Papers

Find a sellection of papers on Data Management written by experts in the discipline.

A Cubic Framework for the Chief Data Officer (CDO): Succeeding in a World of Big Data

Yang W. Lee, Stuart Madnick, Richard Wang, Forea Wang, Hongyun Zhang

In this article, the authors provide a three-dimensional framework that describes the role of the Chief Data Officer.

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A Importância das Métricas para Aprimorar a Qualidade das Informações

Flávio de Almeida Pires e Mario Fernando Cervi

This article discusses the use of metrics as a tool for data quality monitoring and improving (in Portuguese).

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Defining Data Quality Metrics for a Master Data Management Implementation

Mario F. Cervi, Marcelo de Oliveira e Márcio Torelli

This paper presents a method for defining and calculating data quality metrics applied to an MDM implementation.

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Data Quality Contributing to Improve Revenue and Relationship in the Media Industry

Murillo F. Boccia, Flávio de Almeida Pires e Mario F. Cervi

A Brazilian case study presented at the MIT Information Quality Industry Symposium in 2009.

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Customer Data Integration (CDI): Projects in Operational Environments

Flávio de Almeida Pires

In this article, the author presents a framework for implementing a CDI for operating environments.

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Process Embedded Data Integrity

Yang W. Lee, Leo Pipino, Diane M. Strong e Richard Y. Wang

In this article, the authors present a method for data quality continuous improvement.

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Knowing-Why About Data Processes and Data Quality

Yang W. Lee e Diane M. Strong

This article discusses how knowledge of processes by their participants influences the production of data with good quality.

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Managing Data Quality in Dynamic Decision Environments: An Information Product Approach

Richard Wang, Ganesan Shankar e Mostapha Ziad

In this article, the authors present a framework for managing data quality in an e-business environment.

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What Skills Matter in Data Quality?

WooYoung Chung, Craig Fisher e Richard Wang

This paper presents a conceptual framework based on General Systems Theory, in order to facilitate collaborative discourse among data quality researchers and practitioners.

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Data Quality Challenges in Enabling eBusiness Transformation

Arie Segev e Richard Wang

This article discusses data quality challenges in the context of e-Business transformation, presenting the main differences between traditional and e-Business contexts and how they relate to business models, organizations, processes and technologies.

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A Product Perspective on Total Data Quality Management

Richard Wang

In this article, the author proposes that, in order to increase productivity, organizations must manage information in the same way they manage products.

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Beyond Accuracy: What Data Quality Means to Data Consumers

Richard Y. Wang e Diane M. Strong

While companies are improving data quality with practical approaches and appropriate tools, their improvement efforts tend to focus closely on accuracy. The purpose of this article is to address the various aspects of data quality relevant to its consumers.

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