quality management

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‘A Little Extra Service’ Raises Customer Satisfaction and Lowers Costs

Published By: Oracle     Published Date: Jan 16, 2014
You need an answer fast. You searched online and almost got the answer, but require a little more information without having to call someone. What do you do?
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crm best practices, crm software, customer data management, customer experience & engagement, customer relationship management (crm), lead generation, lead management, lead nurturing
    
Oracle

Modernizing HCM: Why the Digital Employment Experience Matters

Published By: Adobe     Published Date: Mar 16, 2016
Competition is the number one pressure faced by today’s HCM teams – by a 69% margin! Of all the pressures that contemporary HR teams face, finding and keeping quality talent ranks above everything else. As a part of that, Best-in-Class organizations need to focus on optimizing the employment experience, from hiring and onboarding, to ongoing management and transition. This report from Aberdeen explores how electronic signature solutions, as well as other digital HR technologies, can improve the employment experience throughout the journey. Read this report to learn: • Why Best-in-Class HR departments are investing in employee-friendly technologies • How digital solutions can impact employee experience, and why that matters for HR • How electronic signatures complement HRIS applications and streamline many HR processes
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hr organizations, hris, esignature, customer management, sales effectiveness, human capital management, knowledge management
    
Adobe

Data Quality: A Survival Guide to Marketing

Published By: SAP     Published Date: Jun 23, 2009
In this paper, Frank Dravis, Six Factors Consulting, discusses how even with the finest marketing organizations, the success of marketing ultimately comes down to the data.
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single platform, data integration, data quality, quality management, soa, architecture, soa, sap businessobjects data services
    
SAP

Overall Approach to Data Quality ROI

Published By: SAP     Published Date: Jun 23, 2009
Learn the importance of Data Quality and the six key steps that you can take and put into process to help you realize tangible ROI on your data quality initiative.
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roi, data quality, sap, return-on-investment, crm, erp, enterprise resource management, customer relationship management
    
SAP

A Roadmap to Data Migration Success

Published By: SAP     Published Date: Feb 21, 2008
Many significant business initiatives and large IT projects depend upon a successful data migration. Your goal is to minimize as much risk as possible through effective planning and scoping. This paper will provide insight into what issues are unique to data migration projects and offer advice on how to best approach them.
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sap, data architect, data migration, business objects, information management software, bloor, sap r/3, application
    
SAP

Data Quality Strategy: A Step-by-Step Approach

Published By: SAP     Published Date: Mar 10, 2009
Learn about the importance of having a data quality strategy and setting the overall goals. The six factors of data are also explained in detail and how to tie it together for implementation.
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sap, data quality, strategy, project management, erp, enterprise resource planning, enterprise software
    
SAP

Three Keys to Better Data-Driven Decisions: What You Should Know... Right Now

Published By: SAP     Published Date: Jun 30, 2011
This white paper explores why today's executives still lack the relevant information or data quality to make decisions in a timely manner. Inside, learn about the biggest decisions-making challenges facings modern businesses and three keys to achieving better data-driven decisions.
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sap, smbs, high-quality data, erp software solution, decision management, data visibility, data quality, corporate strategy
    
SAP

Customer Story: Synaptics Accelerates Innovation with Improved Quality and Lifecycle Management

Published By: Oracle     Published Date: May 08, 2015
A case study of how Synaptics Inc. improved their innovation practices with the help of Oracle Innovation Management Cloud Solution.
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innovation, management, cloud computing
    
Oracle

Using analytics and collaboration to improve healthcare quality and outcomes

Published By: IBM     Published Date: Jul 01, 2015
This white paper discusses how organizations can benefit from implementing collaboration and analytics processes in the three core areas
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healthcare analytics, analytics technology, quality assurance, wellness monitoring, performance analysis, patient self-management
    
IBM

5 Data management for analytics best practices  

Published By: SAS     Published Date: Mar 06, 2018
For data scientists and business analysts who prepare data for analytics, data management technology from SAS acts like a data filter – providing a single platform that lets them access, cleanse, transform and structure data for any analytical purpose. As it removes the drudgery of routine data preparation, it reveals sparkling clean data and adds value along the way. And that can lead to higher productivity, better decisions and greater agility. SAS adheres to five data management best practices that support advanced analytics and deeper insights: • Simplify access to traditional and emerging data. • Strengthen the data scientist’s arsenal with advanced analytics techniques. • Scrub data to build quality into existing processes. • Shape data using flexible manipulation techniques. • Share metadata across data management and analytics domains.
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SAS

