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Published By: IBM Unica     Published Date: Sep 08, 2011
Marketers are looking for cross-channel campaign management solutions that support highly personalized and relevant communications delivered across a variety of highly interactive channels and that enable optimization, channel integration, and institutional memory of the customer.
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ibm, unica, forrester wave, cross-channel, campaign management, cccm, siebel, communication strategy, integration, marketing
    
IBM Unica
Published By: Dell     Published Date: Sep 24, 2012
Employ the newest DellT server technology, with high-density memory, balanced I/O and the latest processors, for your enterprise virtualization and business processing environments.
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hardware, dell, high availability, virtualization, virtualized infrastructure
    
Dell
Published By: SAP     Published Date: Sep 12, 2012
In this paper, get the perspective of a leading SME analyst on SAP Business All-in-One solutions and recent innovations, such as mobility and in-memory computing.
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sap, erp, enterprise resource planning, sap business all-in-one, baio
    
SAP
Published By: Intel     Published Date: Aug 10, 2012
3rd generation Intel® CoreT vProT processors fight sophisticated crimeware with built-in security technologies that work below and beyond the OS
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it security, intel, monitoring, reporting, remediation, automatic monitoring, contagions, built-in-security, virtual realms, hardware-based security, intel ipt, software based convenience, anti-virus, security software, memory, network, display, disk, security, it management
    
Intel
Published By: CDW     Published Date: Dec 23, 2014
Learn how to build a more successful business with the new infrastructure provided from Windows servers and see how you can lower costs, increase security, and improve the “speed to solution”.
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cdw, data, windows, server, infrastructure, lenovo, technology, operations, compatibility, memory, integration, security, speed, business technology
    
CDW
Published By: VMTurbo     Published Date: Mar 25, 2015
An Intelligent Roadmap for Capacity Planning Many organizations apply overly simplistic principles to determine requirements for compute capacity in their virtualized data centers. These principles are based on a resource allocation model which takes the total amount of memory and CPU allocated to all virtual machines in a compute cluster, and assumes a defined level of over provisioning (e.g. 2:1, 4:1, 8:1, 12:1) in order to calculate the requirement for physical resources. Often managed in spreadsheets or simple databases, and augmented by simple alert-based monitoring tools, the resource allocation model does not account for actual resource consumption driven by each application workload running in the operational environment, and inherently corrodes the level of efficiency that can be driven from the underlying infrastructure.
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capacity planning, vmturbo, resource allocation model, cpu, cloud era, it management, knowledge management, enterprise applications
    
VMTurbo
Published By: VMTurbo     Published Date: Apr 14, 2015
Seconds of Delay Have Multi-Million Dollar Consequences, Demand-Driven Control Changes the Game Principled Technologies deployed VMTurbo’s Demand-Driven Control platform in their virtualized data center. VMTurbo assures application performance while maximizing infrastructure utilization. Principled Technologies implemented VMTurbo’s recommendations in its virtual environment with an OLTP application, and saw significant improvements in performance. Learn how Principled Technologies achieved a 37% decrease in latency and 23% increase in orders per minute (OPM).
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vmturbo, datacenter, performance, production, operations, vmware, memory, storage, speed, reallocation, latency, business technology
    
