velocity

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Published By: IBM     Published Date: Feb 01, 2016
Achieving Application Delivery Velocity with a 482% ROI
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ibm, economic impact, urbancode, devops, roi, software development, business technology
    
IBM
Published By: IBM     Published Date: Feb 22, 2016
To help enterprises create trusted insight as the volume, velocity and variety of data continue to explode, IBM offers several solutions designed to help organizations uncover previously unavailable insights and use them to support and inform decisions across the business.
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ibm, data, mdm, big data, insight, infosphere, knowledge management, data management, business technology
    
IBM
Published By: Nimble Storage     Published Date: Feb 26, 2016
Download this eBook to learn the steps you can take now to prepare for the all flash data center. flash storage, SSD, all flash data centers, nimble storage, predictive flash platform, application perfomance, data velocity
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flash storage, ssd, all flash data centers, nimble storage, predictive flash platform, application perfomance, data velocity, data protection, high availability, big data, predictive analytics, data center
    
Nimble Storage
Published By: Panaya     Published Date: Jun 01, 2018
Hear IDC Research Director for ALM Strategies explain how establishing effective agile approaches to software development, QA and testing, ensures software relevance, streamlines execution and increases release velocity. Join IDC guest speaker and Panaya experts to hear: › IDC Research Director, Melinda-Carol Ballou cover the latest ALM industry practices › Which ALM strategies bring greater agility to your backend system › How to implement these practices to achieve frequent, quality change releases
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Panaya
Published By: IBM     Published Date: Feb 22, 2016
To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources.
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ibm, data, performance, scalability, information integration, big data, data management, business technology
    
IBM
Published By: IBM     Published Date: Jul 06, 2016
To help enterprises create trusted insight as the volume, velocity and variety of data continue to explode, IBM offers several solutions designed to help organizations uncover previously unavailable insights and use them to support and inform decisions across the business. Combining the power of IBM® InfoSphere® Master Data Management (MDM) with the IBM big data portfolio creates a valuable connection: big data technology can supply insights to MDM, and MDM can supply master data definitions to big data.
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ibm, mdm, big data, ibm infosphere, data management, data center
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
To help enterprises create trusted insight as the volume, velocity and variety of data continue to explode, IBM offers several solutions designed to help organizations uncover previously unavailable insights and use them to support and inform decisions across the business. Combining the power of IBM® InfoSphere® Master Data Management (MDM) with the IBM big data portfolio creates a valuable connection: big data technology can supply insights to MDM, and MDM can supply master data definitions to big data.
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ibm, mdm, big data, ibm infosphere, mdm advantagw, knowledge management, business technology
    
IBM
Published By: IBM     Published Date: Apr 14, 2017
Any organization wishing to process big data from newly identified data sources, needs to first determine the characteristics of the data and then define the requirements that need to be met to be able to ingest, profile, clean,transform and integrate this data to ready it for analysis. Having done that, it may well be the case that existing tools may not cater for the data variety, data volume and data velocity that these new data sources bring. If this occurs then clearly new technology will need to be considered to meet the needs of the business going forward.
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data integration, big data, data sources, business needs, technological advancements, scaling data
    
IBM
Published By: IBM     Published Date: Jul 06, 2017
Effectively using and managing information has become critical to driving growth in areas such as pursuing new business opportunities, attracting and retaining customers, and streamlining operations. In the era of big data, you must accommodate a rapidly increasing volume, variety and velocity of data while extracting actionable business insight from that data, faster than ever before. These needs create a daunting array of workload challenges and place tremendous demands on your underlying IT infrastructure and database systems. In many cases, these systems are no longer up to the task—so it’s time to make a decision. Do you use more staff to keep up with the fixes, patches, add-ons and continual tuning required to make your existing systems meet performance goals, or move to a new database solution so you can assign your staff to new, innovative projects that move your business forward?
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database, growth, big data, it infrastructure, information management
    
