data science

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Published 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.
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sas, healthcare, healthcare models, episode analytics, analytics, data management
    
SAS
Published By: Intel     Published Date: Jun 07, 2017
Using the Integrated Analytics Hub, data analytics projects have already accounted for an estimated quarterly savings on marketing digital-media expenditures of approximately USD 170,000. Download this white paper to find out more.
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intel, analytics, data, data analytics, data science
    
Intel
Published By: Intel     Published Date: Jun 07, 2017
Intel's Bob Rogers, chief data scientist for big data solutions, sat down with Dan Magestro, research director at the international Institute of Analytics (IIA), to discuss the power of asking questions when assessing an organisation's analytics maturity. Read on to find out more.
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intel, analytics, data, data analytics, data science
    
Intel
Published By: Teradata     Published Date: Oct 15, 2012
Does your organization struggle to get new business insights from all data types with rapid exploration?
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data scientists, analyst, statistician, quants, quantitative analyst, scientist, data science, business technology
    
Teradata
Published By: Aberdeen Group     Published Date: Nov 13, 2015
Aberdeen’s Content Marketing survey revealed that while 95% of marketers are using or considering using a content marketing strategy, there are some distinct differences between those using content well and those just using content. The Best-in-Class are not only creating content at volume, they are taking a much more data-driven approach to their content marketing strategy — and it’s paying off. Find out how.
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customer acquisition, marketing leads, marketing challenges, marketing messages, contact management, data science, demand generation, email marketing
    
Aberdeen Group
Published By: Aberdeen Group     Published Date: Nov 13, 2015
Aberdeen’s research shows that 90% of Best-in-Class marketers report fueling lead generation efforts with content marketing. What do you need to know to follow this best practice of the Best-in-Class? That’s exactly what this Knowledge Brief is intended to uncover.
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customer acquisition, marketing leads, marketing challenges, marketing messages, contact management, data science, demand generation, email marketing
    
Aberdeen Group
Published By: Aberdeen Group     Published Date: Nov 23, 2015
This report examines the pressing need to break down data silos due to the damage they cause to analytical initiatives and user engagement. Read this report to find out more.
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customer acquisition, marketing leads, marketing challenges, marketing messages, contact management, data science, demand generation, email marketing
    
Aberdeen Group
Published By: Waterline Data & Research Partners     Published Date: May 18, 2015
Waterline Data automates the cataloging of data assets and provides an Amazon.com-like guided shopping approach to data discovery that is intended to take the guesswork out of targeting the right data.
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waterline, big data, automation, cataloging, processing, analysis, assets, data science
    
Waterline Data & Research Partners
Published By: Waterline Data & Research Partners     Published Date: May 18, 2015
In this report, Forrester Research recommends that application development and delivery (AD&D) professionals working on BI and big data initiatives get the best out of both by designing and integrating them in a flexible data platform.
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waterline, big data, automation, cataloging, processing, analysis, assets, data science
    
Waterline Data & Research Partners
Published By: Oracle HCM Cloud     Published Date: Jun 07, 2016
Leveraging analytics to drive business growth is top-of-mind for corporate (C-Suite) leaders, prompting HR executives to take a more strategic, data-driven approach to workforce management. Learn the art and science of combining workforce data, business data and IT expertise together to allow HR departments to make more effective and efficient decisions about people.
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Oracle HCM Cloud
Published By: IBM     Published Date: Jul 14, 2016
This video describes how data scientists, analysts and business users can save precious time by using a combination of SPSS and Spark to uncover and act on insights in big data.
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ibm, data, analytics, predictive business, ibm spss, apache spark, coding, data science
    
IBM
Published By: IBM     Published Date: Oct 21, 2016
The greatest challenge of the big data revolution is making sense of all the information generated by today's vast digital economy. It's well enough for an organization to collect every slice of data it can reach, but how does it extract value from this massive volume of information?
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ibm, analytics, data science, data, big data, aps data, aps, data management
    
IBM
Published By: IBM     Published Date: Oct 21, 2016
Between the Internet of Things, customer experience and loyalty programs, social network monitoring, connected enterprise systems and other information sources, today's organizations have access to more data than they ever had before-and frankly, more than they may know what to do with. The challenge is to not just understand that data, but actualize it and use it to recognize real business value. This ebook will walk you through a sample scenario with Albert, a data scientist who wants to put text analytics to work by using the Word2vec algorithm and other data science tools.
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ibm, analytics, aps, aps data, open data science, data science, word2vec, business technology
    
IBM
Published By: IBM     Published Date: Jan 18, 2017
It's all well enough for an organization to collect every slice of data it can reach, but having more data doesn't mean you'll automatically get better insights. First, you have to figure out what you want from your data you have to find its value.
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ibm, aps data, data science, open data science, analytics
    
IBM
Published By: IBM     Published Date: Jan 18, 2017
In the domain of data science, solving problems and answering questions through data analysis is standard practice. Data scientists experiment continuously by constructing models to predict outcomes or discover underlying patterns, with the goal of gaining new insights. But data scientists can only go so far without support.
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ibm, analytics, aps data, open data science, data science, data engineers
    
