Conceptualization and key dimensions of data literacy in enterprise

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School of Business | Master's thesis
Degree programme
Business analytics
This thesis investigates the concept and key dimensions of data literacy in the business context. Data literacy is crucial in today’s dynamic enterprise landscape. With the rise of digitalization, data has become an essential strategic asset for businesses around the world. Technological advancements have led to data generation in greater volume than ever before, allowing companies to extract valuable insights from sources like social media, credit card transactions, and website analytics. Across industries, the demand for data literate employees is on the rise. Data literacy, however, remains an ambiguous term in academic literature, especially in an enterprise context where the concept has seen little exploration. The aim of this study is thus to build a conceptual framework and fill that gap. Semi-structured interviews were conducted with data leaders at Finnish companies to examine practitioners’ conceptualization of data literacy. The interview data was then analyzed using a grounded theory approach to form the key dimensions for the conceptual framework. The insights from interviews show that understanding business processes and business context are a crucial foundation in being data literate at companies. With the foundation established, understanding data, analysis skills, and communication emerge as key dimensions. The variance in interviewee responses to identical questions are in line with existing literature, demonstrating a lack of consensus definition, and reinforcing the context-specific property attributable to data literacy. In addition, there is no effective method of measuring data literacy capabilities at companies. These findings indicate the need for companies to develop their own frameworks and effective methods of measurement if the goal is to become more data literate.
Thesis advisor
Liu, Yong
data literacy, conceptualization, key dimensions, data, enterprise, data maturity, business
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