Building Data Literacy for Sustainable Development: A Framework for Effective Training

Raed A. T. Said (), Kassim S. Mwitondi, Leila Benseddik and Laroussi Chemlali
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Raed A. T. Said: College of Social and Human Sciences, Mohamed Bin Zayed University for Humanities, Abu Dhabi P.O. Box 106621, United Arab Emirates
Kassim S. Mwitondi: Social and Economic Survey Research Institute (SESRI), Qatar University, Doha P.O. Box 2713, Qatar
Leila Benseddik: School of Communication, Arts and Sciences, Canadian University Dubai, Dubai P.O. Box 117781, United Arab Emirates
Laroussi Chemlali: College of Law, Ajman University, Ajman P.O. Box 346, United Arab Emirates

Data, 2025, vol. 10, issue 11, 1-22

Abstract: As the transformative influence of novel technologies sweeps across industries, organisations are called upon to position their staff in the equally dynamic operational environment, which includes embedding technical and legal communication skills in their training programs. For many organisations, internal and external communication of data modelling and related concepts, reporting, and monitoring still pose major challenges. The aim of this research is to develop an effective data training framework for learners with or without mathematical or computational maturity. It also addresses subtle aspects such as the legal and ethical implications of dealing with organisational data. Data was collected from a training course in Python, delivered to government employees in different departments in the United Arab Emirates (UAE). A structured questionnaire was designed to measure the effectiveness of the training program using Python, from the employees’ perspective, based on three key attributes: their personal characteristics, professional characteristics, and technical knowledge. A descriptive analysis of aggregations, deviations, and proportions was used to describe the data attributes gathered for the study. The main findings revealed a huge knowledge gap across disciplines regarding the core skills of big data analytics. In addition, the findings highlighted that previous knowledge about statistical methods of data analysis along with prior programming knowledge made it easier for employees to gain skills in data analytics. While the results of this study showed that their training program was beneficial for the vast majority of participants, responses from the survey indicate that providing a solid knowledge of technical communication, legal and ethical aspects would offer significant insights into the big data analytics field. Based on the findings, we make recommendations for adapting conventional data analytics approaches to align with the complexity or the attainment of the non-orthogonal United Nations Sustainable Development Goals (SDG). Associations of selected responses from the survey with some of the key data attributes indicate that the research highlights vital roles that technology and data-driven skills will play in ensuring a more prosperous and sustainable future for all.

Keywords: association rules; big data; correspondence analysis; legal and ethical awareness; sustainable development goals (SDGs); technical communication; training effectiveness (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2025
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