IBM
Published By: Group M_IBM Q1'18     Published Date: Dec 19, 2017
Effectively using and managing information has become critical to driving growth in areas such as pursuing new business opportunities, attracting and retaining customers, and streamlining operations. In the era of big data, you must accommodate a rapidly increasing volume, variety and velocity of data while extracting actionable business insight from that data, faster than ever before. These needs create a daunting array of workload challenges and place tremendous demands on your underlying IT infrastructure and database systems. This e-book presents six reasons why you should consider a database change, including opinions from industry analysts and real-world customer experiences. Read on to learn more.
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database, streamlining, it infrastructure, database systems
    
Group M_IBM Q1'18
Published By: AppDynamics     Published Date: Sep 21, 2017
Technologies once relegated to the pages of science fiction novels—artificial intelligence, digital currency, and self-driving cars to name a few—have become a reality. Enterprises must innovate with high velocity and at massive scale to stay competitive. Cloud adoption has become a strategic imperative for enterprises—it’s the price required to transform into a digital business.
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AppDynamics
Published By: MarkLogic     Published Date: Mar 13, 2015
Big Data has been in the spotlight recently, as businesses seek to leverage their untapped information resources and win big on the promise of big data. However, the problem with big data initiatives are that organizations try using existing information management practices and legacy relational database technologies, which often collapse under the sheer weight of the data. In this paper, MarkLogic explains how a new approach is needed to handle the volume, velocity, and variety of big data because the current relational model that has been the status quo is not working. Learn about the NoSQL paradigm shift, and why NoSQL is gaining significant market traction because it solves the fundamental challenges of big data, achieving better performance, scalability, and flexibility. Learn how MarkLogic’s customers are reimagining their data to: - Make the world more secure - Provide access to valuable information - Create new revenue streams - Gain insights to increase market share - Reduce b
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enterprise, nosql, relational, databases, data storage, management system, application, scalable, data management
    
MarkLogic
Published By: Waterline Data & Research Partners     Published Date: Nov 07, 2016
Business users want the power of analytics—but analytics can only be as good as the data. The biggest challenge nontechnical users are encountering is the same one that has been a steep challenge for data scientists: slow, difficult, and tedious data preparation. The increasing volume, variety, and velocity of data is putting pressure on organizations to rethink traditional methods of preparing data for reporting, analysis, and sharing. Download this white paper to find out how you can improve your data preparation for business analytics.
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Waterline Data & Research Partners
Published By: IBM     Published Date: Oct 17, 2017
Every day, torrents of data inundate IT organizations and overwhelm the business managers who must sift through it all to glean insights that help them grow revenues and optimize profits. Yet, after investing hundreds of millions of dollars into new enterprise resource planning (ERP), customer relationship management (CRM), master data management systems (MDM), business intelligence (BI) data warehousing systems or big data environments, many companies are still plagued with disconnected, “dysfunctional” data—a massive, expensive sprawl of disparate silos and unconnected, redundant systems that fail to deliver the desired single view of the business. To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources. They need to bring all their corporate data together, deliver it to end users as quickly as possible to maximize
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IBM
Published By: DataStax     Published Date: Nov 02, 2018
Today’s data volume, variety, and velocity has made relational database nearly obsolete for handling certain types of workloads. But it’s also put incredible strain on regular NoSQL databases. The key is to find one that can deliver the infinite scale and high availability required to support high volume, web-scale applications in clustered environments. This white paper details the capabilities and uses case of an Active Everywhere database
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DataStax
Published By: Datastax     Published Date: Aug 23, 2017
About 10 years ago big data was quickly becoming the next big thing. It surged in popularity, swooning into the tech world's collective consciousness and spawning endless start-ups, thought pieces, and investment funding, and big data's rise in the startup world does not seem to be slowing down. But something's been happening lately: big data projects have been failing, or have been sitting on a shelf somewhere and not delivering on their promises. Why? To answer this question, we need to look at big data's defining characteristic - or make that characteristics, plural - or what is commonly known as 'the 3Vs": volume, variety and velocity.
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datastax, big data, funding
    