IBM
Published By: IBM     Published Date: Jan 18, 2017
Data matters more than ever to business success. But value does not come from data alone. Rather, it comes from the insights enabled by data. No matter what your role is, or where you are in your data journey, you are looking for ways to drive innovation.
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ibm, analytics, aps data, open data science, data science, apache spark
    
IBM
Published By: Teradata     Published Date: May 01, 2015
Creating value in your enterprise undoubtedly creates competitive advantage. Making sense of the data that is pouring into the data lake, accelerating the value of the data, and being able to manage that data effectively is a game-changer. Michael Lang explores how to achieve this success in “Data Preparation in the Hadoop Data Lake.” Enterprises experiencing success with data preparation acknowledge its three essential competencies: structuring, exploring, and transforming. Teradata Loom offers a new approach by enabling enterprises to get value from the data lake with an interactive method for preparing big data incrementally and iteratively. As the first complete data management solution for Hadoop, Teradata Loom enables enterprises to benefit from better and faster insights from a continuous data science workflow, improving productivity and business value. To learn more about how Teradata Loom can help improve productivity in the Hadoop Data Lake, download this report now.
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data management, productivity, hadoop, interactive, enterprise
    
Teradata
Published By: xMatters     Published Date: Sep 22, 2014
When it comes to data breaches and service outages, it’s no longer a question of if but when. Governments worldwide increasingly have new laws, pending legislation, privacy regulations and “strong suggestions” for protecting sensitive information and taking action when breaches or service outages occur. Get the Complimentary White Paper and learn how you need to prepare for these new laws and more. The white paper examines current regional legislation and how you can implement communication best practices for maintaining transparency and trust in the face of consumer-facing service disruptions.
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communication, best practices, data, breaches, enterprise, consumer, confidence, science
    
xMatters
Published By: Oracle     Published Date: Jan 28, 2015
Traditional brick-and-mortar multi-channel retailers have online competitors ruled by data scientists who define retail as a data mining and optimization problem. John Bible, Senior Director of Retail Data Science and Insight at Oracle Retail discusses the science of pricing, and predictions for the role of science in retail over the next five years.
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Oracle
Published By: Oracle     Published Date: Jan 28, 2015
Retailers continue to collect this data and many have made good use of it, segmenting and targeting customers and rewarding loyal behavior with discounts and offers. Still, many sense that there’s untapped potential. They’re right. With the cost of data storage plummeting and the capabilities of analytical tools on the rise, this data’s value is set to skyrocket. John Bible, Senior Director of Retail Data Science and Insight at Oracle Retail shares his view on how insights from these vast data storehouses can scientifically inform retailers’ decision-making in critical strategic, tactical and operational areas, including category management, shelf space allocation and new product introductions.
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Oracle
Published By: Hortonworks     Published Date: Apr 05, 2016
The advent of big data revolutionized analytics and data science and created the concept of new data platforms, allowing enterprises to store, access and analyze vast amounts of historical data. The world of big data was born. But existing data platforms need to evolve to deal with the tsunami of data-in-motion being generated by the Internet of Anything (IoAT).
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Hortonworks
Published By: ServiceSource     Published Date: Nov 01, 2013
In this book we describe best practices honed through 13 years of experience and partnership with some of the leading technology companies in the world. These best practices will give you insight into three key areas: • Data management & renewal opportunity generation • Sales strategy & execution • Continuing the renewal cycle We hope you enjoy this book!
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reducing customer churn, servicesource, recurring revenue, higher profit margins, drive innovation, drive performance, saas companies, competitive markets
    
ServiceSource
Published By: HiQ Labs     Published Date: Apr 18, 2017
Experts predict the number of M&A transactions will increase in 2017, but the nature of M&A is changing. The old ways of collecting data are getting to be too slow, too expensive, and too subjective. The ideal M&A transaction relies on accurate, actionable scientific insights into the target’s workforce to support the investigation, due diligence and integration aspects of M&A. hiQ Labs applies scientific rigor to publicly available data sets to forecast which employees are at risk of leaving, map the target workforce’s skills onto the buyer’s company, and identify which employees have the skills critical to the deal’s success, so M&A leaders get a faster, cheaper, and accurate solution based on science.
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hiq labs, m&a, talent
    
HiQ Labs
Published By: Oracle     Published Date: Jul 08, 2015
John Bible, Senior Director of Retail Data Science and Insight at Oracle Retail shares his view on how insights from these vast data storehouses can scientifically inform retailers’ decision-making in critical strategic, tactical and operational areas, including category management, shelf space allocation and new product introductions.
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Oracle
Published By: Oracle     Published Date: Jul 08, 2015
John Bible, Senior Director of Retail Data Science and Insight at Oracle Retail discusses the science of pricing, and predictions for the role of science in retail over the next five years.
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Oracle
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