Perceptions of data quality dimensions and data roles


Autoria(s): Salomone, Sonia; Hyland, Paul; Murphy, Glen D.
Data(s)

2011

Resumo

Several authors stress the importance of data’s crucial foundation for operational, tactical and strategic decisions (e.g., Redman 1998, Tee et al. 2007). Data provides the basis for decision making as data collection and processing is typically associated with reducing uncertainty in order to make more effective decisions (Daft and Lengel 1986). While the first series of investments of Information Systems/Information Technology (IS/IT) into organizations improved data collection, restricted computational capacity and limited processing power created challenges (Simon 1960). Fifty years on, capacity and processing problems are increasingly less relevant; in fact, the opposite exists. Determining data relevance and usefulness is complicated by increased data capture and storage capacity, as well as continual improvements in information processing capability. As the IT landscape changes, businesses are inundated with ever-increasing volumes of data from both internal and external sources available on both an ad-hoc and real-time basis. More data, however, does not necessarily translate into more effective and efficient organizations, nor does it increase the likelihood of better or timelier decisions. This raises questions about what data managers require to assist their decision making processes.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/48014/

Relação

http://eprints.qut.edu.au/48014/1/anzam_-_Salomore.pdf

Salomone, Sonia, Hyland, Paul, & Murphy, Glen D. (2011) Perceptions of data quality dimensions and data roles. In 25th ANZAM Conference, 2011, Wellington, New Zealand.

Direitos

Copyright 2011 The authors

Please note that the copyright of the conference proceedings belongs to ANZAM, but the copyright of the individual papers belongs to the authors."

Fonte

QUT Business School; School of Management

Palavras-Chave #150302 Business Information Systems #Data Quality Dimensions #Data Roles #Information Technology
Tipo

Conference Paper