quantit

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Published By: Polycom     Published Date: Jul 24, 2014
Brains, not brawn: Fewer companies than ever before are shackled to the tyranny of the volume play: producing vast quantities of goods to reap razor-thin margins. Instead, manufacturing has been freed to search for the next big idea – and many of them. What’s empowering this idea revolution: automated processes, new technologies at the ready, and a thorough understanding of R&D’s costs and contributions? Realizing that there is strength in numbers, companies are creating virtual innovation hubs with valued partners, joining industry consortia, and opening up product development to crowdsourcing. What’s common to all: Companies are drawing closer to epicenters of talent, demand, and supply and moving faster than ever to commercialize great ideas. Are you ready?
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polycom, commodity, innovation, manufacturing, automation, r&d
    
Polycom
Published By: IBM     Published Date: Oct 13, 2017
Analytics is game-changing and can produce valuable insights from the ever-growing volume, velocity and variety of data. Business Intelligence (BI) provides the foundation for many types of Analytics. It enables companies to deliver exceptional customer experience, enhance marketing effectiveness, increase operational efficiencies, reduce financial risks, improve product quality and reliability, and so on. But businesses are also challenged to generate timecritical actionable insights and make a compelling financial business case for BI investments.
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ibm, cognos analytics, business intelligence, customer experience, marketing
    
IBM
Published By: Cognos     Published Date: Jun 19, 2007
This paper looks at research into the link between visual perception and understanding, and translates the findings into practical techniques that you can use to communicate more clearly with your data.
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visual communication, visual perception, graph, graphical representation, graphs, presentations, evaluation, presentation
    
Cognos
Published By: SAS     Published Date: Oct 18, 2017
With enhanced regulatory pressure, banks must continuously evaluate their risks. To meet these demands, the AML industry has turned to analytical/statistical methodologies to reduce false-positive alerts, increase monitoring coverage and reduce the rapidly escalating financial cost of maintaining their AML programs. An effective AML transaction monitoring strategy includes segmenting the customer base by analyzing customer activity and risk characteristics in order to monitor them more effectively. This paper explains how to blend both quantitative and qualitative methods to tune scenarios to identify the activity that poses the most risk to the bank.
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SAS
Published By: Janrain, Inc.     Published Date: Oct 29, 2012
Never before have digital marketers been blessed with such immense quantities of online customer data at our disposal, yet been so incapacitated by how to use it. This paper explores ways to collect value from customer related information.
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janrain, user management, vibrant audience, online users, user engagement, big data, customer related information, collect value
    
Janrain, Inc.
Published By: CDW     Published Date: Apr 04, 2016
Prefabricated modular data centers offer many advantages over traditionally built data centers, including flexibility, improved predictability, and faster speed of deployment. Cost , however, is sometimes stated as a barrier to deploying these designs. In this paper, we focus on quantifying the capital cost differences of a prefabricated vs. traditional 440 kW data center, both built with the same power and cooling architecture, in order to highlight the key cost drivers, and to demonstrate that prefabrication does not come at a capex premium . The analysis was completed and validated with Romonet’s Cloud-based Analytics Platform, a vendor-neutral industry resource.
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analysis, development management, data management, business intelligence, best practices
    
CDW
Published By: CDW - APC     Published Date: Apr 07, 2016
Prefabricated modular data centers offer many advantages over traditionally built data centers, including flexibility, improved predictability, and faster speed of deployment. Cost , however, is sometimes stated as a barrier to deploying these designs. In this paper, we focus on quantifying the capital cost differences of a prefabricated vs. traditional 440 kW data center, both built with the same power and cooling architecture, in order to highlight the key cost drivers, and to demonstrate that prefabrication does not come at a capex premium . The analysis was completed and validated with Romonet’s Cloud-based Analytics Platform, a vendor-neutral industry resource.
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analysis, development management, data management, business intelligence, best practices
    
