workload data

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Published By: Pure Storage     Published Date: Dec 05, 2018
With the growth of unstructured data and the challenges of modern workloads such as Apache Spark™, IT teams have seen a clear need during the past few years for a new type of all-flash storage solution, one that has been designed specifically for users requiring high levels of performance in file- and object-based environments. With FlashBlade™, it addresses performance challenges in Spark environments by delivering the consistent performance of all-flash storage with no caching or tiering, as well as fast metadata operations and instant metadata queries.
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Pure Storage
Published By: BMC ASEAN     Published Date: Dec 18, 2018
38% of enterprises have moved workloads from the public cloud back to their on-premise data centers- with costs being among the biggest concerns.
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BMC ASEAN
Published By: BMC ASEAN     Published Date: Dec 18, 2018
400+ IT professionals reveal what’s next for workload automation How are today’s leading companies using workload automation to drive their most important IT initiatives? Find out in this detailed report summary from analyst firm Enterprise Management Associates (EMA). You’ll learn how the role of workload automation is evolving, including: The rise of predictive analytics in WLA Surprising stats on the frequency and ease of migration How big data and cloud impact WLA The use of containers and micro services architectures Workload automation is changing fast. Keep up with the latest analyst research – download the report.
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BMC ASEAN
Published By: BMC Control M     Published Date: Jul 22, 2009
Gartner has positioned BMC CONTROL-M in the Leaders Quadrant of their "2009 Magic Quadrant for Job Scheduling." The report assesses the ability to execute and completeness of vision of key vendors in the marketplace. Read a full copy today, courtesy of BMC Software.
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quadrant, magic quadrant, job scheduling, bmc control-m, workload, automation broker, gartner, data, job, itwab, it workload automation broker
    
BMC Control M
Published By: CDW     Published Date: Nov 12, 2012
This reference guide is designed to provide you with an in-depth look at data center optimization, what's driving it and why organizations need to plan for it.
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data center, data center optimization, data center convergence, workload mobility, data center strategy
    
CDW
Published By: Nimble Storage     Published Date: Oct 28, 2013
Nimble Storage’s patented Cache Accelerated Sequential Layout (CASL™) is the industry’s first flash-optimized storage designed from the ground up to maximize efficiency. In this product brief, you’ll learn how Nimble Storage customers run more workloads with less storage infrastructure, protect more data, and streamline data management so they can focus on higher-value projects.
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nimble storage, data storage, backup, disaster recovery, flash memory, data protection, ssd, hybrid storage, high-performance storage, storage efficiency, storage management, storage for vdi, storage for virtualized servers, storage for private cloud, storage for vmware, storage for oracle, storage for microsoft, storage for exchange, storage for sharepoint
    
Nimble Storage
Published By: Nimble Storage     Published Date: Oct 28, 2013
It’s easy to underestimate the performance and capacity requirements for VDI storage, and missteps now can lead to expensive problems later. In “Risk-Free Storage for VDI,” you’ll learn how Nimble Storage delivers responsive performance to handle peak VDI workloads, integrated data protection, and instant backups and restores—all for dramatically less than you’re paying now.
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nimble storage, data storage, backup, disaster recovery, flash memory, data protection, ssd, hybrid storage, high-performance storage, storage efficiency, storage management, storage for vdi, storage for virtualized servers, storage for private cloud, storage for vmware, storage for oracle, storage for microsoft, storage for exchange, storage for sharepoint
    
Nimble Storage
Published By: Gigaom     Published Date: Sep 16, 2019
We’ve heard it before. A data warehouse is a place for formally-structured, highly-curated data, accommodating recurring business analyses, whereas data lakes are places for “raw” data, serving analytic workloads, experimental in nature. Since both conventional and experimental analysis is important in this data-driven era, we’re left with separate repositories, siloed data, and bifurcated skill sets. Or are we? In fact, less structured data can go into your warehouse, and since today’s data warehouses can leverage the same distributed file systems and cloud storage layers that host data lakes, the warehouse/lake distinction’s very premise is rapidly diminishing. In reality, business drivers and business outcomes demand that we abandon the false dichotomy and unify our data, our governance, our analysis, and our technology teams. Want to get this right? Then join us for a free 1-hour webinar from GigaOm Research. The webinar features GigaOm analyst Andrew Brust and special guest, Dav
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Gigaom
Published By: Dell EMC     Published Date: Mar 18, 2016
The EMC Isilon Scale-out Data Lake is an ideal platform for multi-protocol ingest of data. This is a crucial function in Big Data environments, in which it is necessary to quickly and reliably ingest data into the Data Lake using protocols closest to the workload generating the data. With OneFS it is possible to ingest data via NFSv3, NFSv4, SMB2.0, SMB3.0 as well as via HDFS. This makes the platform very friendly for complex Big Data workflows.
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emc, emc isilon, data lake, storage, network, big data
    
