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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: 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: 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: Amazon Web Services     Published Date: Feb 01, 2018
Moving Beyond Traditional Decision Support Future-proofing a business has never been more challenging. Customer preferences turn on a dime, and their expectations for service and support continue to rise. At the same time, the data lifeblood that flows through a typical organization is more vast, diverse, and complex than ever before. More companies today are looking to expand beyond traditional means of decision support, and are exploring how AI can help them find and manage the “unknown unknowns” in our fast-paced business environment.
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predictive, analytics, data lake, infrastructure, natural language processing, amazon
    
Amazon Web Services
Published By: Datarobot     Published Date: May 14, 2018
The DataRobot automated machine learning platform captures the knowledge, experience, and best practices of the world’s leading data scientists to deliver unmatched levels of automation and ease-of-use for machine learning initiatives. DataRobot enables users of all skill levels, from business people to analysts to data scientists, to build and deploy highly-accurate predictive models in a fraction of the time of traditional modeling methods
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Datarobot
Published By: BMC ESM     Published Date: Aug 20, 2009
There is a natural progression from reactive to proactive, and ultimately predictive technology, and this progression corresponds to the maturity level of your IT organization and the tools you leverage.
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bmc, predictive technology, tools, it tools, itil, predictive intelligence, dynamic thresholding
    
BMC ESM
Published By: BMC ESM     Published Date: Aug 20, 2009
See the highlights of BMC’s Application Performance and Analytics; a predictive, resourceful and intelligent solution that empowers IT Operations to reduce mean time to repair (MTTR), avoid problems with early warning, find problems faster using fewer resources, ensure applications meet business requirements and put the right person on the right problem, every time.
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bmc, application performance and analytics, it operations, mttr, mean time to repair, data center
    
BMC ESM
Published By: SAS     Published Date: Apr 21, 2015
High-performing organizations leverage the power of analytics by channeling their efforts in four areas: focus, adopt, adapt, and activate. These companies have embraced a new paradigm that promotes agility, fast execution, and lasting organizational change.
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SAS
Published By: SAS     Published Date: Apr 21, 2015
Exploring predictive analytics for the first time? Malene Haxholdt, global marketing manager for business analytics at SAS, explains what you need to know to get started.
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SAS
Published By: Epicor     Published Date: Jul 18, 2017
Big-box retailers often have the resources, product variety, and name recognition to get ahead of smaller competitors. However, small and midsize businesses are able to crush the big-box stores where it matters most—the customer experience. Whether by design, geography, or as a matter of principle, small and midsize retailers are closer to their customers and are able to engage them on a level that big-box stores simply cannot. This closeness—combined with the right retail management system—allows smaller business to deliver a superior shopping experience with: • Special orders • Predictive inventory analysis • Digital, mobile channels and device integration This white paper—written by Innovative Retail Technologies and sponsored by Epicor—explains how the right software solution leads to a more agile retail strategy, which then leads to a better experience for your customers.
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retail store software, retail sales software, retail saas, business retail software, epicor eagle, benefits of epicor eagle, benefits of retail pos, advantages of retail saas, advantages of retail store software
    
Epicor
Published By: Epicor     Published Date: Jan 09, 2018
Successful financial management really comes down to providing employees with the tools they need to make the most informed decisions at any given time. Accurate forecasts, budgets, and plans lead to smarter investments. In this Aberdeen research report, top performers are found to provide their employees with the tools that enable success, in addition to exhibiting the following characteristics: • Predictive • Informed • Efficient • Agile Download the report to find out how Epicor enterprise resource planning (ERP) solutions can help you improve your processes and turn your manufacturing business into a financial planning, budgeting, and forecasting leader.
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enterprise resource planning (erp), financial management, manufacturing, budgeting, forecasting
    
Epicor
Published By: HP     Published Date: Nov 05, 2014
HP Proactive Care helps prevent problems and stabilize IT by utilizing secure, realtime, predictive analytics and proactive consultations when your products are connected to HP. Benefits include: • Problem prevention • Predictive analytics for proactive reports • Personalized consultation with a Technical Account Manager • Rapid access to advanced technical experts Download this customer brief now.
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proactive care, it stability, problem protection, reduce risks, prevent it issues, care service, gen9, customer brief
    
HP
Published By: BMC Software     Published Date: Jul 22, 2015
In this white paper, you’ll discover an enterprise approach to Big Data that leverages workload automation to: - Integrate Hadoop workflows into your enterprise processes to deliver new applications faster - Resolve issues faster with predictive analytics, automated alerts, and early problem detection - Achieve compliance and governance adherence
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big data, business processes, enterprise systems, hadoop, compliance
    
