predictive capabilities

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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
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
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
By: Group M_IBM Q1'18     Published Date: Feb 15, 2018
See how you can turn data into actionable insights with predictive analytics. Take our brief assessment to learn which analytical capabilities will enable you to find the greatest value in your data and make confident, accurate business decisions.
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analytics assessment, business decisions, predictive analytics, analytics
    
Group M_IBM Q1'18
By: Domino Data Lab     Published Date: Feb 08, 2019
As data science becomes a critical capability for companies, IT leaders are finding themselves responsible for enabling data science teams with infrastructure and tooling. But data science is much more like an experimental research organization than the engineering and business teams that IT organizations support today. Compounding the challenge, data science teams are growing fast, often by 100% a year. This guide will quickly help you understand what data science teams do to build their predictive models and how to best support them. Learn how to modernize IT’s approach to ensure your company’s data science teams perform their best, and maximize impact to the business. Some highlights include: Why data science should not be treated like engineering. How to go beyond simple infrastructure allocation and give data science teams capabilities to manage their workflows and model lifecycle. Why agility and special hardware to support burst computing are so important to data science break
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Domino Data Lab
By: Domino Data Lab     Published Date: May 23, 2019
As data science becomes a critical capability for companies, IT leaders are finding themselves responsible for enabling data science teams with infrastructure and tooling. But data science is much more like an experimental research organization than the engineering and business teams that IT organizations support today. Compounding the challenge, data science teams are growing fast, often by 100% a year. This guide will quickly help you understand what data science teams do to build their predictive models and how to best support them. Learn how to modernize IT’s approach to ensure your company’s data science teams perform their best, and maximize impact to the business. Some highlights include: Why data science should not be treated like engineering. How to go beyond simple infrastructure allocation and give data science teams capabilities to manage their workflows and model lifecycle. Why agility and special hardware to support burst computing are so important to data science break
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Domino Data Lab
By: Alteryx, Inc.     Published Date: Sep 06, 2017
Predictive analytics is on the verge of widespread adoption as enterprises become more interested in deploying predictive capabilities. In fact, a recent 2017 TDWI education survey, ranked predictive analytics the top analytics-related topic respondents wanted to learn about. The TDWI Navigator Report- Predictive Analytics provides a comprehensive overview of the state of the predictive analytics market. Download this report to better understand: Opportunities and obstacles of implementing predictive analytics Market forces and trends driving the adoption of predictive analytics Features and market landscapes that define predictive analytics Download this report today to get a better sense on how your organization can take advantage of predictive analytics to drive change in your business.
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Alteryx, Inc.
By: BMC ASEAN     Published Date: Dec 18, 2018
From the impact of disruptive technologies to the imperative of digital transformation, businesses today must find new ways to innovate or risk being left behind. While data flowing rapidly between the Internet of Things and multi-cloud computing environments brings tremendous opportunity, there’s also a great deal of complexity. Artificial intelligence (AI) and machine learning (ML) are part of the new wave of solutions capturing the minds of enterprise leaders to respond to these new opportunities and complexities. Digitally literate leaders who are highly cognizant of this wave, are jumping in headfirst and applying AI and ML to solve real business challenges—making enterprise goals of enabling cost savings via smarter operations and decision making come to fruition. BMC Cognitive Service Management (CSM) addresses the complexities of multi-cloud computing by applying intelligence, automation, and predictive capabilities. CSM employs a differentiated approach with a more holistic
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BMC ASEAN
By: BMC     Published Date: Nov 19, 2018
Learn how BMC Cognitive Service Management (CSM) addresses the complexities of multi-cloud computing by applying intelligence, automation, and predictive capabilities
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bmc, cognitive service management, service management, itsm, automation, digital transformation
    
BMC
By: IBM     Published Date: Aug 01, 2012
Discover how using predictive analytics can help your company convert prospects and cross-sell to existing customers. The campaign optimization capabilities provided with predictive analytics offer an unprecedented level of targeting and coordination across all channels - quickly resulting in decreased costs and increased revenue.
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ibm, marketing, technology, campaign profitability, predictive analytics, analytics, roi, crm, customer, business, white paper
    
IBM
By: Adobe     Published Date: Aug 02, 2017
With Adobe Analytics and Adobe Audience Manager—both part of Adobe Marketing Cloud—media companies can overcome today’s audience intelligence challenges. Adobe Analytics is an industry-leading solution for applying real time analytics and detailed segmentation across all of your marketing channels. A unified platform and customer ID unlock powerful customer intelligence and help you discover and retain high-value audiences. Make forward-looking decisions with its predictive intelligence capabilities, and find out which of your marketing efforts are paying off with its attribution functionality.
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goals and kpis, data warehouse, resource management, insight loop, content and campaigns, audience optimisation
    
Adobe
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
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
By: IBM     Published Date: Oct 07, 2015
Whether you work in marketing, customer service, sales, finance, operations or another area of your business, IBM predictive analytics software puts a wealth of advanced capabilities at your fingertips, anywhere you need them—on premises, on cloud or as a hybrid solution.
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IBM
By: IBM     Published Date: Oct 07, 2015
Integrating TM1 BI and Predictive capabilities to unlock the hidden value of your data
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IBM
By: IBM     Published Date: Oct 17, 2016
See how you can turn data into actionable insights with predictive analytics. Take our brief assessment to learn which analytical capabilities will enable you to find the greatest value in your data and make confident, accurate business decisions.
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ibm, analytics, spss, stats, modeler, predictive analytics
    
IBM
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
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
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.
By: CrowdTwist     Published Date: Apr 16, 2018
In order for brands to compete and provide the level of personalization consumers have already come to expect, marketers need to work quickly to develop competencies around their abilities to collect contextual and anticipatory insight and meet customers in the moments that matter most to them. Now is the time for marketers to invest in technology that supports data capture, segmentation, predictive analytics, and machine learning. With these capabilities in place, brands should be on track to build rich first party profiles of customers across all channels and maximize customer lifetime value by creating relevant experiences at all stages of the customer lifecycle.
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customers, predictive, branding, consumers, competition, lifecycle
    
CrowdTwist
By: IBM     Published Date: Mar 07, 2014
8 to 10 page Analyst Whitepaper by Ptak / Noel addressing the need for IT to bring Analytics technology to IT to help them be more proactive, predictive providing faster mean time to repair. This paper will also explore how IBM is helping customers with it's new IT Analytics platform that offers Search, Predict and Optimize capabilities.
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ibm, big data, operational insight, it analytics, optimize capabilities, predict capabilities
    
IBM
By: IBM     Published Date: Aug 08, 2012
This white paper examines the role social media can play in presenting a more strategic view of customer data and how the right combination of technologies can deliver insight to help companies more effectively meet perpetually shifting consumer demands expressed through, and influenced by, these dynamic communication channels. Discover the implications of social media for marketing and sales, as well as IT. And learn the how and why social media tools and applications can be integrated with existing technology investments.
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social media analytics, consumer insight, marketing digitization, ibm, facebook, strategic considerations, lower cost, influence, intimacy, scale, speed, assess, measure, integrate, predictive capabilities, virtualization, analysis
    
IBM
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
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