Dell EMC
Published By: AWS     Published Date: Jul 29, 2019
What you'll learn in this webinar: Optimize your operations by taking advantage of the modern, scalable cloud infrastructure available on Amazon Web Services (AWS). Migrate your Oracle applications and databases to AWS and get all the benefits of the cloud. Migrating mission-critical Oracle databases and applications to the cloud is complex and you may feel locked into your platform. Amazon Aurora provides commercial-grade database performance and availability at a fraction of the cost. Apps Associates—an AWS Partner Network (APN) Partner and Oracle expert—can migrate enterprise workloads to the cloud, freeing customers to focus on higher-value initiatives. Watch this webinar to learn how to: Run your entire Oracle database and application environment on the cloud Take advantage of lower IT costs on the cloud and reduce your Total Cost of Ownership (TCO) Leverage Amazon Aurora to help satisfy your company’s cloud-first mandate, improve security, and reduce risk
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AWS
Published By: MemSQL     Published Date: Nov 15, 2017
THE LAMBDA ARCHITECTURE SIMPLIFIED Your Guide to Building a Scalable Data Architecture for Real-Time Workloads YOU'LL LEARN: - What defines the Lambda Architecture, broken down by each layer - How to simplify the Lambda Architecture by consolidating the speed layer and batch layer into one system - How to implement a scalable Lambda Architecture that accommodates streaming and immutable data - How companies like Comcast and Tapjoy use Lambda Architectures in production
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data, scalable, architecture, production
    
MemSQL
Published By: Cohesity     Published Date: Aug 09, 2019
As organizations continue to look for ways to increase business agility, a need for a modern database architecture that can rapidly respond to the needs of business is more apparent than ever. While an RDBMS still serves as a lifeline for many organizations, the adoption of technologies such as NoSQL and Hadoop are enabling organizations to best address database performance and scalability requirements while also satisfying the goals of embracing hybrid cloud and becoming more data-driven. And with organizations relying so heavily on these new technologies to yield rapid insights that positively impact the business, the need to evaluate how those new technologies are managed and protected is essential. Hadoop and NoSQL workloads are now pervasive in production environments and require “production-class” data protection, yet few data protection solutions offer such capabilities today.
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Cohesity
Published By: Cohesity     Published Date: Aug 09, 2019
In a context of mass data fragmentation on-premises and in the cloud, organizations now struggle with the compounded complexities brought about by modern workloads such as containers, NoSQL/NewSQL databases, and SaaS applications. These new workloads are turning traditional backup and recovery approaches on their head—in particular, in Microsoft Office 365 deployments for which new backup, recovery, and data management schemas must be deployed.
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Cohesity
Published By: Cohesity     Published Date: Aug 09, 2019
IT organizations everywhere are undergoing significant transformation to keep pace with the needs of their businesses. They’re tasked with consolidating data centers and migrating both workloads and data to the cloud. The transition has been easier for some than others. As hybrid architectures increasingly become the norm, how are enterprises gaining complete visibility, simplifying management, and making use of all of their data—both on-premises and in the cloud? Five enterprises explain how they’ve replaced multiple products that created legacy data silos with Cohesity – a single, hyperconverged softwaredefined platform with native Microsoft Azure integration for simplified secondary data and applications. For them, Cohesity and Azure together boost IT agility while lowering costs, solving critical secondary data challenges from long-term retention, storage tiering, test/dev, disaster recovery and cloud-native backup in a proven hybrid cloud architecture.
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Cohesity
Published By: Cohesity     Published Date: Aug 09, 2019
Data for secondary workloads – backup, test/dev, disaster recovery, and archiving to name a few – have become siloed the same way application data has, leading to multiple point solutions to manage an increasing amount of data. This white paper looks at the evolution of these challenges and offers practical advice on ways to store, manage and move secondary data in hybrid cloud architectures while extracting the hidden value it can provide.
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Cohesity
Published By: Cisco     Published Date: Apr 19, 2011
Download this white paper to learn how IT automation helps businesses make better decisions faster in addition to raising the bar in business innovation.
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cisco, it automation solutions, application optimization automation, job scheduling, workload automation, network automation, private cloud infrastructure, data center automation, intelligent automation suite, tidal enterprise scheduler, applicaiton visibility and management, intelligent automation for networks
    
Cisco
Published By: EMC Corporation     Published Date: Dec 08, 2014
Traditional methods for provisioning and maintaining storage resources are no longer sufficient to achieving business goals due to the fact that technology layers mask the relationship of application workloads to the physical storage devices that support them. The broad adoption of disruptive technologies - including cloud, virtualization, mobility, software-defined data centers, and big data - have introduced new and more challenging requirements for enterprise IT. Find our more in this whitepaper.
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cloud, big data, software-defined data, virtualization, storage, mobility
    
