data science

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By: IBM     Published Date: Sep 02, 2014
Life Sciences organizations need to be able to build IT infrastructures that are dynamic, scalable, easy to deploy and manage, with simplified provisioning, high performance, high utilization and able to exploit both data intensive and server intensive workloads, including Hadop MapReduce. Solutions must scale, both in terms of processing and storage, in order to better serve the institution long-term. There is a life cycle management of data, and making it useable for mainstream analyses and applications is an important aspect in system design. This presentation will describe IT requirements and how Technical Computing solutions from IBM and Platform Computing will address these challenges and deliver greater ROI and accelerated time to results for Life Sciences.
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     IBM
By: Dell and Intel®     Published Date: Jun 18, 2015
The rapid evolution of big data technology in the past few years has changed forever the pursuit of scientific exploration and discovery. Along with traditional experiment and theory, computational modeling and simulation is a third paradigm for science. Its value lies in exploring areas of science in which physical experimentation is unfeasible and insights cannot be revealed analytically, such as in climate modeling, seismology and galaxy formation. More recently, big data has been called the “fourth paradigm" of science. Big data can be observed, in a real sense, by computers processing it and often by humans reviewing visualizations created from it. In the past, humans had to reduce the data, often using techniques of statistical sampling, to be able to make sense of it. Now, new big data processing techniques will help us make sense of it without traditional reduction
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     Dell and Intel®
By: Revolution Analytics     Published Date: May 09, 2014
As the primary facilitator of data science and big data, machine learning has garnered much interest by a broad range of industries as a way to increase value of enterprise data assets. Through techniques of supervised and unsupervised statistical learning, organizations can make important predictions and discover previously unknown knowledge to provide actionable business intelligence. In this guide, we’ll examine the principles underlying machine learning based on the R statistical environment. We’ll explore machine learning with R from the open source R perspective as well as the more robust commercial perspective using Revolution Analytics Enterprise (RRE) for big data deployments.
Tags : revolution analytics, data science, big data, machine learning
     Revolution Analytics
By: RMS     Published Date: Jul 25, 2019
U.S. Flood is a high-gradient, intricate peril incorporating various sources, and causing a variety of effects. It requires sophisticated models, data science, and analytics technology to properly understand and assess each risk.
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     RMS
By: SAS     Published Date: Aug 19, 2019
With the combination of electronic health records, rich repositories of claims data, medical device outputs, laboratory and prescription systems, real-world data and the data mined from other information technology systems, the health and life sciences ecosystem can now gain new perspective. Download this complimentary paper to learn more about how health care data has the power to transform the sector, helping to address the industry’s biggest challenges surrounding costs and quality of patient care. By adopting solutions that allow them to both produce and consume data analytics insights in a way that better guides clinical and business strategies, innovative health care organizations can learn not only to survive but also thrive in the decades to come.
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     SAS
By: Zaloni     Published Date: Apr 23, 2019
Although data and analytics are highlighted throughout the popular press as well as in trade publications, too many managers think the value of this data processing is limited to a few numerically intensive fields such as science and finance. In fact, big data and the insights that emerge from analyzing it will transform every industry, from “precision farming” to manufacturing and construction. Governments must also be alert to the value of data and analytics as the enabler for smart cities. Institutions that master available data will leap ahead of their less statistically adept competitors through many advantages: finding hidden opportunities for efficiency, using data to become more responsive to clients, and developing entirely new and unanticipated product lines. The average time spent by most companies on the S&P 500 Index has decreased from an average of 60 to 70 years to only 22 years. There are winners and losers in the changes that come with the evolution of both technology
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     Zaloni
By: Uberflip     Published Date: Dec 20, 2018
In today’s world, marketers know that producing content isn’t enough. If they’re going to continue to make an investment in creating content, they need to do more to ensure it performs. We’ve long since known that combining content with a remarkable experience will allow it to reach its full potential, and allow marketers to see results. But as with any emerging category, content experience was not without its detractors. After all, what kind of results could you expect from an investment in the experience around that content? If you’ve ever wondered why you should care about content experience, and wanted something a little more concrete than a few anecdotes from marketers, or third-party stats, then look no further.