CDW - APC
Published By: VMware     Published Date: May 10, 2012
This on-demand webcast from IDC and VMware will provide both quantitative measurement of the business value -- defined as the expected ROI -- and qualitative analysis associated with the use of VMware View.
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capital, operational costs, vmware virtualization, server virtualization, desktop virtualization, public cloud, private cloud, virtual machine
    
VMware
Published By: Bronto     Published Date: Sep 09, 2013
Bronto Software and Retail Systems Research have just published survey findings of 179 retailers regarding their holiday 2012 online marketing plans. Download the report to discover the quantitative findings.
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online marketing, holiday marketing, mobile marketing, social marketing
    
Bronto
Published By: Vision Critical     Published Date: Jun 23, 2009
Kodak's community-which boasts over 2,600 members to date-has been effective in combining quantitative and qualitative research initiatives, resulting in a more comprehensive understanding of consumer behavior, trends, and demand, which the company continues to use to its advantage. In addition to evaluating existing products and marketing initiatives, it has helped to identify new product and marketing opportunities through analysis of how members shop.
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kodak, online community, customer voice, customer data, crm, cost savings, vision critical, marketing research
    
Vision Critical
Published By: SAP     Published Date: Jun 27, 2009
Read this white paper by Don Tapscott and explore the criteria best-in-class retailers use for selecting business intelligence solutions. Companies that effectively harness the vast quantities of information that IT systems generate - both within the corporation and outside its walls - are poised to gain competitive advantage.
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sap, business intelligence, it systems, price, promotion, markdown, businessobjects, rfid
    
SAP
Published By: BlackBerry Cylance     Published Date: Jul 02, 2018
The information security world is rich with information. From reviewing logs to analyzing malware, information is everywhere and in vast quantities, more than the workforce can cover. Artificial intelligence (AI) is a field of study that is adept at applying intelligence to vast amounts of data and deriving meaningful results. In this book, we will cover machine learning techniques in practical situations to improve your ability to thrive in a data driven world. With clustering, we will explore grouping items and identifying anomalies. With classification, we’ll cover how to train a model to distinguish between classes of inputs. In probability, we’ll answer the question “What are the odds?” and make use of the results. With deep learning, we’ll dive into the powerful biology inspired realms of AI that power some of the most effective methods in machine learning today. Learn more about AI in this eBook.
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artificial, intelligence, enterprise
    
BlackBerry Cylance
Published By: SAS     Published Date: Mar 06, 2018
Imagine getting into your car and saying, “Take me to work,” and then enjoying an automated drive as you read the morning news. We are getting very close to that kind of scenario, and companies like Ford expect to have production vehicles in the latter part of 2020. Driverless cars are just one popular example of machine learning. It’s also used in countless applications such as predicting fraud, identifying terrorists, recommending the right products to customers at the right time, and correctly identifying medical symptoms to prescribe appropriate treatments. The concept of machine learning has been around for decades. What’s new is that it can now be applied to huge quantities of data. Cheaper data storage, distributed processing, more powerful computers and new analytical opportunities have dramatically increased interest in machine learning systems. Other reasons for the increased momentum include: maturing capabilities with methods and algorithms refactored to run in memory; the
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SAS
Published By: Schneider Electric     Published Date: Jun 04, 2014
When faced with the decision of upgrading an existing data center, building new, or leasing space in a retail colocation data center, there are both quantitative and qualitative differences to consider. The 10-year TCO may favor upgrading or building over outsourcing, however, this paper demonstrates that the economics may be overwhelmed by a business’ sensitivity to cash flow, cash cross-over point, deployment timeframe, data center life expectancy, regulatory requirements, and other strategic factors. This paper discusses how to assess these key factors to help make a sound decision.
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schneider, electric, data, infrastructure, upgrade, retail, outsource, own
    
