
By: IBM     Published Date: Sep 16, 2015
A fast, simple, scalable and complete storage solution for today’s data-intensive enterprise IBM Spectrum Scale is used extensively across industries worldwide. Spectrum Scale simplifies data management with integrated tools designed to help organizations manage petabytes of data and billions of files—as well as control the cost of managing these ever-growing data volumes.
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     IBM
By: RedPoint     Published Date: Sep 22, 2014
Enterprises can gain serious traction by taking advantage of the scalability, processing power and lower costs that Hadoop 2.0/YARN offers. YARN closes the functionality gap by opening Hadoop to mature enterprise-class data management capabilities. With a lot of data quality functionality left outside of Hadoop 1, and a lot of data inside HDFS originating outside the enterprise, the quality of the data residing in the Hadoop cluster is sometimes as stinky as elephant dung. Some of the topics discussed in this paper include: • The key features, benefits and limitations of Hadoop 1.0 • The benefit of performing data standardization, identity resolution, and master data management inside of Hadoop. • The transformative power of Hadoop 2.0 and its impact on the speed and cost of accessing, cleansing and delivering high-quality enterprise data. Download this illuminating white paper about what YARN really means to the world of big data management.
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     RedPoint
By: RedPoint     Published Date: Sep 22, 2014
The emergence of YARN for the Hadoop 2.0 platform has opened the door to new tools and applications that promise to allow more companies to reap the benefits of big data in ways never before possible with outcomes possibly never imagined. By separating the problem of cluster resource management from the data processing function, YARN offers a world beyond MapReduce: less encumbered by complex programming protocols, faster, and at a lower cost. Some of the topics discussed in this paper include: • Why is YARN important for realizing the power of Hadoop for data integration, quality and management? • Benchmark results of MapReduce vs. Pig vs. visual “data flow” design tools • The 3 key features of YARN that solve the complex problems that prohibit businesses from gaining maximum benefit from Hadoop. Download this paper to learn why the power of Hadoop 2.0 lies in enabling applications to run inside Hadoop, without the constraints of MapReduce.
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     RedPoint
By: RedPoint     Published Date: Nov 10, 2014
Adoption of Hadoop by data-driven organizations is exploding. Hadoop’s potential cost effectiveness and facility for accepting unstructured data is making it central to modern, “Big Data” architectures. The advancements in Hadoop 2.0 increase the technology’s promise to an even greater extent. But with these opportunities also come challenges and adoption hurdles that make getting the most out of Hadoop easier said than done. Read on as we review some Hadoop basics, highlight some of the adoption challenges that exist and explain how RedPoint Data Management for Hadoop helps organizations accelerate their work with Hadoop.
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     RedPoint
By: IBM     Published Date: Nov 14, 2014
Every day, the world creates 2.5 quintillion bytes of data and businesses are realizing tangible results from investments in big data analytics. IBM Spectrum Scale (GPFS) offers an enterprise class alternative to Hadoop Distributed File System (HDFS) for building big data platforms and provides a range of enterprise-class data management features. Spectrum Scale can be deployed independently or with IBM’s big data platform, consisting of IBM InfoSphere® BigInsights™ and IBM Platform™ Symphony. This document describes best practices for deploying Spectrum Scale in such environments to help ensure optimal performance and reliability.
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     IBM
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: 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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     IBM
By: Intel     Published Date: Aug 06, 2014
Around the world and across all industries, high-performance computing is being used to solve today’s most important and demanding problems. More than ever, storage solutions that deliver high sustained throughput are vital for powering HPC and Big Data workloads. Intel® Enterprise Edition for Lustre* software unleashes the performance and scalability of the Lustre parallel file system for enterprises and organizations, both large and small. It allows users and workloads that need large scale, high- bandwidth storage to tap into the power and scalability of Lustre, but with the simplified installation, configuration, and monitoring features of Intel® Manager for Lustre* software, a management solution purpose-built for the Lustre file system.Intel ® Enterprise Edition for Lustre* software includes proven support from the Lustre experts at Intel, including worldwide 24x7 technical support. *Other names and brands may be claimed as the property of others.
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     Intel
By: Dell and Intel®     Published Date: Aug 24, 2015
To extract value from an ever-growing onslaught of data, your organization needs next-generation data management, integration, storage and processing systems that allow you to collect, manage, store and analyze data quickly, efficiently and cost-effectively. That’s the case with Dell| Cloudera® Apache™ Hadoop® solutions for big data. These solutions provide end-to-end scalable infrastructure, leveraging open source technologies, to allow you to simultaneously store and process large datasets in a distributed environment for data mining and analysis, on both structured and unstructured data, and to do it all in an affordable manner.
