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Informative Article | Data & Knowledge Engineering | India | Volume 12 Issue 8, August 2023
Effective Communication of Data Science Results to Non - Technical Stakeholders
Abstract: Effective communication of data science results to non - technical stakeholders is pivotal for ensuring the comprehension, acceptance, and practical utilization of data - driven insights within organizations. In a data - centric era where businesses heavily rely on data science for decision - making, bridging the gap between data scientists and non - technical decision - makers is crucial. This involves recognizing the diverse audience, tailoring communication, utilizing visualizations, providing contextual narratives, and incorporating real - world examples. Collaboration and communication within data science workflows are essential, as recent research highlights. The evolving perspective challenges the traditional notion of communication as a final step, emphasizing its continuous relevance throughout the data analysis process. The challenges in communicating machine learning and deep learning model results to non - technical stakeholders are multifaceted. The complexity of these models, their interpretability as "black boxes, " the probabilistic nature of predictions, and the need to convey business impact present significant hurdles. Addressing these challenges requires simplifying concepts, providing intuitive visualizations, and emphasizing practical significance. Regular engagement, training, and fostering a data - driven culture within organizations are vital for enhancing understanding and facilitating informed decision - making among non - technical stakeholders.
Keywords: communication, interpretability, data science, visualization, machine learning, deep learning, collaboration, complexity, simplicity, stakeholders
Edition: Volume 12 Issue 8, August 2023,
Pages: 2497 - 2499