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Published By: IBM     Published Date: Dec 05, 2016
Learn directly from KONE's expert about their recent IoT experience in implementing predictive maintenance (PMQ) and IoT. The session will cover: 1) KONE's business area that the PMQ and IoT solution is supporting, and the metrics used to measure success; 2) KONE's Predictive Maintenance and IoT Platform use case, key personas, savings and benefits realized; and 3) Observations from implementation, including: a) The analytics journey at KONE; b) Organizational change (culture, processes, etc.); c) Measurable maintenance benefits; d) Implementation considerations, learnings, going forward; and e) Future projects and capabilities.
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ibm, leadership, watson, watson iot, predictive maintenance
    
IBM
Published By: Intel Security     Published Date: Apr 06, 2016
Spend less on prevention; invest in detection, response and predictive capabilities.
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security architect, information, continuous response, incident, monitoring, remediation, adaptive architecture, protection, advanced threats, prevention, detection
    
Intel Security
Published By: Interactive Intelligence     Published Date: Sep 11, 2013
Cloud communications provide myriad benefits for organizations, including speed of deployment, the ability to future-proof infrastructure and applications, business continuity, predictable monthly payments, and many more. Most organizations turn to the cloud in order to cost-effectively access enhanced capabilities while eliminating the complexity of deploying and managing premises-based solutions. Cloud-based contact center solutions offer additional benefits, notably the ease of adding or removing agents as needed based on fluctuating or seasonal traffic, ease of deploying remote or at-home agents, and ease of adding multi-channel services.
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interactive intelligence, contact centers, organizations, deployment, cloud, solutions, seasonal traffic, infrastructure
    
Interactive Intelligence
Published By: KPMG     Published Date: Dec 05, 2018
Some HR leaders are confidently harnessing the disruptive technologies that will transform the HR function. How ready are you for the digital workplace? Read this report – which includes insights from HR leaders in some of the world’s most successful organisations – to understand: the anticipated impact of artificial intelligence and disruptive technologies the growing importance of the employee experience the potential of predictive analytics the changes required in workplace culture and capabilities for successful transformation.
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KPMG
Published By: MicroStrategy     Published Date: Aug 21, 2019
To survive and thrive in an era of accelerating digital disruption, organizations require accessible data, actionable insights, continuous innovation, and disruptive business models. It’s no longer enough to prioritize and implement analytics – leaders are being challenged to stop doing analytics just for analytics’ sake and focus on defined business outcomes. In addition, these leaders are being challenged to bring predictive capabilities and even prescriptive recommended actions into production at scale. As AI and accelerated growth and transformation become top of mind, many enterprises are realizing that their current segmented analytics approach isn’t built to last, and that real transformation will require proper endto- end data management, data security, and a data processing platform company-wide. The year 2019 will be a turning point for many organizations that realize being data-driven doesn’t guarantee future success.
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MicroStrategy
Published By: Mintigo     Published Date: Sep 05, 2018
One of the most common use cases for AI in B2B is to make predictions about which accounts are most likely to buy and which leads are most likely to convert. However, use cases for AI are being extended beyond predictive account and lead scoring to include decision-making and process automation as well. Download this SiriusDecisions technology perspective on Predictive Analytics and Artificial Intelligence Technology to learn more. This paper will cover: • The benefits, evolution and capabilities of AI technology solutions for B2B organizations • The core and extended capability groups of AI • The business priorities supported by AI Fill out the form to get your free copy!
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Mintigo
Published By: Red Hat     Published Date: Dec 15, 2015
New Gartner research predicts that 75% of IT organizations will have a bimodal capability by 2017. Bimodal is a critical capability that combines the solid conventional capabilities of IT alongside a capability to respond to the level of uncertainty and the need for agility required for a digital transformation. According to Gartner, half of IT organizations that have a bimodal capability will make a mess. Learn more about Gartner's predictions for common mistakes that CIOs will make and how to avoid them.
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Red Hat
Published By: Red Hat     Published Date: May 05, 2015
New Gartner research predicts that 75% of IT organizations will have a bimodal capability by 2017. Bimodal is a critical capability that combines the solid conventional capabilities of IT alongside a capability to respond to the level of uncertainty and the need for agility required for a digital transformation. According to Gartner, half of IT organizations that have a bimodal capability will make a mess. Learn more about Gartner's predictions for common mistakes that CIOs will make and how to avoid them.
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red hat, gartner, bimodal it, cio, it architecture, hybrid, ntegration, devops, automation, sourcing, innovation management
    