VMTurbo
Published By: AWS     Published Date: Apr 27, 2018
Until recently, businesses that were seeking information about their customers, products, or applications, in real time, were challenged to do so. Streaming data, such as website clickstreams, application logs, and IoT device telemetry, could be ingested but not analyzed in real time for any kind of immediate action. For years, analytics were understood to be a snapshot of the past, but never a window into the present. Reports could show us yesterday’s sales figures, but not what customers are buying right now. Then, along came the cloud. With the emergence of cloud computing, and new technologies leveraging its inherent scalability and agility, streaming data can now be processed in memory, and more significantly, analyzed as it arrives, in real time. Millions to hundreds of millions of events (such as video streams or application alerts) can be collected and analyzed per hour to deliver insights that can be acted upon in an instant. From financial services to manufacturing, this rev
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AWS
Published By: Epson     Published Date: Jan 10, 2019
Since the earliest days of the industry, insurance companies have faced a never-ending struggle: processing the voluminous amount of paperwork that underwriting, claims, and compliance require. But the days of enduring the burdens caused by mountains of paper can become a distant memory. By investing in new, proven methods of converting paper documents to readable digital formats, insurance organizations can fully automate document processing to accelerate workflows, minimize processing times and enable more efficient operations.
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Epson
Published By: AI Business     Published Date: Mar 11, 2019
LOOK TO RELEVANT USE CASES FOR YOUR BUSINESS. While use cases vary across industries, the most common ones fall into these categories and are usually associated with the listed neural network: • Image classification or object detection: convolutional neural network (CNN) • Time-series predictions: long short-term memory (LSTM) • Natural language processing: recurrent neural network (RNN) • Unlabeled data classification and data labeling: autoencoder (AE) • Anomaly detection: autoencoder (AE) • Recommender systems: multilayer perceptron (MLP) Work with your deep learning talent or consultants to identify which use cases best match your organization and desired solutions. Then recreate a successful, already proven method.
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AI Business
Published By: Amazon     Published Date: Nov 07, 2013
This planning and implementation guide discusses planning topics, architectural considerations, and configuration steps relevant before and after launching the necessary AWS services such as Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Virtual Private Cloud (Amazon VPC) to run a high-availability and site-resilient Exchange architecture.
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amazon web services, microsoft exchange, aws cloud, cloud, web services, servers, processor, memory, storage, log replication, network traffic, resiliency, availability, configuration, deployment
    
Amazon
Published By: Texas Memory Systems     Published Date: Feb 25, 2012
With flash based systems now commonly in the TBs of capacity and rapidly becoming more affordable, it may be time to look at using solid state storage with high bandwidth applications. Read this white paper to find out more.
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solid state storage, bandwidth, high bandwidth, applications, data warehousing, tbs, tb capacity, storage, ramsan, texas memory systems, high availability, performance, solid state, enterprise, racks, data storage, digital signal, low latency, enterprise data storage, ssds
    
Texas Memory Systems
Published By: Texas Memory Systems     Published Date: Feb 25, 2012
Most companies have only put limited effort toward the system architecture that surrounds the flash memory modules. In this white paper, Storage Switzerland focuses on the importance of architecture design in solid state storage systems.
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ssd, architecture, design, zero-latency, retrieval, solid state storage, bandwidth, high bandwidth, flash controllers, applications, data warehousing, tbs, tb capacity, storage, ramsan, texas memory systems, high availability, performance, solid state, enterprise
    
Texas Memory Systems
Published By: Texas Memory Systems     Published Date: Feb 25, 2012
It is common knowledge that PCIe SSD is faster, right? Maybe not, says George Crump from Storage Switzerland. Read on to find out why.
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pcie, pcie ssd, ssd, architecture, design, zero-latency, retrieval, solid state storage, bandwidth, high bandwidth, flash controllers, applications, data warehousing, tbs, tb capacity, storage, ramsan, texas memory systems, high availability, performance
    
Texas Memory Systems
Published By: Texas Memory Systems     Published Date: Feb 25, 2012
In this part II of Enhancing Server And Desktop Virtualization With SSD, Storage Switzerland focuses on the next challenge of integrating SSD into a virtual server or desktop infrastructure and effectively using the technology in this environment.
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integrated ssd, ssd, virtual server, infrastructure, desktop infrastructure, server virtualization, desktop virtualization, architecture, design, zero-latency, retrieval, solid state storage, bandwidth, high bandwidth, flash controllers, applications, data warehousing, tbs, tb capacity, storage
    
Texas Memory Systems
Published By: Texas Memory Systems     Published Date: Feb 25, 2012
For data centers looking to get the maximum performance from Flash-based storage supporting their virtual infrastructure, the RamSan-720 should be given strong consideration.
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ramsan-720, integrated ssd, ssd, virtual server, infrastructure, desktop infrastructure, server virtualization, desktop virtualization, architecture, design, zero-latency, retrieval, solid state storage, bandwidth, high bandwidth, flash controllers, applications, data warehousing, tbs, tb capacity
    
