data systems

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By: IBM     Published Date: Sep 02, 2014
Research teams using next-generation sequencing (NGS) technologies face the daunting challenge of supporting compute-intensive analysis methods against petabytes of data while simultaneously keeping pace with rapidly evolving algorithmic best practices. NGS users can now solve these challenges by deploying the Accelrys Enterprise Platform (AEP) and the NGS Collection on optimized systems from IBM. Learn how you can benefit from the turnkey IBM Application Ready Solution for Accelrys with supporting benchmark data.
Tags : ibm, accelrys, turnkey ngs solution
     IBM
By: IBM     Published Date: Sep 16, 2015
The IBM Spectrum Scale solution provided for up to 11x better throughput results than EMC Isilon for Spectrum Protect (TSM) workloads. Using published data, Edison compared a solution comprised of EMC® Isilon® against an IBM® Spectrum Scale™ solution. (IBM Spectrum Scale was formerly IBM® General Parallel File System™ or IBM® GPFS™, also known as code name Elastic Storage). For both solutions, IBM® Spectrum Protect™ (formerly IBM Tivoli® Storage Manager or IBM® TSM®) is used as a common workload performing the backups to target storage systems evaluated.
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     IBM
By: Storiant     Published Date: Mar 16, 2015
Read this new IDC Report about how today's enterprise datacenters are dealing with new challenges that are far more demanding than ever before. Foremost is the exponential growth of data, most of it unstructured data. Big data and analytics implementations are also quickly becoming a strategic priority in many enterprises, demanding online access to more data, which is retained for longer periods of time. Legacy storage solutions with fixed design characteristics and a cost structure that doesn't scale are proving to be ill-suited for these new needs. This Technology Spotlight examines the issues that are driving organizations to replace older archive and backup-and-restore systems with business continuity and always-available solutions that can scale to handle extreme data growth while leveraging a cloudbased pricing model. The report also looks at the role of Storiant and its long-term storage services solution in the strategically important long-term storage market.
Tags : storiant, big data, analytics implementations, cloudbased pricing model, long-term storage services solution, long-term storage market
     Storiant
By: MEMSQL     Published Date: Apr 12, 2016
The pace of data is not slowing. Applications of today are built with infinite data sets in mind. As these real-time applications become the norm, and batch processing becomes a relic of the past, digital enterprises will implement memory-optimized, distributed data systems to simplify Lambda Architectures for real-time data processing and exploration.
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     MEMSQL
By: Data Direct Networks     Published Date: Apr 08, 2014
DataDirect Networks (DDN), the largest privately-held provider of high-performance storage, has a large and growing presence in HPC markets. HPC users identify DDN as their storage provider more than any other storage-focused company, with twice the mentions of EMC, and more the twice the mentions of NetApp, Hitachi Data Systems, or Panasas.(5) DDN’s strength in HPC is anchored by its Storage Fusion Architecture (SFA), winner of the HPCwire Editor’s Choice Award for “Best HPC Storage Product or Technology” in each of the past three years. The DDN SFA12KX combines SATA, SAS, and solid-state disks (SSDs) for an environment that can be tailored to a balance of throughput and capacity
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     Data Direct Networks
By: Intel     Published Date: Aug 06, 2014
Powering Big Data Workloads with Intel® Enterprise Edition for Lustre* software The Intel® portfolio for high-performance computing provides the following technology solutions: • Compute - The Intel® Xeon processor E7 family provides a leap forward for every discipline that depends on HPC, with industry-leading performance and improved performance per watt. Add Intel® Xeon Phi coprocessors to your clusters and workstations to increase performance for highly parallel applications and code segments. Each coprocessor can add over a teraflops of performance and is compatible with software written for the Intel® Xeon processor E7 family. You don’t need to rewrite code or master new development tools. • Storage - High performance, highly scalable storage solutions with Intel® Lustre and Intel® Xeon Processor E7 based storage systems for centralized storage. Reliable and responsive local storage with Intel® Solid State Drives. • Networking - Intel® True Scale Fabric and Networking technologies – Built for HPC to deliver fast message rates and low latency. • Software and Tools: A broad range of software and tools to optimize and parallelize your software and clusters. Further, Intel Enterprise Edition for Lustre software is backed by Intel, the recognized technical support providers for Lustre, and includes 24/7 service level agreement (SLA) coverage.
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     Intel
By: Dell and Intel®     Published Date: Aug 24, 2015
New technologies help decision makers gain insights from all types of data - from traditional databases to high-visibility social media sources. Big data initiatives must ensure data is cost-effectively managed, shared by systems across the enterprise, and quickly and securely made available for analysis and action by line-of-business teams. In this article, learn how Dell working with Intel® helps IT leaders overcome the challenges of IT and business alignment, resource constraints and siloed environments through a comprehensive big data portfolio based on choice and flexibility, redefined economics and connected intelligence.
