Exploring the Impact of Big Data on Data Governance

Organizations continue to be attracted by the benefits of big data, which are only sometimes realized against gain expectations. Business leaders, including the CEO, CIO, and chief data officers, are deeply concerned about the failure rate of big data projects and the low returns on investment due to their inability to realize the expected benefits. Grounded in the extended technology acceptance model, the purpose of this qualitative multiple-case study was to explore strategies data managers used to implement big data projects successfully. The participants included nine data experts and two IT risk practitioners who implemented big data technology with data governance programs. Data was collected using semi-structured interviews and a review of organizational documents. Inductive thematic analysis was used to analyze the data. Seven themes emerged: business requirements, big data technology adoption, a business-IT unified framework, a holistic implementation framework checklist, a data governance program, and executive management support and impact on GRC. A key recommendation to data managers is to align business requirements with technology selection and adoption while ensuring the best practice framework is available to a designated individual or team. The implications for positive social change include the potential for social justice, promotion of equity, diversity, and inclusion.

Publication Details

Journal
ScholarWorks (Walden University)
Published
2024-09-16
Primary Topic
Big Data and Business Intelligence
Type
article
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article

Exploring the Impact of Big Data on Data Governance

ScholarWorks (Walden University)
Big Data and Business Intelligence
article

Exploring the Impact of Big Data on Data Governance

article en

Abstract

Organizations continue to be attracted by the benefits of big data, which are only sometimes realized against gain expectations. Business leaders, including the CEO, CIO, and chief data officers, are deeply concerned about the failure rate of big data projects and the low returns on investment due to their inability to realize the expected benefits. Grounded in the extended technology acceptance model, the purpose of this qualitative multiple-case study was to explore strategies data managers used to implement big data projects successfully. The participants included nine data experts and two IT risk practitioners who implemented big data technology with data governance programs. Data was collected using semi-structured interviews and a review of organizational documents. Inductive thematic analysis was used to analyze the data. Seven themes emerged: business requirements, big data technology adoption, a business-IT unified framework, a holistic implementation framework checklist, a data governance program, and executive management support and impact on GRC. A key recommendation to data managers is to align business requirements with technology selection and adoption while ensuring the best practice framework is available to a designated individual or team. The implications for positive social change include the potential for social justice, promotion of equity, diversity, and inclusion.

ScholarWorks (Walden University)
Reduced inequalities
Openalex Percentile: Top 38%
Big Data and Business Intelligence
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