predictive business

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Published By: AWS     Published Date: Jul 24, 2019
Trupanion, a Seattle-based medical insurance provider for cats and dogs, needed to find data insights quickly. With only 1% of pet owners insured, the process of evaluating a claim to approve or deny payment was manual and time-consuming. Building accurate predictive models for decision-making required manpower, time, and technology that the small company simply did not have. DataRobot Cloud, built on AWS, helped Trupanion create an automated method for building data models using machine learning that reduced the time required to process claims from minutes to seconds. Join our webinar to hear how Trupanion transformed itself into an AI-driven organization, with robust data analysis and data science project prototyping that empowered the company to make better decisions and optimize business processes in less time and at a reduced cost. Join our webinar to learn: Why you don’t need to be an expert in data science to create accurate predictive models. How you can build and deploy pr
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AWS
Published By: Genesys     Published Date: Jun 19, 2019
Contact centers often pool agents into large groups of generalists to distribute work evenly. Skills-based routing takes this a step further with specialized groups. But neither approach scales properly to identify all opportunities and drive business outcomes on each interaction. Predictive routing uses artificial intelligence (AI) and machine learning to create balance—meeting targets and giving customers a personalized experience. Read Demystifying AI: Creating an AI partnership that maximizes business results to learn how predictive routing systematically: Evaluates historical and real-time data to make predictions; Makes the best customer-agent match to drive desired outcomes; Keeps agents engaged and reduces handle times.
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Genesys
Published 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
Published By: Oracle EMEA     Published Date: Apr 15, 2019
Forward-thinking enterprises understand what it takes to be successful in this data-rich, increasingly automated economy. According to the Harvard Business Review Analytic Services research report The Rise of Intelligent Automation: TurningComplexity into Profit, sponsored by Oracle, at least 7 in 10 executives understand that predictive analytics (80%) and AI and machine learning (68%) are important for the future of the business. Even as executives recognize the vital role data plays in their businesses, many are unable to take advantage of the value residing in their data. The old ways of collecting, managing, storing, and analyzing data are no longer effective, and are preventing businesses from extracting potential value. Many simply can’t execute on a data-driven vision.
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Oracle EMEA
Published 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
Published By: Domino Data Lab     Published Date: Feb 08, 2019
A data science platform is where all data science work takes place and acts as the system of record for predictive models. While a few leading model-driven businesses have made the data science platform an integral part of their enterprise architecture, most companies are still trying to understand what a data science platform is and how it fits into their architecture. Data science is unlike other technical disciplines, and models are not like software or data. Therefore, a data science platform requires a different type of technology platform. This document provides IT leaders with the top 10 questions to ask of data science platforms to ensure the platform handles the uniqueness of data science work.
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Domino Data Lab
Published By: Splunk     Published Date: Dec 11, 2018
Predictive IT is a powerful new approach that uses machine learning and artificial intelligence (AI) to predict incidents before they impact customers and end users. By using AI and predictive analytics, IT organizations are able to deliver seamless customer experiences that meet changing customer behavior and business demands. Discover the critical steps required to build your IT strategy, and learn how to harness predictive analytics to reduce operational inefficiencies and improve digital experiences. Download this executive brief from CIO to learn: 5 steps to an effective predictive IT strategy Where AI can help, and where it can’t How to drive revenue and exceptional customer experiences with predictive analytics
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predictive it, predictive it tools, predictive analytics for it, big data and predictive analytics
    
Splunk
Published By: Splunk     Published Date: Sep 10, 2018
collectd is an open source daemon that collects system and application performance metrics. With this data, collectd then has the ability to work alongside other tools to help identify trends, issues and relationships not easily observable. Read this e-book to get a deep dive into what collectd is and how you can begin incorporating it into your organization’s environment.
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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
    
Splunk
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: Hewlett Packard Enterprise     Published Date: Aug 23, 2018
Learn how predictive analytics and machine learning can help optimize application performance and meet the needs of the business with Nimble Storage Infosight. This ESG report highlights: • Optimal application performance and delivery is difficult to achieve in complex environments. • Many IT infrastructure and operations teams are stretched to the breaking point. • Predictive analytics and machine learning can be applied to great effect.
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Hewlett Packard Enterprise
Published By: Splunk     Published Date: Aug 22, 2018
The world of artificial intelligence (AI) has finally arrived at the doorstep of IT operations. As organizations move toward using both big data and machine learning functionality to support a variety of IT operations, processes and tasks, artificial intelligence for IT operations (AIOps) platforms have emerged as a one-stop solution. Gartner has released a “Market Guide for AIOps Platforms” that provides findings about the AIOps industry and its latest developments. Download your complimentary copy to: *Gain insight into the developing industry of AIOps and its future *Learn how to optimize IT operations powered by machine learning to drive business value *Compare different AIOps platform vendors and their range of capabilities
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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
    
Splunk
Published By: Splunk     Published Date: Aug 17, 2018
Imagine a world where incident alerts arrive 30 minutes before problems even begin — you’d actually have the power to prevent outages and deliver a truly seamless experience to your customers. Sound impossible? Think again — the right AIOps (Artificial Intelligence for IT Operations) solution can help you maintain uptime, reduce manual incident-management tasks and increase productivity.
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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
    