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     Dell and Intel®
By: Dell and Intel®     Published Date: Aug 24, 2015
Organizations working at gathering insights from vast volumes of varied data types understand that they need more than traditional, structured systems, and tools. This paper discusses how the many Dell | Cloudera Hadoop solutions help organizations of all sizes, and with a variety of needs and use cases, tackle their big data requirements.
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     Dell and 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: Kx Systems     Published Date: Jan 16, 2015
?Kdb+ is a column-based relational database with extensive in-memory capabilities, developed and marketed by Kx Systems. Like all such products, it is especially powerful when it comes to supporting queries and analytics. However, unlike other products in this domain, kdb+ is particularly good (both in terms of performance and functionality) at processing, manipulating and analysing data (especially numeric data) in real-time, alongside the analysis of historical data. Moreover, it has extensive capabilities for supporting timeseries data. For these reasons Kx Systems has historically targeted the financial industry for trading analytics and black box trading based on real-time and historic data, as well as realtime risk assessment; applications which are particularly demanding in their performance requirements. The company has had significant success in this market with over a hundred major financial institutions and hedge funds deploying its technology. In this paper, however, we wa
Tags : kx systems, kdb+, relational database
     Kx Systems
By: snowflake     Published Date: Jun 09, 2016
Today’s data, and how that data is used, have changed dramatically in the past few years. Data now comes from everywhere—not just enterprise applications, but also websites, log files, social media, sensors, web services, and more. Organizations want to make that data available to all of their analysts as quickly as possible, not limit access to only a few highly-skilled data scientists. However, these efforts are quickly frustrated by the limitations of current data warehouse technologies. These systems simply were not built to handle the diversity of today’s data and analytics. They are based on decades-old architectures designed for a different world, a world where data was limited, users of data were few, and all processing was done in on-premises datacenters.
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     snowflake
By: snowflake     Published Date: Jun 09, 2016
THE CHALLENGE: DATA SOLUTIONS CAN’T KEEP PACE WITH DATA NEEDS Organizations are increasingly dependent on diff erent types of data to make successful business decisions. But as the volume, rate, and types of data expand and become less predictable, conventional data warehouses cannot consume all this data eff ectively. Big data solutions like Hadoop increase the complexity of the environment and generally lack the performance of traditional data warehouses. This makes it difficult, expensive, and time-consuming to manage all the systems and the data.
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     snowflake
By: BitStew     Published Date: May 26, 2016
The heaviest lift for an industrial enterprise is data integration, the Achilles’ heel of the Industrial Internet of Things (IIoT). Companies are now recognizing the enormous challenge involved in supporting Big Data strategies that can handle the data that is generated by information systems, operational systems and the extensive networks of old and new sensors. To compound these issues, business leaders are expecting data to be captured, analyzed and used in a near real-time to optimize business processes, drive efficiency and improve profitability. However, integrating this vast amount of dissimilar data into a unified data strategy can be overwhelming for even the largest organizations. Download this white paper, by Bit Stew’s Mike Varney, to learn why a big data solution will not get the job done. Learn how to leverage machine intelligence with a purpose-built IIoT platform to solve the data integration problem.
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     BitStew
By: HERE Technologies     Published Date: May 22, 2019
Operational readiness depends on rich location data. When managing logistics and tracking high-value assets, there is no room for error and our new data-driven world demands richer, smarter advanced mapping and navigation services. The 2018 Counterpoint Research Location Ecosystems Update compared 16 location platform vendors—including Google, TomTom and Mapbox—and it named HERE the “undisputed leader” in location based services. Counterpoint recognized HERE for its integrated analytical capability and commitment to open partnerships, allowing for custom operational requirements and a truly mobile location intelligence platform. See how HERE provides the industry leading tools and expertise to process that data—streamlining the logistics supply chain, boosting responsiveness, and guaranteeing mission success.
Tags : mapping, defence, location data.
     HERE Technologies
By: Group M_IBM Q3'19     Published Date: Jun 27, 2019
The enterprise data warehouse (EDW) has been at the cornerstone of enterprise data strategies for over 20 years. EDW systems have traditionally been built on relatively costly hardware infrastructures. But ever-growing data volume and increasingly complex processing have raised the cost of EDW software and hardware licenses while impacting the performance needed for analytic insights. Organizations can now use EDW offloading and optimization techniques to reduce costs of storing, processing and analyzing large volumes of data.
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     Group M_IBM Q3'19
By: Infinidat EMEA     Published Date: May 14, 2019
Big Data and analytics workloads represent a new frontier for organizations. Data is being collected from sources that did not exist 10 years ago. Mobile phone data, machine-generated data, and website interaction data are all being collected and analyzed. In addition, as IT budgets are already under pressure, Big Data footprints are getting larger and posing a huge storage challenge. This paper provides information on the issues that Big Data applications pose for storage systems and how choosing the correct storage infrastructure can streamline and consolidate Big Data and analytics applications without breaking the bank.