Texas Memory Systems
Published By: Texas Memory Systems     Published Date: Feb 25, 2012
In this final piece on server virtualization and SSD, Storage Switzerland discusses the power of performance, specifically, the dramatic impact that latent-free storage can make on the virtual environment. Read on to find out more!
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desktop virtualization, architecture, design, zero-latency, retrieval, solid state storage, bandwidth, high bandwidth, flash controllers, applications, data warehousing, tbs, tb capacity, storage, ramsan, texas memory systems, high availability, performance, solid state, enterprise
    
Texas Memory Systems
Published By: Silver Peak     Published Date: Oct 28, 2013
Enterprises have long been battling the inherent performance limitations of Wide Area Networks (WANs) when delivering applications to remote offices. Caching emerged in the 1990’s as a potential way of addressing this problem, accelerating the performance of specific applications, such as web services, while reducing overall WAN traffic. While caching achieved reasonable success for a few short years, the market for these point products ultimately subsided as a result of several operational and functional limitations. Enterprises require an application acceleration solution that spans all types of traffic, one that is easy to manage, and 100% data coherency when supporting business-critical applications. This white paper will address these issues and offer a solution that addresses these enterprise requirements. The result is a complete solution for improved application delivery across a distributed enterprise environment.
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silver peak, network memory, application caching, wan, caching, networking
    
Silver Peak
Published By: Lumension     Published Date: Feb 07, 2014
Memory injections are on the rise. And traditional endpoint security tools can do little to stop them. Here’s what you need to know about memory-based attacks—and how to effectively protect against them.
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lumension, persistent threats, memory-based attacks, information security, it regimes, threat solution, risk mitigation, data security products, vulnerability management, layered defenses, e-security, targeted phishing, organized attacks, apt attacks, computer security, infrastructure, whitelisting solutions, application control, encryption, business scanning
    
Lumension
Published By: SnowFlake     Published Date: Jul 08, 2016
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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forrester, enterprise, data, technology, best practices, innovation, security, business technology
    
SnowFlake
Published By: Gigaom     Published Date: Jan 15, 2019
This recorded one-hour webinar will show you the benefits of end-to-end solutions and storage consolidation.
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nutanix, storage, storage infrastructure, storage consolidation, hybrid cloud, memory storage
    
Gigaom
Published By: Group M_IBM Q418     Published Date: Sep 10, 2018
LinuxONE from IBM is an example of a secure data-serving infrastructure platform that is designed to meet the requirements of current-gen as well as next-gen apps. IBM LinuxONE is ideal for firms that want the following: ? Extreme security: Firms that put data privacy and regulatory concerns at the top of their requirements list will find that LinuxONE comes built in with best-in-class security features such as EAL5+ isolation, crypto key protection, and a Secure Service Container framework. ? Uncompromised data-serving capabilities: LinuxONE is designed for structured and unstructured data consolidation and optimized for running modern relational and nonrelational databases. Firms can gain deep and timely insights from a "single source of truth." ? Unique balanced system architecture: The nondegrading performance and scaling capabilities of LinuxONE — thanks to a unique shared memory and vertical scale architecture — make it suitable for workloads such as databases and systems of reco
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Group M_IBM Q418
Published By: SAS     Published Date: Mar 06, 2018
Imagine getting into your car and saying, “Take me to work,” and then enjoying an automated drive as you read the morning news. We are getting very close to that kind of scenario, and companies like Ford expect to have production vehicles in the latter part of 2020. Driverless cars are just one popular example of machine learning. It’s also used in countless applications such as predicting fraud, identifying terrorists, recommending the right products to customers at the right time, and correctly identifying medical symptoms to prescribe appropriate treatments. The concept of machine learning has been around for decades. What’s new is that it can now be applied to huge quantities of data. Cheaper data storage, distributed processing, more powerful computers and new analytical opportunities have dramatically increased interest in machine learning systems. Other reasons for the increased momentum include: maturing capabilities with methods and algorithms refactored to run in memory; the
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SAS
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