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Published By: Hewlett Packard Enterprise     Published Date: Jul 18, 2018
"This research by Nimble Storage, a Hewlett Packard Enterprise Company, outlines the top five causes of application delays. The report analyzes more than 12,000 anonymized cases of downtime and slow performance. Read this report and find out: -Top 5 causes of downtime and poor performance across the infrastructure stack -How machine learning and predictive analytics can prevent issues -Steps you can take to boost performance and availability "
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Hewlett Packard Enterprise
Published By: FICO     Published Date: Mar 22, 2018
Predictive analytics provide the foresight to understand cybersecurity risk exposure. Cybersecurity strategies often consist of “whack-a-mole” exercises focused on the perpetual detection and mitigation of vulnerabilities. As a result, organizations must re-think the ever-escalating costs associated with vulnerability management. After all, the daily flow of cybersecurity incidents and publicized data breaches, across all industries, calls into question the feasibility of achieving and maintaining a fully effective defense. The time is right to review the risk management and risk quantifcation methods applied in other disciplines to determine their applicability to cybersecurity. Security scoring is a hot topic, and rightfully so. When evaluating ways to integrate these scores into your cybersecurity strategy, be sure to look for an empirical approach to model development. The FICO Enterprise Security Score is the most accurate, predictive security score on the market.
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FICO
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: 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.
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Group M_IBM Q2'19
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