Splunk
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
    
Splunk
Published By: TIBCO Software     Published Date: Aug 15, 2018
TIBCO Spotfire® Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms. Spotfire Data Science provides a complete array of tools (from visual workflows to Python notebooks) for the data scientist to work with data of any magnitude, and it connects natively to most sources of data, including Apache™ Hadoop®, Spark®, Hive®, and relational databases. While providing security and governance, the advanced analytic platform allows the analytics team to share and deploy predictive analytics and machine learning insights with the rest of the organization, white providing security and governance, driving action for the business.
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TIBCO Software
Published By: TIBCO Software     Published Date: Aug 13, 2018
The combination of legislation, market dynamics, and increasingly sophisticated risk management strategies requires you to be proactive in detecting risks like fraud quicker and more effectively. Dynamic detection systems need to adapt to evolving compliance regulations, scale to deal with growing transaction volumes, detect sophisticated risk specific patterns, and reduce false-positives. TIBCO's Risk Management Accelerator uses a combination of predictive analytics, streaming analytics, and business process management to deliver a powerful and cost-effective system for detecting anomalies. Download this solution brief to learn more.
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TIBCO Software
Published By: Dell Server     Published Date: Aug 08, 2018
A fundamental people-process-technology transformation enables businesses to remain competitive in today’s innovation economy. Initiatives such as advanced security, fraud detection services, connected consumer Internet of Things (IoT) devices, augmented or virtual reality experience, machine and deep learning, and cognitively enabled applications drive superior business outcomes such as predictive marketing and maintenance. Superior business outcomes require businesses to consider IT a core competency. For IT, an agile, elastic, and scalable IT infrastructure forms the crucial underpinning for a superior service delivery model. Dell EMC’s Intelligent Automation powered by Intel® Xeon® Platinum processor simplifies the management and maintenance of its PowerEdge server hardware. Designed to drive down the cost and resources associated with server lifecycle management, Intelligent Automation relies on integrated Dell Remote Access Controller(iDRAC) and OpenManage server management soft
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Dell Server
Published By: BlackLine     Published Date: Aug 06, 2018
The capacity to be anticipatory (aware, predictive and adaptive) of emerging technology and trends in business, demographics, and the social environment impacting your organization and industry. It is crucial to be #FutureReady
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BlackLine
Published By: Hewlett Packard Enterprise     Published Date: Jul 18, 2018
"Learn how predictive analytics and machine learning can help optimize application performance and meet the needs of the business with Nimble Storage Infosight. This ESG report highlights: • Optimal application performance and delivery is difficult to achieve in complex environments. • Many IT infrastructure and operations teams are stretched to the breaking point. • Predictive analytics and machine learning can be applied to great effect."
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: Jul 18, 2018
"Learn how predictive analytics and machine learning can help optimize application performance and meet the needs of the business with Nimble Storage Infosight. This ESG report highlights: • Optimal application performance and delivery is difficult to achieve in complex environments. • Many IT infrastructure and operations teams are stretched to the breaking point. • Predictive analytics and machine learning can be applied to great effect."
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Hewlett Packard Enterprise
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes.
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TIBCO Software
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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TIBCO Software
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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TIBCO Software
Published By: Dell EMC & Intel     Published Date: Apr 13, 2018
A fundamental people-process-technology transformation enables businesses to remain competitive in today’s innovation economy. Initiatives such as advanced security, fraud detection services, connected consumer Internet of Things (IoT) devices, augmented or virtual reality experience, machine and deep learning, and cognitively enabled applications drive superior business outcomes such as predictive marketing and maintenance. Superior business outcomes require businesses to consider IT a core competency. For IT, an agile, elastic, and scalable IT infrastructure forms the crucial underpinning for a superior service delivery model. Dell EMC’s Intelligent Automation powered by Intel® Xeon® Platinum processor simplifies the management and maintenance of its PowerEdge server hardware. Designed to drive down the cost and resources associated with server lifecycle management, Intelligent Automation relies on integrated Dell Remote Access Controller(iDRAC) and OpenManage server management soft
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Dell EMC & Intel
Published By: Dell EMC & Intel     Published Date: Mar 16, 2018
A fundamental people-process-technology transformation enables businesses to remain competitive in today’s innovation economy. Initiatives such as advanced security, fraud detection services, connected consumer Internet of Things (IoT) devices, augmented or virtual reality experience, machine and deep learning, and cognitively enabled applications drive superior business outcomes such as predictive marketing and maintenance. Superior business outcomes require businesses to consider IT a core competency. For IT, an agile, elastic, and scalable IT infrastructure forms the crucial underpinning for a superior service delivery model. The more up to date the infrastructure, the more capable it is of supporting the scale and complexity of a changing application landscape. Current-generation applications must be supplemented and eventually supplanted with next-generation (also known as cloud-native) applications — each with very different infrastructure requirements. Keeping infrastructure up
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Dell EMC & Intel
Published 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
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