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Meeting the Challenges of Data Quality Management

Meeting the Challenges of Data Quality Management outlines the foundational concepts of data quality management and its;

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Journey to Data Quality

, based on rigorous research and informed by real-world examples, describes the challenges of data management and provides the principles;

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Journey to Data Quality

rigorous research and informed by real-world examples, describes the challenges of data management and provides the principles, strategies, tools;

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Roundtable on Data Science Postsecondary Education: A Compilation of Meeting Highlights

Approaches for Data Science Education at the Ph.D. Level 9 Meeting #8: Challenges and Opportunities to Better Engage Women and Minorities in Data;

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Competing with High Quality Data

organizations needs. As a data quality professional, you must ask yourself whether you are meeting current industry standards, such as the pervasive;

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Big Scientific Data Management

This book constitutes the refereed proceedings of the First International Conference on Big Scientific Data Management, BigSDM 2018, held;

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Managing Data Quality

management in practical terms, focusing on three key areas - the nature of data in enterprises, the purpose and scope of data quality management, and;

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Multi-Domain Master Data Management

through the challenges of a multi-domain master data management (MDM) implementation. Authors Mark Allen and Dalton Cervo bring their expertise to;

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DAMA-DMBOK

The Data Management Body of Knowledge (DAMA-DMBOK2) presents a comprehensive view of the challenges, complexities, and value of effective;

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Identification of Internal Customer Requirements and Meeting Those Requirements Through Business Process Improvement Within a Quality Management System at an Australian Electrical Manufacturer

Identification of Internal Customer Requirements and Meeting Those Requirements Through Business Process Improvement Within a Quality;

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Administrative Capacity in the New EU Member States

of public management systems. The new member states face considerable challenges--improving fiscal management, building absorption capacity;

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Management of Data Quality in Enterprise Resource Planning Systems

existing ERP system implementation and business management models. The usage of general purpose data quality "add-ons" such as address edit;

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Uncertainty Modelling and Quality Control for Spatial Data

Data quality in multi-dimensional integration Research challenges on data quality in the integration and analysis of data from multiple;

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Uncertainty Modelling and Quality Control for Spatial Data

Data quality in multi-dimensional integration Research challenges on data quality in the integration and analysis of data from multiple;

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Information Quality Management

information. The growth of data warehouses and communication and information technologies has increased the need for high information quality;

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Mississippi River Water Quality and Interstate Collaboration

November 18-19, 2013. The workshop examined a wide array of challenges and progress in water quality monitoring and evaluation in states along the;

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Management of Data Center Networks

network management challenges that present within intra- and inter-data center networks, including reliability, routing, and security. The book;

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Water Quality Management

data is necessary and having enough data without proper interpretation is not helpful for water quality management decisions. Hence;

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Big Data Management

successfully implemented big data platforms. The topics discussed cover the entire data management life cycle, data quality, data stewardship;

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Healthcare Data Analytics and Management

, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding;

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Knowledge Management in the Development of Data-Intensive Systems

-Intensive Systems addresses new challenges arising from knowledge management in the development of data-intensive software systems. These challenges;

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Fundamentals of Data Warehouses

results of the European DWQ project, it offers a conceptual framework by which the architecture and quality of data warehousing efforts can be;

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Methodological Issues of Longitudinal Surveys

improve and to maintain the highest level of data quality, data management tools for large-scale longitudinal surveys, the dissemination;

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We'Ve Got to Start Meeting Like This

meetings and get better results. It explains how meeting management practices and attitudes have changed, and the most appropriate and effective;

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Artificial Intelligence and Machine Learning for Digital Pathology: State-Of-The-Art and Future Challenges

, well-annotated samples and data. The main challenges are finding biobanks containing ''fit-for-purpose'' samples, providing quality related;

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Automating Quality Systems

is compatible with concepts of Total Quality Management. The integration of quality operations and data with other manufacturing sub-systems;

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Data Architecture

the challenges organizations face in structuring and managing their data. Using a holistic approach to the field of data architecture, the;

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