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Results 1 - 15 of 15Sort Results By: Published Date | Title | Company Name
Published By: Oracle     Published Date: Dec 21, 2018
After talking to 27 leading CFOs, the Economist Intelligence Unit finds that the finance team’s data analytics skills put the CFO in the driving seat of digital change.The result is that the CFO has a new responsibility to: • Help other business units meet their digital ambitions•Make relevant data visible across the business• Develop goals and metrics for digital success
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Oracle
Published By: Dell EMC     Published Date: Feb 23, 2017
During the course of research efforts in the all-flash array (AFA) space, IDC is still encountering IT executives, particularly CIOs and CFOs, who have an outdated perspective on relevant cost metrics for comparing all-flash solutions with legacy hard disk drive (HDD)–based systems. In IDC's view, flash is an absolute requirement for performance reasons in any 3rd Platform computing environment. While most understand the need for flash performance, there is still a subset that does not view the broader use of flash in the enterprise as cost effective
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Dell EMC
Published By: Akamai Technologies     Published Date: Mar 09, 2017
ENGAGE AND SATISFY FINANCIAL SERVICES CUSTOMERS In order to stay relevant and retain today’s “always-on”, mobile customers, financial institutions must prioritize and innovate. According to a recent Akamai FinServ industry survey conducted by TechValidate, almost half of the respondents are “behind” or “slightly behind” their peers with regard to their mobile capabilities. Download a free report with detailed findings and takeaways from the survey to find out how to maximize customer acquisition, increase retention, and drive card usage. You’ll also learn: - Current mobile strategies and barriers to adoption - The right metrics to measure success - The most important factors in a mobile banking experience
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financial services customer engagement, customer service, mobile customers, akamai, mobile strategies, mobile banking
    
Akamai Technologies
Published By: Success Factors     Published Date: Jul 08, 2014
From data to intelligence in 5 simple steps. The best place, we suggest, is with expert, practical guidance. Download this informative resource.
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success factors, big data, intelligence, hr metrics, practical guidance
    
Success Factors
Published By: Oracle     Published Date: Mar 07, 2019
An On-Demand Webinar with the Economist Intelligence Unit (EIU) and a leading CFO, exploring the changing role of today’s CFO, based on EIU’s recent CFO survey. Learn how CFOs and Finance: • Are well-placed to exercise digital leadership • Make relevant data visible across the business • Develop goals and metrics for digital success
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Oracle
Published By: Oracle     Published Date: Mar 01, 2019
After talking to 27 leading CFOs, the Economist Intelligence Unit finds that the finance team’s data analytics skills put the CFO in the driving seat of digital change. The result is that the CFO has a new responsibility to: • Help other business units meet their digital ambitions • Make relevant data visible across the business • Develop goals and metrics for digital success Watch the webinar
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Oracle
Published By: Achievers     Published Date: Jan 17, 2014
Knowledge and strategic relationships fuel many organizations in today’s rapidly changing, global economy. As such, organizations need to leverage the individuals—and their networks—that possess the most relevant knowledge, whether they are current employees or are only loosely connected to the organization. To do this, organizations should create and leverage peer collaboration networks that enable them to identify and connect with individuals who have the unique skills, knowledge, and capabilities these organizations need. Bersin’s Research, Why Reputations and Networks Matter in the Open Talent Economy, indicates that this approach works in driving value—organizations that have effectively used internal reputation networks and profile databases have been able to increase key metrics such as employees’ time to productivity and innovation levels.
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talent management, employee enagement, human resources
    
Achievers
Published By: Success Factors     Published Date: Jul 10, 2014
From data to intelligence in 5 simple steps. The best place, we suggest, is with expert, practical guidance. Download this informative resource.
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success factors, big data, intelligence, hr metrics, practical guidance, human resources
    
Success Factors
Published By: SAS     Published Date: Mar 14, 2014
This Q&A with Tom Davenport, Director of Research for the International Institute for Analytics (IIA), will help you understand how analytics is evolving, where you need to go, and how to get there.
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sas, data categorization, retrieval and quality, data visualization, data governance program, data management, data quality, business objectives, quality data, accuracy, lineage, structural consistency, relevant metrics, analytics, analytical study, visualization deployment, deployment, institute for analytics
    
SAS
Published By: SAS     Published Date: Mar 14, 2014
This paper explores the challenges organizations have today in implementing a data governance program via an actual business case. It highlights SAS technology that can help you solve many of those challenges.
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sas, data categorization, retrieval and quality, data visualization, data governance program, data management, data quality, business objectives, quality data, accuracy, lineage, structural consistency, relevant metrics, business relevance, visualization deployment, deployment, institute for analytics, data center
    
SAS
Published By: SAS     Published Date: Mar 14, 2014
This report examines how data visualization can help organizations unleash the full value of information, and outlines key considerations to guide the solution evaluation process.
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sas, data categorization, retrieval and quality, data visualization, data governance program, data management, data quality, business objectives, quality data, accuracy, lineage, structural consistency, relevant metrics, business relevance, visualization deployment, deployment, institute for analytics, productivity, data center
    
SAS
Published By: SAS     Published Date: Mar 14, 2014
Managing expectations before, during and after the adoption of visualization software is crucial. Users should know what the rollout process will look like and how it will take place, and have clear goals for using the tool. Make sure that the desired outcome isn’t just look-and-feel. Creating beautiful charts and graphs is not a substitute for practical business decisions.
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sas, data categorization, retrieval and quality, data visualization, data governance program, data management, data quality, business objectives, quality data, accuracy, lineage, structural consistency, relevant metrics, business relevance, visualization deployment, deployment, institute for analytics, data center
    
SAS
Published By: SAS     Published Date: Mar 14, 2014
This paper explores ways to qualify data control and measures to support the governance program. It will examine how data management practitioners can define metrics that are relevant.
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sas, data quality, business objectives, quality data, accuracy, lineage, structural consistency, relevant metrics, business relevance, measured value, emergent patterns, quality metrics, potential classifications, data analyst, scorecard, reporting the scorecard, improve scorecard, business process
    
SAS
Published By: SAS     Published Date: Mar 14, 2014
This paper will consider the relevance of measurement and monitoring – defining inspection routines, inserting them into the end-to-end application processing, and reporting the results.
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sas, data quality, business objectives, quality data, accuracy, lineage, structural consistency, relevant metrics, business relevance, measured value, emergent patterns, quality metrics, potential classifications, data analyst, scorecard, reporting the scorecard, improve scorecard, business process, productivity, data center
    
SAS
Published By: SAS     Published Date: Mar 14, 2014
Jill Dyche and SpectraDynamo explains the importance of understanding how to manage data and issues regarding data categorization, retrieval and quality.
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sas, data categorization, retrieval and quality, spectradynamo, telemetry data, data governance program, data management, data quality, business objectives, quality data, accuracy, lineage, structural consistency, relevant metrics, business relevance, measured value, emergent patterns, quality metrics, data center
    
SAS
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