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     Uberflip
By: AWS     Published Date: Dec 15, 2017
Healthcare and Life Sciences organizations are using data to generate knowledge that helps them provide better patient care, enhances biopharma research and development, and streamlines operations across the product innovation and care delivery continuum. Next-Gen business intelligence (BI) solutions can help organizations reduce time-to-insight by aggregating and analyzing structured and unstructured data sets in real or near-real time. AWS and AWS Partner Network (APN) Partners offer technology solutions to help you gain data-driven insights to improve care, fuel innovation, and enhance business performance. In this webinar, you’ll hear from APN Partners Deloitte and hc1.com about their solutions, built on AWS, that enable Next-Gen BI in Healthcare and Life Sciences. Join this webinar to learn: How Healthcare and Life Sciences organizations are using cloud-based analytics to fuel innovation in patient care and biopharmaceutical product development. How AWS supports BI solutions f
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     AWS
By: Adobe     Published Date: Nov 09, 2017
Marketing leaders are asking their analytics teams to provide better insights into customers, prospects and journeys, and a more accurate assessment of the impact of marketing tactics. Use this research to find a digital marketing analytics tool to support your needs. This Magic Quadrant is intended for chief marketing of?cers (CMOs), marketing analytics and data science practitioners, and other digital marketing leaders involved in the selection of systems to support marketing analytics requirements.
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     Adobe
By: Cognizant     Published Date: Oct 03, 2017
Impact that situation awareness can have on extended supply chain operations w/focus on logistics companies
Tags : data science, predictive analytics, applications services, systems integration, business process management, digital transformation, social mobile analytics cloud (smac), integrated cloud services
     Cognizant
By: Cognizant     Published Date: Sep 19, 2017
Focus on creating consistent terminology in order to generate insights from the digital data encircling employees, partners, processes and customers.
Tags : data science, predictive analytics, applications services, systems integration, business process management, digital transformation, social mobile analytics cloud (smac), integrated cloud services
     Cognizant
By: Cognizant     Published Date: Sep 21, 2017
Additional insight on Forbes Research that ends with four “How To Get Started” steps.
Tags : data science, predictive analytics, applications services, systems integration, business process management, digital transformation, social mobile analytics cloud (smac), integrated cloud services
     Cognizant
By: Cognizant     Published Date: Sep 21, 2017
The impact that state-of-the-art simulation and modeling techniques can have on supply chain operations.
Tags : data science, predictive analytics, applications services, systems integration, business process management, digital transformation, social mobile analytics cloud (smac), integrated cloud services
     Cognizant
By: Dome9     Published Date: Apr 25, 2018
Last year at this time, we forecast a bumpy ride for infosec through 2017, as ransomware continued to wreak havoc and new threats emerged to target a burgeoning Internet of Things (IoT) landscape. ‘New IT’ concepts – from DevOps to various manifestations of the impact of cloud – seemed poised to both revolutionize and disrupt not only the implementation of security technology, but also the expertise required of security professionals as well. Our expectations for the coming year seem comparatively much more harmonious, as disruptive trends of prior years consolidate their gains. At center stage is the visibility wrought by advances in data science, which has given new life to threat detection and prevention – to the extent that we expect analytics to become a pervasive aspect of offerings throughout the security market in 2018. This visibility has unleashed the potential for automation to become more widely adopted, and not a moment too soon, given the scale and complexity of the thre
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     Dome9
By: Oracle     Published Date: Dec 21, 2018
Join Oracle’s CX and Marketing Strategy Director, Wendy Hogan, and Senior Vice President Oracle Marketing, Shashi Seth, as they tell how AI, machine learning and data science can engage customers, automate tasks and build ROI. Reaching the right customers on the right channel at the right time, brings rewards for CMOs who embrace these innovations, including engaged customers and increased ROI. Be inspired by the new-generation AI, machine learning and data science and take your marketing to the next level.
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     Oracle
By: SAS     Published Date: Nov 04, 2015
In a panel discussion at the 12th annual SAS Health Analytics Executive Forum in May 2015, leaders from Dignity Health, Horizon Blue Cross Blue Shield of New Jersey, Janssen Pharmaceuticals and SAS shared what they have done to prove the value of analytics to their business leaders – and what has worked for them as they developed an analytic culture in their organizations and put analytic insights to work.
Tags : sas, healthcare, healthcare models, episode analytics, analytics
     SAS
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