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     Dell and Intel®
By: Adaptive Computing     Published Date: Feb 27, 2014
Big data applications represent a fast-growing category of high-value applications that are increasingly employed by business and technical computing users. However, they have exposed an inconvenient dichotomy in the way resources are utilized in data centers. Conventional enterprise and web-based applications can be executed efficiently in virtualized server environments, where resource management and scheduling is generally confined to a single server. By contrast, data-intensive analytics and technical simulations demand large aggregated resources, necessitating intelligent scheduling and resource management that spans a computer cluster, cloud, or entire data center. Although these tools exist in isolation, they are not available in a general-purpose framework that allows them to inter operate easily and automatically within existing IT infrastructure.
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     Adaptive Computing
By: Aberdeen     Published Date: Jun 17, 2011
Download this paper to learn the top strategies leading executives are using to take full advantage of the insight they receive from their business intelligence (BI) systems - and turn that insight into a competitive weapon.
Tags : aberdeen, michael lock, data-driven decisions, business intelligence, public sector, analytics, federal, state, governmental, decisions, data management
     Aberdeen
By: Avanade DACH     Published Date: May 08, 2018
In this six-step guide, we aim to help you solve your data challenges to prepare for advanced analytics, cognitive computing, machine learning and the resulting benefits of AI. We’ll show you how to get your data house in order, scale beyond the proof of concept stage, and develop an agile approach to data management. By continually repeating the steps in this guide, you’ll sharpen your data and shape it into a truly transformational business asset. You’ll be able to overcome some of the most common business problems, and work toward making positive changes: • Improve customer satisfaction • Reduce equipment outages • Increase marketing campaign ROI • Minimize fraud loss • Improve employee retention • Increase accuracy for financial forecasts
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     Avanade  DACH
By: Dell PC Lifecycle     Published Date: May 15, 2018
Windows Server 2016 is an important release in enabling IT to deliver on the promise of the third platform. It provides a path to a seamless, integrated cloud environment—incorporating public, private and hybrid models—with the software-defined data center as the hub. In migrating to this next-generation data center model, it is essential that IT leaders choose the right partner for the compute platform, as well as storage, networking and systems management
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     Dell PC Lifecycle
By: Google Apigee     Published Date: Jun 08, 2018
A must-read for IT professionals that provides a comprehensive analysis of the API management marketplace and evaluates 22 vendors across 15 essential criteria. APIs are the de-facto standard for building and connecting modern applications. But securely delivering, managing and analyzing APIs, data and services, both inside and outside an organization, is complex. And it’s getting even more challenging as enterprise IT environments grow dependent on combinations of public, private and hybrid cloud infrastructures. Choosing the right APIs can be critical to a platform’s success. Likewise, full lifecycle API management can be a key ingredient in running a successful API-based program. Tools like Gartner’s Magic Quadrant for Full Life Cycle API Management help enterprises evaluate these platforms so they can find the right one to fit their strategy and planning. Apigee is pleased to offer you a complimentary copy of the Gartner report. Access in-depth evaluations of API managemen
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     Google Apigee
By: IBM     Published Date: Apr 03, 2018
Can your database systems handle data growth and keep up with performance requirements? Here are six reasons to change.
Tags : database systems, data management, hybrid data
     IBM
By: IBM     Published Date: Apr 03, 2018
This paper gives key considerations when making a strategic commitment to a database platform.
Tags : data management, cloud, database platform
     IBM
By: IBM     Published Date: Apr 03, 2018
The next generation of IBM Db2 helps organizations get more value from their big data to improve their IT economics.
Tags : ibm, data management, db2
     IBM
By: Datastax     Published Date: May 14, 2018
" For any business that wants to successfully compete in today’s digital economy, it is not a question of if but rather how much of their business will be done with cloud applications. A cloud application is one with many endpoints including browsers, mobile devices, and/or machines that are geographically distributed. The application is intensely transactional (high velocity reads and/or writes), always available, and instantaneously responsive no matter the number of users or machines using the application. Download this free white paper and explore how DataStax customers are delivering real-time value at epic scale with their cloud applications. Explore the core database requirements that make businesses successful with cloud applications, which include continuous availability, linear scale, and geographic distribution."
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     Datastax
By: Datastax     Published Date: May 14, 2018
The data management practices of old will no longer work. If you’re still trying to use a centralized approach, you are probably finding it difficult to keep up with the real-time demands of the Right-Now Economy. This special Gartner report describes the main drivers for modernizing data management — operational efficiency and analytics — and explains why balancing connecting data with collecting data will be a fundamental requirement for modern data management moving forward.
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     Datastax
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