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data quality control

Results 1 - 14 of 14Sort Results By: Published Date | Title | Company Name
Published By: SafetyCulture     Published Date: Aug 14, 2018
Consistency and customer experience are key to quality and profitability in retail. Manual reporting processes can be unwieldy and time-consuming, but bringing together all compliance procedures under one digital platform means fast, consistent and easy-to-access performance data. Using real-time insights into best practice improves the reporting of quality control, stock loss prevention, inspection processes, logistics and more – saving time, increasing efficiency and boosting customer satisfaction. Benefits include better branding through monitoring rollouts with uploaded photos and videos, protection against shrinkage through improved inspection processes and audits, and clearer visibility of issues which means a speedier response.
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SafetyCulture
Published By: Optum     Published Date: Nov 20, 2017
Unlocking value and achieving growth in health care depends on population health management supported by a foundation of accurate, comprehensive and actionable data. This toolkit is designed to help you take immediate action to assess, refine and expand your organization’s ability to deliver improved care quality while controlling costs.
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health care, action, insight, analytics, population health management, provider, delivery, quality, growth, phm, value, optum, partner, leader, executive, toolkit, resource, implement
    
Optum
Published By: Progress     Published Date: Oct 09, 2017
"The customer experience is incredibly important to business success and is often tied to customer engagement, retention rates, revenue, purchase frequency and overall loyalty. Today, the customer journey is incredibly complex, with everything from geographic location to data quality influencing the customer experience. As a result, brands may not be making the most of their customer experiences. However, with a mix of new technology combined with best practices, companies can regain control of the customer journey and create memorable experiences for their customers. "
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Progress
Published By: IBM     Published Date: Oct 18, 2016
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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ibm, idc, big data, data, analytics, information governance, enterprise applications, data center
    
IBM
Published By: IBM     Published Date: Jul 08, 2016
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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ibm, idc, big data, data, analytics, information governance, data center
    
IBM
Published By: IBM     Published Date: Apr 06, 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, analytics, unstructured content, enterprise information, ibm, security, it management
    
IBM
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 center
    
IBM
Published By: STARLIMS     Published Date: Apr 16, 2014
Learn how a Laboratory Information Management System can improve trace evidence management in the crime lab, but will also help analysts with data entry, documentation, and quality control.
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starlims, lims, trace evidence management, crime lab, quality control, it management
    
STARLIMS
Published By: Melissa Data     Published Date: Nov 18, 2008
Learn what a Web Service is and how it works, the advantages of using a Data Quality Web Service, the technology assessment for implementation, and several case studies (Saab and other real world case studies) to demonstrate real life successes.
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melissa data, data quality, contact data verification, address verification, validate address, address verification software, address verify, address validation software, data quality tools, data quality management, data quality objects, data quality api, address quality, data cleanse, data hygiene, data quality, data quality analysis, data quality api, data quality assurance, data quality control
    
Melissa Data
Published By: Melissa Data     Published Date: Nov 18, 2008
Tom Brennan and John Nydam explain the Melissa Data and Stalworth partnership, discuss the business problems caused by bad data, and describe how DQ*Plus provides a complete data quality solution for enterprise applications and commercial databases.
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melissa data, data quality, contact data verification, address verification, validate address, address verification software, address verify, address validation software, data quality tools, data quality management, data quality objects, data quality api, address quality, data cleanse, data hygiene, data quality, data quality analysis, data quality api, data quality assurance, data quality control
    
Melissa Data
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