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     Infinidat EMEA
By: Infinidat EMEA     Published Date: May 14, 2019
Continuous data availability is a key business continuity requirement for storage systems. It ensures protection against downtime in case of serious incidents or disasters and enables recovery to an operational state within a reasonably short period. To ensure continuous availability, storage solutions need to meet resiliency, recovery, and contingency requirements outlined by the organization.
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     Infinidat EMEA
By: ASG Software Solutions     Published Date: Feb 24, 2010
A recent survey of CIOs found that over 75% want to develop an overall information strategy in the next three years, yet over 85% are not close to implementing an enterprise-wide content management strategy. Meanwhile, data runs rampant, slows systems, and impacts performance. Hard-copy documents multiply, become damaged, or simply disappear.
Tags : asg, cmdb, bsm, itil, bsm, metacmdb, archiving, sap, ilm, mobius, workload automation, wla, visibility, configuration management, metadata, metacmdb, lob, sdm, service dependency mapping, ecommerce
     ASG Software Solutions
By: AWS     Published Date: Jul 10, 2019
Being able to monitor and respond to patient inquiries quickly and effectively is critical to creating a positive clinical experience and delivering successful products. But compiling and monitoring this data to address customer concerns in a timely way is a challenge when you have disparate sources and systems, global teams, and multiple patients. Read how a top 10 global pharmaceutical company worked with Slalom and AWS to design and implement a unified and globally distributed event and inquiry data reporting system. By combining three types of requests into one solution, the company has improved the customer experience and increased call center and data input operational efficiency by 50%. Learn how to Increase access to relevant data to help inform future or ongoing clinical trials Adapt your existing system development processes to an agile approach Engage with Slalom and AWS throughout the lifecycle of a healthcare engagement
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     AWS
By: APC by Schneider Electric     Published Date: Feb 09, 2011
In the broadening data center cost-saving and energy efficiency discussion, data center physical infrastructure preventive maintenance (PM) is sometimes neglected as an important tool for controlling TCO and downtime. PM is performed specifically to prevent faults from occurring. IT and facilities managers can improve systems uptime through a better understanding of PM best practices.
Tags : absolute, data protection, maitenance, ups, physical infrastructure, infrastructure, data loss protection, dlp, ponemon, it security, sensitive data
     APC by Schneider Electric
By: Hewlett Packard Enterprise     Published Date: Jun 17, 2019
"Cloud-based predictive analytics platforms are a relatively new phenomenon, and they go far beyond the remote monitoring systems of a prior generation. Three key features differentiate cloud-based predictive analytics — data sharing, scope of monitoring, and use of artificial intelligence/machine learning (AI/ML) to drive autonomous operations. To help familiarize the uninitiated with specifically what types of value these systems can drive, IDC discusses them at some length in this white paper."
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     Hewlett Packard Enterprise
By: Cisco EMEA     Published Date: Nov 13, 2017
The HX Data Platform uses a self-healing architecture that implements data replication for high availability, remediates hardware failures, and alerts your IT administrators so that problems can be resolved quickly and your business can continue to operate. Space-efficient, pointerbased snapshots facilitate backup operations, and native replication supports cross-site protection. Data-at-rest encryption protects data from security risks and threats. Integration with leading enterprise backup systems allows you to extend your preferred data protection tools to your hyperconverged environment.
Tags : hyperflex, systems, data platform, storage efficiency, business, cisco
     Cisco EMEA
By: BigCommerce     Published Date: Oct 16, 2018
Businesses who have lived through the evolution of the digital age are well aware that we’ve experienced a generational shift in technology. The rise of software as a service (SaaS), cloud, mobile, big data, the Internet of Things (IoT), social media, and other technologies have disrupted industries and changed customers’ expectations. In our always-on, buy anything anywhere world, customers want their shopping experiences to be personalized, dynamic, and convenient. As a result, many businesses are trying to reinvent themselves. Success in a fast-paced economy depends on continually adapting and innovating. Companies have to move quickly to keep up; there’s no time for disjointed technologies and old systems that don’t serve the customer-obsessed mentality needed to thrive in the digital age.
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     BigCommerce
By: BigCommerce     Published Date: Oct 16, 2018
Whether your company has been selling online for 20 minutes or 20 years, you are undoubtedly familiar with the PCI DSS (Payment Card Industry Data Security Standard). It requires merchants to create security management policies and procedures for safeguarding customers’ payment data. Originally created by Visa, MasterCard, Discover, and American Express in 2004, the PCI DSS has evolved over the years to ensure online sellers have the systems and processes in place to prevent a data breach.
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     BigCommerce
By: SAP     Published Date: May 18, 2014
New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose built platforms more capable of meeting the real-time needs of a more demanding end user and the opportunities presented by Big Data. Significant strategy shifts are under way to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support Big Data and real-time needs of innovative enterprises companies.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
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