EMC Corporation
Published By: VMware     Published Date: Nov 07, 2016
With the rise of companies such as Netflix and Uber, the marketplace is feeling the impact of “digital disruptors”—fast-moving, application-centric organizations that are taking advantage of digitalization to create thriving and market-changing business models. In an effort to stay competitive, more enterprises are adopting multi-cloud strategies as a means “to optimize workload performance and cost” across their IT environment, both on and off premises. The trend brief “Top Trends Driving the Need for Unified Cloud Management” discusses how a cloud management platform (CMP) enables IT organizations to accelerate IT services delivery and improve data center operations while maintaining control across multi-cloud environments. The brief highlights the VMware enterprise-ready cloud management platform based on VMware vRealize® Suite and powered by Intel® based server platforms.
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VMware
Published By: Microsoft     Published Date: Jul 20, 2018
When it comes to performance, Azure SQL Database is built for you, the developer. Azure SQL Database is designed to make your work easier and let you focus on other priorities. It scales on the fly, without downtime, with capabilities that make it great for building multitenant software as a service (SaaS) apps. Plus, it learns and adapts to your database workload, whatever that may be, using built-in intelligence to continually adjust and improve over time. That said, there’s more to a successful app than impressive performance. That’s why we built Azure SQL Database to be just as intelligent in other areas, such as availability and security, so that you won’t need to worry about those essentials either. Finally, we built Azure SQL Database to let you work the way you want, using the tools and platforms you prefer. It’s why we call Azure SQL Database the intelligent database for developers. Read on to learn more, and we’re sure you’ll agree.
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Microsoft
Published By: Microsoft     Published Date: Jul 20, 2018
Microsoft commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study to examine the potential return on investment (ROI) enterprises may realize by shifting some or all their management and operations from on-premises, hosted, and outsourced implementations to Azure’s infrastructure-as-a-service (IaaS) offering. The purpose of this study is to give readers a framework to evaluate the potential financial impact, or ROI, of leveraging Azure IaaS for their organizations. Benefits gained by interviewed customers that migrated or re-architected some or all workloads from on-premises to IaaS include: › Greater revenue opportunities from business-to-business (B2B) and customer web channels with a solution that is more mobile and reliable, and meets scale and seasonality needs. › Increased profits from those revenues. › Improved production efficiency. › Reduced datacenter, IT resource, and outsourcing costs. › Easier and faster software and hardware management (such as p
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Microsoft
Published By: Pure Storage     Published Date: Apr 15, 2019
This year, businesses will increasingly turn to AI to power their business transformation. Machine learning and deep learning workloads are quickly becoming a mission-critical workload in the enterprise data center. As an IT leader, are you ready for the impending wave of AI applications that will demand new approaches to computing, storage and networking? Do you have the right strategy for scaling AI workload in your data center? We’ll introduce you to the IT visionaries who have made it happen. In this webinar we’ll explore how one IT leader accelerated his company’s success with an AI infrastructure strategy, sharing their best practices and insights. By watching this webinar, you'll learn: - Why it’s now critical for enterprise IT to have an AI infrastructure strategy that supports the business - Explore one IT leader’s experience developing and implementing a best-of-breed platform for scaling AI workload in the data center - Gain insights that can drive your AI infrastructur
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Pure Storage
Published By: Vertica     Published Date: Aug 16, 2010
The Vertica Analytic Database is the only database built from scratch to handle today's heavy business intelligence workloads. In customer benchmarks, Vertica has been shown to manage terabytes of data running on extraordinarily low-cost hardware and answers queries 50 to 200 times faster than competing row-oriented databases and specialized analytic hardware. This document summarizes the key aspects of Vertica's technology that enable such dramatic performance benefits, and compares the design of Vertica to other popular relational systems.
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vertica, ec2, elastic, cloud computing, workflow, benchmark, projections, ad-hoc, business intelligence, cloud, cloudbased applications, analytic, saas, dbms, mpp
    
Vertica
Published By: NetApp     Published Date: Oct 12, 2010
Read about the simplicity of architecting a robust infrastructure with Microsoft® Windows® Server 2008 R2 Hyper-VT in a virtual environment with NetApp® storage, to provide the ability to maintain HA for both the computing and storage resources between the primary and secondary sites and complete disaster recovery in the event of the loss of a whole site.
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netapp, hyper v, microsoft exchange server, sql server, sharepoint server mixed workload, disaster recovery, data center, virtualization
    
NetApp
Published By: IBM     Published Date: Oct 14, 2009
Discover the unique support for data warehousing and business intelligence offered by the IBM DB2 portfolio. This white paper shows how an IBM System z server, integrated with the IBM DB2 family of solutions, can help you meet requirements for data warehousing and business intelligence.
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data warehousing, ibm, business intelligence, total cost of ownership, tco, integrated facility for linux, eal5, workload consolidation, scalability, disaster recovery, workload management, operational data stores
    
IBM
Published By: Savvis     Published Date: Jul 07, 2010
The cloud services market is now directly addressing the needs of application developers, with an emerging class of services that provides fast, on-demand provisioning; instant scale up and down capabilities, and support for multi-tier application architectures, as well as workload migration capabilities and a pay-as-you go model.
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savvis, software development, cloud testing, application architecture, workload migration, saas, software-as-a-service, cloud computing, virtual data center
    
Savvis
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