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intelligence systems

Results 1 - 25 of 61Sort Results By: Published Date | Title | Company Name
Published 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.
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aberdeen, michael lock, data-driven decisions, business intelligence, public sector, analytics, federal, state
    
Aberdeen
Published By: Cisco Umbrella EMEA     Published Date: Aug 08, 2019
"The average company uses more than 50 security vendors: firewalls, web proxies, SIEM, appliances, intelligence - and the list goes on. Do you have more security tools than you can handle? There’s an easier way to make the most of your existing investments. We'll share ways you can reduce security alerts and extend your security off network, anywhere users go, with Cisco Umbrella. Built with a bidirectional API, Cisco Umbrella easily integrates with the other systems in your stack, so you can extend protection from on-premises security appliances to devices and sites beyond your perimeter — and amplify investments you’ve already made. Read the eBook to learn more about getting more bang for your security buck."
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Cisco Umbrella EMEA
Published By: SDL     Published Date: Sep 20, 2019
Component Content Management: A New Paradigm in Intelligent Content Services While technology has changed the world, the way that companies manage information has inherently stayed the same. The advent of near-ubiquitous connectivity among applications and machines has resulted in a data deluge that will fundamentally alter the landscape of content management. From mobile devices to intelligent machines, the volume and sophistication of data have surpassed the ability of humans to manage it with outdated methods of collection, processing, storage, and analysis. The opportunity afforded by the advent of artificial intelligence (AI) has stimulated the market to search for a better way to capture, classify, and analyze this data in its journey to digital transformation (DX). The paradigm of document-based information management has proven to be a challenge in finding, reusing, protecting, and extracting value from data in real time. Legacy systems may struggle with fragmented information
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SDL
Published 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
Published By: Cisco     Published Date: Jul 08, 2016
What You Will Learn: This document will identify the essential capabilities you need in an advanced malware protection solution, the key questions you should ask your vendor, and shows you how Cisco combats today’s advanced malware attacks using a combination of four techniques: • Advanced analytics • Collective global security threat intelligence • Enforcement across multiple form factors (networks, endpoints, mobile devices, secure gateways, and virtual systems) • Continuous analysis and retrospective security
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Cisco
Published By: Pentaho     Published Date: Feb 26, 2015
Ventana’s benchmark research on big data integration will help you become familiar with the tools and technologies you need to help your organization succeed with big data.
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benchmark research, big data integration, big data, business intelligence systems, business analytics, data integration, research
    
Pentaho
Published By: Aberdeen Group     Published Date: Jun 02, 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
    
Aberdeen Group
Published By: IBM APAC     Published Date: May 18, 2017
Today, everything computes. Intelligence has been infused into things no one would recognize as computers: appliances, cars, roadways, clothes, even rivers and cornfields. Tomorrow, many of these things will think, thanks to breakthroughs in cognitive computing. Even the things that don’t think themselves will continue collecting and reporting the massive quantities of data that feed cognitive systems.
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ibm, tss, cloud, mobile, appliances
    
IBM APAC
Published By: Oracle     Published Date: Aug 09, 2013
Talent management has moved to the top of the CEO’s agenda. In a 2012 global survey of CEOs and CFOs by the Economist Intelligence Unit, 53 percent of these leaders said that insufficient talent within their organization could harm them financially over the next 12 months. The number expressing financial concerns rose to 67 percent at organizations with more than 1,500 employees. Moreover, a full 83 percent of HR and business executives believe that talent programs need to be improved, according to Deloitte’s 2012 report Talent Edge 2020. With statistics like these, it’s no wonder there’s more pressure than ever on HR leaders to make the right talent decisions for their organizations and to source the right talent management systems to maximize the value of their workforce.
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oracle, talent cloud, cloud, talent management, human resources
    
Oracle
Published By: Oracle     Published Date: Aug 15, 2013
Talent management has moved to the top of the CEO’s agenda. In a 2012 global survey of CEOs and CFOs by the Economist Intelligence Unit, 53 percent of these leaders said that insufficient talent within their organization could harm them financially over the next 12 months. The number expressing financial concerns rose to 67 percent at organizations with more than 1,500 employees. Moreover, a full 83 percent of HR and business executives believe that talent programs need to be improved, according to Deloitte’s 2012 report Talent Edge 2020. With statistics like these, it’s no wonder there’s more pressure than ever on HR leaders to make the right talent decisions for their organizations and to source the right talent management systems to maximize the value of their workforce.
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oracle, talent cloud, cloud, talent management, enterprise applications, human resource technology, business technology
    