Schneider Electric
Published By: Schneider Electric     Published Date: Jun 04, 2014
Standardized, scalable, pre-assembled, and integrated data center facility power and cooling modules provide a “total cost of ownership” (TCO) savings of 30% compared to traditional, built-out data center power and cooling infrastructure. Avoiding overbuilt capacity and scaling the design over time contributes to a significant percentage of the overall savings. This white paper provides a quantitative TCO analysis of the two architectures, and illustrates the key drivers of both the capex and opex savings of the improved architecture.
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schneider, electric, data, center, scalable, integrated, power, cooling
    
Schneider Electric
Published By: SAS     Published Date: Apr 13, 2011
Learn how organizations are using data mining to solve their problems, including a $1 billion decision that produced positive results.
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data mining, qualitative data, quantitative data, john f. elder, data quality, sas, bottom-line
    
SAS
Published By: SAS     Published Date: Apr 13, 2011
This paper will outline the value and methods involved in data mining across both quantitative and qualitative data. In addition, it will describe the data transformations necessary before doing such work, and the tools that are particularly valuable for mining mixed data types.
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business intelligence, michael lock, predictive analytics, business insight, business visibility, small to medium sized business
    
SAS
Published By: IBM     Published Date: Mar 03, 2015
View this webinar to learn how to understand your customers with quantitative and qualitative analytics.
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ibm, customer experience, quantitative analytics, qualitative analytics
    
IBM
Published By: IBM     Published Date: Apr 18, 2014
For many enterprises System z is central to modern analytics because of the vast quantities or rich data stored upon it – not to mention excellent qualities of service. Carl Olofson, an IDC analyst looks, at the role of the mainframe in relation to big data, how it has become a hub for modern day analytics, its ability to integrate information from other sources to enhance business decisions and how it is positioned for the future. Download this paper and learn.
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ibm, mainframe, platform, big data, analytics, big data and analytics, bda, big data technology
    
IBM
Published By: Active Power     Published Date: Nov 17, 2014
This paper provides a quantitative analysis of the in-service reliability of Active Power’s CleanSource 750HD UPS (uninterruptible power supply) system versus a double-conversion UPS with batteries.
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active power, data center power, data center batteries, power and cooling, energy, data center energy, power source
    
Active Power
Published By: Altiscale     Published Date: Mar 30, 2015
Implementing and scaling Hadoop to analyze large quantities of data is enormously complicated. Unforeseen, very challenging problems are to be expected. However, if you can learn to recognize the problems before a fire starts, you can prevent your hair (and your Hadoop implementation) from igniting. From the Hadoop experts at Altiscale, here are some of the danger signs and problems you should watch out for, as well as real-world lessons learned for heading them off.
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implementing and scaling, data analysis, hadoop scaling
    
Altiscale
Published By: IBM     Published Date: Jul 08, 2015
While the term 'big data' has only recently come into vogue, IBM has designed solutions capable of handling very large quantities of data for decades. IBM InfoSphere Information Server is designed to help organizations understand, cleanse, monitor, transform and deliver data.
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IBM
Published By: Dice     Published Date: Oct 07, 2013
Put up a job listing and you’ll get a number of resumes. Is that success? Quantity is never the goal. Quality is. So, what does it take to attract the best talent? If it were as simple as free meals, this article would be very short.
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dice, top tech talent, job posting, talent, human resources
    
Dice
Published By: Dice     Published Date: Feb 10, 2016
What are the top ways recruiters are using social media? Check out Dice’s Social Recruiting Survey to learn how sourcers use social to improve candidate quality and quantity, as well as time-to-hire.
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reachmail dice, social recruiting, social media, recruiting survey, candidate quality, time to hire, human resources
    
Dice
Published By: Dice     Published Date: Feb 10, 2016
Improve the quality and quantity of tech candidates applying to your jobs with Dice’s 6 Do’s and Don’ts of Creating Great Job Postings. You’ll also get 10 sample postings you can use as inspiration for your own tech jobs.
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reachmail dice, tech job postings, best practices, sample job postings, tech jobs, human resources
    
Dice
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