Red Hat
Published By: SAS     Published Date: Jan 17, 2018
The Internet of Things can bring big benefits. But what exactly is IoT, and how are different industries taking advantage of it? This TDWI e-book explores in detail what IoT and the Industrial IoT (IIoT) do for retailers, the automotive industry, state and local governments working with utilities firms, and the manufacturing industry. Common themes include connectedness, data-driven insights, predictive capabilities and transformation.
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SAS
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
Published By: SAS     Published Date: Aug 28, 2018
With the widespread adoption of predictive analytics, organizations have a number of solutions at their fingertips. From machine learning capabilities to open platform architectures, the resources available to innovate with growing amounts of data are vast. In this TDWI Navigator Report for Predictive Analytics, researcher Fern Halper outlines market opportunities, challenges, forces, status and landscape to help organizations adopt technology for managing and using their data. As highlighted in this report, TDWI shares some key differentiators for SAS, including the breadth and depth of functionality when it comes to advanced analytics that supports multiple personas including executives, IT, data scientists and developers.
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SAS
Published By: Schneider Electric     Published Date: May 31, 2019
Gartner predicts that by 2020, 90 percent of organizations will adopt hybrid infrastructure management capabilities. However, this isn’t easy. With a hybrid IT environment can come complexity, confusion, and even infrastructure fragmentation. And, if you leave this poorly managed, your users, business, and most of all customers will certainly start to notice. In this eBook, we’ll explore the evolution of the enterprise data center, impacts of cloud-powered digital solutions, and how to manage hybrid IT solutions.
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hybrid, digital solutions, schneider electric
    
Schneider Electric
Published By: Splunk     Published Date: Aug 17, 2018
IT organizations are now responsible for delivering seamless customer experiences while preventing outages and managing an increasing number of systems. With growing responsibility placed on IT, there is an opportunity to drive strategy for company-wide business processes and operations. Companies using machine data powered platforms like Splunk collect disparate data types to quickly troubleshoot and monitor systems. By adding predictive capabilities, IT can glean critical insights for the business and develop strategic initiatives on issues that matter. Download the white paper “Embracing the Strategic Opportunity of IT” to learn how to: Enable a business aware IT organization Unlock operational efficiencies Solve problems with predictive analytics
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it event management, it event management tool, event logs, aiops platform, what is aiops, aiops vendor, market guide for aiops platforms, guide for aiops platforms, monitor end to end, itoa, aiops, predictive analysis, machine learning, event correlation, event management, it operations analytics, it analytics, ibm watson, hp monitoring, hp operations manager
    
Splunk
Published By: SPSS     Published Date: Jun 30, 2009
This paper describes why and how Enterprise Feedback Management (EFM) is a critical component in solving the problem of enhancing customer-driven innovation and improving the predictive capabilities of the IT organization.
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predictive enterprise, spss, enterprise feedback management, efm, customer-driven innovation, crm, customer relationship management, customer experience, consumer behavior, actionable insight, centralized system, feedback programs, push orientation, lifecycle-based approach, customer retention, churn rate, compliance, internal r&d, behavioral data, descriptive data
    
SPSS
Published By: SPSS, Inc.     Published Date: Mar 31, 2009
This paper describes why and how Enterprise Feedback Management (EFM) is a critical component in solving the problem of enhancing customer-driven innovation and improving the predictive capabilities of the IT organization.
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predictive enterprise, spss, enterprise feedback management, efm, customer-driven innovation, crm, customer relationship management, customer experience, consumer behavior, actionable insight, centralized system, feedback programs, push orientation, lifecycle-based approach, customer retention, churn rate, compliance, internal r&d, behavioral data, descriptive data
    
SPSS, Inc.
Published By: TIBCO Software     Published Date: Jul 22, 2019
Connected Intelligence in Insurance Insurance as we know it is transforming dramatically, thanks to capabilities brought about by new technologies such as machine learning and artificial intelligence (AI). Download this IDC Analyst Infobrief to learn about how the new breed of insurers are becoming more personalized, more predictive, and more real-time than ever. What you will learn: The insurance industry's global digital trends, supported by data and analysis What capabilities will make the insurers of the future become disruptors in their industry Notable leaders based on IDC Financial Insights research and their respective use cases Essential guidance from IDC
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TIBCO Software
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