predictive

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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: TIBCO Software     Published Date: Aug 20, 2019
The oil field is being dynamically transformed through the connective power of the Internet, the advancements in remote connected sensors, and the possibilities of machine learning and artificial intelligence (AI). As the quest for hydrocarbons and alternative energy sources extends into deeper and harsher environments, operators, service companies, and asset owners are leveraging technology advancements to ensure their employees are safer, their fields are more productive, and their capital assets are operating at peak efficiency.
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machine learning, predictive analytics, hydrocarbons, oil&gas, cybersecurity, asset efficiency, safety
    
TIBCO Software
Published By: TIBCO Software     Published Date: Aug 20, 2019
“How will we use all the data from the smart grid?”
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greater efficiency, demand forecasting, advanced analytics, smart meters, predictive analytics, data security
    
TIBCO Software
Published By: TIBCO Software     Published Date: Aug 02, 2019
A perfect storm of legislation, market dynamics, and increasingly sophisticated fraud strategies requires you to be proactive in detecting fraud quicker and more effectively. TIBCO’s Fraud Management Platform allows you to meet ever-increasing requirements faster than traditional in-house development, easier than off-the-shelf systems, and with more control because you’re in charge of priorities, not a vendor. All this is achieved using a single engine that can combine traditional rules with newer predictive analytics models. In this webinar you will learn: Why a fraud management platform is necessary How to gain an understanding of the components of a fraud management platform The benefits of implementing a fraud management platform How the TIBCO platform has helped other companies Unable to attend live? We got you. Register anyway and receive the recording after the event.
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TIBCO Software
Published By: RMS     Published Date: Jul 25, 2019
The insurance industry boasts some of the most sophisticated modeling capabilities in the world. And yet the average property underwriter does not have access to the kind of predictive tools that carriers use at a portfolio level to manage risk aggregation, streamline reinsurance buying and optimize capitalization.
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RMS
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: 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
Published By: ETQ     Published Date: Jul 10, 2019
Product recalls cost food and beverage companies millions of dollars each year, but 56% of last year's recalls across the US, UK and Ireland were preventable. With compliance challenges becoming more complex and public scrutiny exponentially greater, one recall can cause a world of trouble. The new US Food Safety Modernization Act (FSMA) seeks to encourage a more proactive and predictive approach to food safety. Learn how automation can help you comply with this new regulation by 2020 and avoid a costly product recall.
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ETQ
Published By: Group M_IBM Q3'19     Published Date: Jun 24, 2019
Today's energy, environment, and utility companies face an unfamiliar landscape in which they must integrate alternative energies, expand situational awareness across the system, and deepen their relationships with customers-all while continuing to deliver reliable, safe, and affordable electricity, gas and water to everyone.By combining predictive analytics with IoT, cloud and mobile technologies, utilities companies can Lower costs, improve operational efficiency and increase equipment reliability.
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Group M_IBM Q3'19
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: Genesys     Published Date: Jun 19, 2019
Successfully managing a contact center requires a collaborative, multidisciplinary approach to handle a broad range of operational and tactical tasks. Planning, day-to-day operations and quality management must be seamlessly orchestrated, along with human resources functions like recruitment, learning and development, and employee scheduling. Read this executive brief to learn how to transition to an AI strategy that can take your team – and business results – to the next level. See how you can: Create an AI strategy with a single data model that includes routing, interaction analytics, forecasting/scheduling and predictive engagement Harness the power of your data to align customers with the best resource Drive employee effectiveness by ensuring you hire the right people and manage their performance to drive their success over the long term
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Genesys
Published By: Sierra Wireless     Published Date: Jun 19, 2019
By simplifying the ability of companies to securely extract, orchestrate and act on data from when it is generated by energy assets to when it is transmitted to the cloud, Octave simplifies the development and commercialization of Energy IoT applications. With Octave, energy companies are empowered to realize the Energy IoT’s tremendous potential, with new demand response, energy efficiency optimization, predictive maintenance and other applications that maximize the value created by energy assets and minimize their environmental impact. In doing so, these Energy IoT applications can reduce energy costs, improve customer engagement, lower greenhouse gas emissions and increase energy reliability. Start with Sierra to learn more about how our Octave D2C data orchestration solution can help you bring to market Energy IoT applications that reimagine the future of energy.
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Sierra Wireless
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: KPMG     Published Date: Jun 06, 2019
HR’s most confident leaders are using data, predictive insights and AI to transform HR into a new value driver. Discover what it takes to become an HR transformation trailblazer. Read this report to discover: • how trailblazers are exploiting uncertainty to drive new competitive advantage • which technologies HR leaders are investing in • what it means to integrate human and digital labour in a collaborative workplace • six priorities for forward-looking HR leaders.
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KPMG
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: TIBCO Software     Published Date: May 16, 2019
Banks globally are betting big on artificial intelligence and machine learning to give them the technological edge they need for more real-time, personalized and predictive banking services. A framework will help both differentiate early winners and provide them with sustained advantages in intelligence. Download this IDC Analyst Infobrief to learn about how the world’s best banks are becoming more personal, more predictive, and more real-time than ever. What you will learn: 8 trends that reflect bank’s readiness for connected intelligence 9 pitfalls to avoid & 9 ways to bridge the gaps The personal, real-time and predictive building blocks of AI & ML for banks Notable leaders based on IDC Financial Insights’ research and their respective use cases Essential guidance from IDC to leading banks
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data, analytics, customer, banks, intelligence, capabilities, customers, insights
    
