Journal of Data Analysis and Information Processing

Volume 11, Issue 3 (August 2023)

ISSN Print: 2327-7211   ISSN Online: 2327-7203

Google-based Impact Factor: 1.59  Citations  

Considerations for a Planned Democratizing Data Framework for Valid and Trusted Data

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DOI: 10.4236/jdaip.2023.113013    142 Downloads   581 Views  

ABSTRACT

A key requirement of today’s fast changing business outcome and innovation environment is the ability of organizations to adapt dynamically in an effective and efficient manner. Becoming a data-driven decision-making organization plays a crucially important role in addressing such adaptation requirements. The notion of data democratization has emerged as a mechanism with which organizations can address data-driven decision-making process issues and cross-pollinate data in ways that uncover actionable insights. We define data democratization as an attitude focused on curiosity, learning, and experimentation for delivering trusted data for trusted insights to a broad range of authorized stakeholders. In this paper, we propose a general indicator framework for data democratization by highlighting success factors that should not be overlooked in today’s data driven economy. In this practice-based research, these enablers are grouped into six broad building blocks: 1) “ethical guidelines, business context and value”, 2) “data leadership and data culture”, 3) “data literacy and business knowledge”, 4) “data wrangling, trustworthy & standardization”, 5) “sustainable data platform, access, & analytical tool”, 6) “intelligent data governance and privacy”. As an attitude, once it is planned and built, data democratization will need to be maintained. The utility of the approach is demonstrated through a case study for a Cameroon based start-up company that has ongoing data analytics projects. Our findings advance the concepts of data democratization and contribute to data free flow with trust.

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Takang, T. and Amaechi, A. (2023) Considerations for a Planned Democratizing Data Framework for Valid and Trusted Data. Journal of Data Analysis and Information Processing, 11, 240-261. doi: 10.4236/jdaip.2023.113013.

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