LNS Research: Quality 4.0 Impact and Strategy Handbook

Published By: SAS     Published Date: Mar 06, 2018
The most recent decade has seen rapid advances in connectivity, mobility, analytics, scalability, and data, spawning what has been called the fourth industrial revolution, or Industry 4.0. This fourth industrial revolution has digitalized operations and resulted in transformations in manufacturing efficiency, supply chain performance, product innovation, and in some cases enabled entirely new business models. This transformation should be top of mind for quality leaders, as quality improvement and monitoring are among the top use cases for Industry 4.0. Quality 4.0 is closely aligning quality management with Industry 4.0 to enable enterprise efficiencies, performance, innovation and business models. However, much of the market isn’t focusing on Quality 4.0, since many quality teams are still trying to solve yesterday’s problems: inefficiency caused by fragmented systems, manual metrics calculations, quality teams independently performing quality work with minimal cross-functional own
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SAS

Scalable Data Quality: A Seven Step Plan for Any Organization

Published By: Melissa Data Corp.     Published Date: Nov 18, 2008
This white paper describes the seven steps you need to develop a plan for data quality – one that scales to your growing business needs.
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melissa data, data quality, contact data verification, address verification, validate address, address verification software, address verify, address validation software
    
Melissa Data Corp.

The Real Cost of Bad Data: The 1-10-100

Published By: Melissa Data Corp.     Published Date: Nov 18, 2008
What are the long-term costs of bad data? This white paper gives you the answers and tells you how to fix it.
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melissa data, data quality, contact data verification, address verification, validate address, address verification software, address verify, address validation software
    
Melissa Data Corp.

The Infrastructure for Information Management: A Brave New World for the CIO

Published By: SAS     Published Date: Sep 13, 2013
If businesses are recognizing the need for a dial-tone approach to establishing “data utility” services for meeting user expectations for data accessibility, availability and quality, it is incumbent upon the information management practitioners to ensure that the organization is properly prepared, from both a policy/process level and a technology level.
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sas, cio, chief information officer, data utility, information management, software development
    
SAS

Are you ready for Analytic's 3.0?

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
    
SAS

Best Practices in Enterprise Data Governance

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
    
SAS

Data Visualization: Charting the Best Course for Your Organization

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
    
SAS

Data Visualization: 7 Considerations for Visualization Deployment

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
    
SAS

Maps, Mechanics & Morals When Launching Your Data Governance Initiative

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
    
SAS

HP 3PAR StoreServ Storage Total Quality Commitment

Published By: HP     Published Date: Jul 22, 2014
HP offers an approach to the modern data center that addresses systemic limitations in storage by offering Tier-1 solutions designed to deliver the highest levels of flexibility, scalability, performance, and quality—including purpose-built, all-flash arrays that are flash-optimized without being flash-limited. This white paper describes how, through the incorporation of total quality management throughout each process and stage of development, HP delivers solutions that exceed customer quality expectations, using HP 3PAR StoreServ Storage as an example.
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3par, storeserv, storage, data, solutions, flash, data management, business technology
    
HP

Five Best Practices for Application-aware Network Performance Management (AANPM) in 2014

Published By: EMA     Published Date: Apr 01, 2014
Application-aware Network Performance Management (AANPM) practices and products provide detailed insights into exactly who is using which resources, what quality of experience is taking place, and where to look when things go wrong. Such information can significantly improve planning, monitoring, and troubleshooting efforts.
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ema, application aware network performace, aanpm, quality of experience, research, it management, data management, consulting
    
EMA

Making the case for data lifecycle management

Published By: IBM     Published Date: May 28, 2014
Read the whitepaper to find out how one client improved business value of their data by implementing InfoSphere Optim processes and technologies.
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ibm, data lifecycle management, infosphere optim, integrating big data, governing big data, integration, best practices, big data
    
IBM

Driving Customer Loyalty through Network & Service Quality

Published By: IBM     Published Date: Jul 27, 2015
Read this whitepaper to look at why network service quality matters to customer loyalty and CSP attitudes to improve it
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customer loyalty, network service quality, communications service providers, service quality metrics, operational performance, customer experience management, cem, cem solution
    
IBM

Customer service: Exploit the value of content to drive service quality and customer satisfaction

Published By: IBM     Published Date: Oct 22, 2014
Great service is delivered one customer at a time and improving interactions across all channels means truly understanding customer wants and needs. Massive amounts of unstructured data exist in your organization and can deliver customer insight that is specific, relevant and actionable. Learn how to harness that data to provide great customer service.
Tags : 
customer service, service quality, customer satisfaction, content management, it management, data management, business intelligence, business management
    
IBM

Big Data, Good Data, Bad Data-the link between information governance and Big Data outcomes

Published By: IBM     Published Date: Feb 24, 2015
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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big data, ibm, big data outcomes, information governance, big data analytics, it management, data management, data center
    
IBM
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