Oracle
Published By: Pure Storage     Published Date: Apr 10, 2019
Deep learning opens up new worlds of possibility in artificial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly, and legacy storage systems are not keeping up. Advanced AI applications require a modern all-flash storage infrastructure that is built specifically to work with high-powered analytics.
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Pure Storage
Published By: Cognizant     Published Date: Oct 23, 2018
Incorporating artificial intelligence into your business systems and processes is a journey unlike any other digital technology implementation. There is no utility AI. Every company must chart its own path to success. This white paper offers insights and recommendations to help organizations identify use cases, pilot and learn from them, and then repeat the process so AI becomes a key element in the organization’s continuous improvement.
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cognizant, artificial intelligence
    
Cognizant
Published By: IBM     Published Date: Jul 26, 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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scalability, data warehousing, resource planning
    
IBM
Published By: Pure Storage     Published Date: Jan 12, 2018
Deep learning opens up new worlds of possibility in artificial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Advanced AI applications require a modern all-fl ash storage infrastructure that is built specifically to work with high-powered analytics.
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data, deep learning, automated, intelligence, pure storage
    
Pure Storage
Published By: HERE Technologies     Published Date: Sep 27, 2018
Location has become paramount to building new apps, services, experiences and business models. If data is the new oil, then location is the crude oil. This is why most of the top location platform players have been developing technologies to power next-generation autonomous mobility systems. And the “richness” of location data and real-time intelligence are becoming strong monetization opportunities. The 2018 Counterpoint Research Location Ecosystems Update compared 16 location platform vendors, including Google, TomTom and Mapbox. Learn why the HERE Open Location Platform – described as super-rich, always up-to-date, and a neutral offering – is a leader in the location data arena.
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HERE Technologies
Published By: Pure Storage     Published Date: Apr 18, 2018
Deep learning opens up new worlds of possibility in artifi cial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Advanced AI applications require a modern all-fl ash storage infrastructure that is built specifically to work with high-powered analytics.
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Pure Storage
Published By: Pure Storage     Published Date: Apr 10, 2019
Deep learning opens up new worlds of possibility in artificial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Advanced AI applications require a modern all-flash storage infrastructure that is built specifically to work with high-powered analytics.
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Pure Storage
Published By: IBM     Published Date: Jan 27, 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.
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IBM
Published By: BAE Systems     Published Date: Dec 29, 2015
How to secure your network without busting your IT budget
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bae systems, applied intelligence, fortune 500, business security, network security, it management, security products, security systems
    
BAE Systems
Published By: IBM     Published Date: Sep 11, 2017
This book is written for readers who have varying levels of familiarity with ODM. It doesn’t focus on any particular vendor’s offering; instead, it talks about the features of ODM as a model for managing operational decision-making. This book isn’t about offline business intelligence systems. While those systems are very valuable, the focus of this book is on automated decisions that can be executed in real time in conjunction with your business applications and processes.
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odm, management, operation-decision making, intelligence systems
    
IBM
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: IBM     Published Date: Jul 02, 2018
Businesses are struggling with numerous variables to determine what their stance should be regarding artificial intelligence (AI) applications that deliver new insights using deep learning. The business opportunities are exceptionally promising. Not acting could potentially be a business disaster as competitors gain a wealth of previously unavailable data to grow their customer base. Most organizations are aware of the challenge, and their lines of business (LOBs), IT staff, data scientists, and developers are working to define an AI strategy. IDC believes that this emerging environment is to date still highly undefined, even as businesses must make critical decisions. Should businesses develop in-house or use VARs, systems integrators, or consultants? Should they deploy on-premise, in the cloud, or in some hybrid form? Can they use existing infrastructure, or do AI applications and deep learning require new servers with new capabilities? We believe that many of these questions can be
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IBM
Published By: Flexera     Published Date: Sep 08, 2016
This white paper will discuss the key elements of Software Vulnerability Management and how a properly deployed solution based on Vulnerability Intelligence will help organizations to maintain compliance and further secure their IT systems from breaches, attacks and data loss
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Flexera
Published By: Pure Storage     Published Date: Dec 05, 2018
Deep learning opens up new worlds of possibility in artificial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Read this MIT Technology Review custom paper to learn how advanced AI applications require a modern all-flash storage infrastructure that is built specifically to work with high-powered analytics, helping to accelerate business outcomes for data driven organizations.
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Pure Storage
Published By: Workforce Software     Published Date: Apr 03, 2012
We will go over a brief introduction of what workforce analytics is, and take a look at why it is sometimes so difficult to get the information we need out of our HR or Business Intelligence systems. We will also dive into the important metrics we should consider as HR professionals and what metrics will ultimately drive your business forward.
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human resources, hr management, workforce software, workforce analytics, employees, business analytics
    
Workforce Software
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