Datastax
Published 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
Published By: Datastax     Published Date: Aug 27, 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
Published By: Datastax     Published Date: Nov 02, 2018
Today’s data volume, variety, and velocity has made relational database nearly obsolete for handling certain types of workloads. But it’s also put incredible strain on regular NoSQL databases. The key is to find one that can deliver the infinite scale and high availability required to support high volume, web-scale applications in clustered environments. This white paper details the capabilities and uses case of an Active Everywhere database
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Datastax
Published By: Oracle     Published Date: Jan 08, 2019
How To Get Better At 'Small, High-Velocity' Decisions
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Oracle
Published By: Group M_IBM Q119     Published Date: Mar 01, 2019
The velocity of technology infrastructure change continues to accelerate, putting serious stress on Security Operations (SecOps). This has forced security folks to face the fact that operations has never really been their forte. That’s a bit harsh, but denial never helps address problems. The evidence is fairly strong that most organizations are pretty bad at security operations. How many high-profile breaches could have been avoided if one of many alerts was acted upon? How many attacks were made possible by not having properly patched servers or infrastructure? How many successful compromises resulted from human error?
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Group M_IBM Q119
Published By: Cybric     Published Date: Oct 30, 2017
Learn how a security rationalization process helps CISOs optimize your security infrastructure while improving the bottom line. Development velocity is accelerating as enterprises adopt DevOps methodologies, yet security is still not integrated into the coding and deployment processes. Security teams are falling further behind as their manual processes and controls can’t scale at the same rate as development. This paper discusses: The impact the current approach to application security has on business How shifting security left in the application development process, seamlessly integrating it “early and often,” can accelerate innovation Questions the Board and C-suite are now asking about security: are you prepared? Read this paper to learn how, by shifting security left in the development process, it’s now no longer an obstacle to velocity, innovation and competitiveness. Instead, it’s an asset.
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application security, (security) automation, (security) orchestration, security visibility, devsecops, devops, security assurance, security resilience, application security tools, cio, ciso, appsec
    
Cybric
Published By: Dynatrace     Published Date: Apr 16, 2018
Internet-of-things (IoT) is increasing in excitement across all industries as they look to provide innovation in their product and services, and monitor risks and costs in their business operations. But IoT is not a single technology. It is an ecosystem of human and non-human touchpoints that span across multiple technologies. This creates a dynamic and complex environment that is difficult to see and manage in scope. The traditional monitoring approach of watching dashboards, responding to alerts, and manually analyzing doesn’t work anymore. Today’s hyper-dynamic, highly distributed IoT application environments have become way too complex and move too quickly. The volume, velocity, and variety of information is simply more than humans can keep up with using traditional tools.
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Dynatrace
Published By: BlueArc Corporation     Published Date: Apr 24, 2008
It’s no secret: The scale and pace of business change today is challenging all of us to do more -- better, faster and with ever greater efficiency. Customers are demanding more and wanting it now. Market expectations for product and process innovation are growing. Mergers and acquisitions in many industries are at or near all-time highs. Complex global supply chains and highly distributed organizations are the norm.
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bluearc, it management, networking
    
BlueArc Corporation
Published By: Red Hat, Inc.     Published Date: Jul 10, 2012
Today, as IT departments struggle to design and implement solutions capable of managing exponential data growth with strict requirements for application scale and performance, many of them are turning to in-memory data grids (IMDGs).
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it departments, data growth, managing data growth, application scale, application performance, in-memory data grids, imdgs, big data, data volume, data velocity, data variability, data management, data collection, data processing, data scaling, data storage systems, data access, data solutions, data challenges, management tooling
    
Red Hat, Inc.
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