TIBCO Software
Published By: Forcepoint     Published Date: May 14, 2019
In Philip K. Dick's 1956 "The Minority Report," murder ceased to occur due to the work of the "Pre-Crime Division," that anticipated and prevented killings before they happened. Today, we are only beginning to see the impact of predictive analytics upon cybersecurity – especially for insider threat detection and prevention. Based on user interaction with data, CISOs and their teams emerge as the IT equivalent of a Pre-Crime Division, empowered to intervene before a violation is ever committed. Watch this webcast where we examine the technologies which make predictive analytics valuable, along with ethically minded guidance to strike the balance between vigilance and privacy.
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Forcepoint
Published By: Hewlett Packard Enterprise     Published Date: May 10, 2019
The performance of enterprise applications will have a direct impact on business activities and outcomes. The quality of the delivery of applications will depend on how smoothly the underlying data infrastructure operates. ? 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: May 10, 2019
Applications are the engines that drive today’s digital businesses. When the infrastructure that powers those applications is difficult to administer, or fails, businesses and their IT organizations are severely impacted. Traditionally, IT assumed much of the responsibility to ensure availability and performance. In the digital era, however, the industry needs to evolve and reset the requirements on vendors. HPE Nimble Storage has broken away from convention and transformed how storage is managed and supported with the HPE InfoSight predictive analytics platform. HPE engaged ESG to conduct a quantitative survey of the HPE Nimble Storage installed base, as well as non-HPE Nimble Storage customers, to better assess how HPE InfoSight positively impacts customer environments. To find out more download this whitepaper today.
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: May 10, 2019
Anwendungen sind die treibende Kraft bei den Abläufen im digitalen Unternehmen von heute. Wenn die Verwaltung der Infrastruktur hinter diesen Anwendungen Probleme bereitet oder sogar unmöglich ist, hat dies gravierende Aus? wirkungen auf die Unternehmen und deren IT?Abteilungen. Bisher hat die IT?Abteilung einen großen Teil der Verant? wortung für Verfügbarkeit und Leistung übernommen. Im digitalen Zeitalter muss die Branche jedoch die Anforderun? gen an die Anbieter weiterentwickeln und neu definieren.
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: Apr 26, 2019
With the maturing of the all-flash array (AFA) market, the established market leaders in this space are turning their attention to other ways to differentiate themselves from their competition besides just product functionality. Consciously designing and driving a better customer experience (CX) is a strategy being pursued by many of these vendors.This white paper defines cloud-based predictive analytics and discusses evolving storage requirements that are driving their use and takes a look at how these platforms are being used to drive incremental value for public sector organizations in the areas of performance, availability, management, recovery, and information technology (IT) infrastructure planning.
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Hewlett Packard Enterprise
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: Group M_IBM Q2'19     Published Date: Apr 10, 2019
Today's energy, environment, and utility companies face an unfamiliar landscape in which they must integrate alternative energies, expand situational awareness across the system, and deepen their relationships with customers-all while continuing to deliver reliable, safe, and affordable electricity, gas and water to everyone.By combining predictive analytics with IoT, cloud and mobile technologies, utilities companies can Lower costs, improve operational efficiency and increase equipment reliability.
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Group M_IBM Q2'19
Published By: Group M_IBM Q2'19     Published Date: Apr 10, 2019
Today's energy, environment, and utility companies face an unfamiliar landscape in which they must integrate alternative energies, expand situational awareness across the system, and deepen their relationships with customers-all while continuing to deliver reliable, safe, and affordable electricity, gas and water to everyone.By combining predictive analytics with IoT, cloud and mobile technologies, utilities companies can Lower costs, improve operational efficiency and increase equipment reliability.
Tags : 
    
Group M_IBM Q2'19
Published By: Group M_IBM Q2'19     Published Date: Apr 10, 2019
Today's energy, environment, and utility companies face an unfamiliar landscape in which they must integrate alternative energies, expand situational awareness across the system, and deepen their relationships with customers-all while continuing to deliver reliable, safe, and affordable electricity, gas and water to everyone.By combining predictive analytics with IoT, cloud and mobile technologies, utilities companies can Lower costs, improve operational efficiency and increase equipment reliability.
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Group M_IBM Q2'19
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