BMC Software
Published By: FICO     Published Date: Feb 06, 2017
FICO is helping the bank construct the most predictive and effective expected loss models possible and is also helping it assess risk impact across portfolios
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FICO
Published By: BlackLine     Published Date: Aug 06, 2018
The biotechnology and pharmaceutical industry is among the most heavily regulated industries in the world, challenged by evolving regulations, complex compliance requirements and close regulatory scrutiny. At the same time, companies must address the market pressures of globalization, the use of predictive data analytics and digital technologies, and the industry’s ongoing consolidation. In this challenging environment, confidence in internal controls is crucial.
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BlackLine
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: Genesys     Published Date: Jun 13, 2018
When building artificial intelligence (AI) into your business strategy, it’s easy to become distracted by all the new technologies on the market—each one promising a better customer experience. Make decisions based on facts, not misconceptions. When you evaluate AI technologies, consider these facts: • Bots working with human agents enables a seamless customer journey • Automated self-service costs as little as 20 cents per interaction • A single platform makes it easier to deliver personalized, proactive and predictive experiences See how AI connects customer conversations in this new analyst guide, 2017 ContactBabel Inner Circle Guide to Self-Services.
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artificial intelligence, customer experience, customer journey, self-servic e, personalization
    
Genesys
Published 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.
Published By: IBM Watson Health     Published Date: Sep 29, 2017
In the world of value-based healthcare, your data is the key to extracting the most actionable insights that provide real value to your organization. But getting to those insights can prove difficult, especially if you have to connect disparate data sources. You need transparency into key insights that can help your team make more informed decisions for the success of your organization. In this listicle, we explore five ways an analytics solution can help you transform your organization through the power of insight. From risk modeling to predictive analytics, utilizing the right mix of analytics can improve patient outcomes and ultimately move your organization closer to your ideal value-based care model
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value-based care, analytics, insights, data, business intelligence, ehr, fee-for-service, cognitive, predictive, outcomes, infrastructure
    
IBM Watson Health
Published By: IBM Watson Health     Published Date: Nov 10, 2017
To address the volume, velocity, and variety of data necessary for population health management, healthcare organizations need a big data solution that can integrate with other technologies to optimize care management, care coordination, risk identification and stratification and patient engagement. Read this whitepaper and discover how to build a data infrastructure using the right combination of data sources, a “data lake” framework with massively parallel computing that expedites the answering of queries and the generation of reports to support care teams, analytic tools that identify care gaps and rising risk, predictive modeling, and effective screening mechanisms that quickly find relevant data. In addition to learning about these crucial tools for making your organization’s data infrastructure robust, scalable, and flexible, get valuable information about big data developments such as natural language processing and geographical information systems. Such tools can provide insig
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population health management, big data, data, data analytics, big data solution, data infrastructure, analytic tools, predictive modeling
    
IBM Watson Health
Published By: Bluewater Learning     Published Date: Nov 02, 2018
Would you like to make better-informed decisions about where to invest your time & resources? Are you interested in gaining more insight into what is working, what isn't, & why? There is a movement towards advanced & predictive analytics in the Learning & Talent Management space. But what does that really mean? Bluewater's team of consultants & developers can help you define what analytics means for your company.
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Bluewater Learning
Published By: TIBCO Software     Published Date: Oct 03, 2018
The Insurance industry continues to undergo significant transformation, with new technologies, business models, and competitors entering the market at an increasing rate. To be successful in attracting and retaining the most valuable customers, insurance companies must innovate and increase the speed at which they respond to customer demands. Traditionally, the insurance software market was dominated by a handful of specialist vendors with products that were initially expensive, difficult to deploy, costly to maintain, and did not provide the speed needed for today's market. Now there has been a shift away from these "black box" applications to platforms that allow insurers to make their algorithmic IP available to business users, allowing much faster response to business demands. The algorithmic platform approach also comes at a fraction of the cost of black box solutions, while delivering advanced analytical techniques like Machine Learning and Artificial Intelligence (AI).
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artificial intelligence, machine learning, dynamic pricing, predictive claims, real-time fraud, contextual customer experience, operational effectiveness
    
TIBCO Software
Published By: TIBCO Software     Published Date: Mar 04, 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: 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, banking
    
TIBCO Software
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