| Summary: | In this case study, five key processes in modelling a data story of aviation data patterns during COVID-19 have been executed. It started with the collection of secondary data from relevant sources. Data inspection, transformation, and preparation activities, including data cleaning, filtering, and sampling, are all included in this work. Iterative exploratory data analysis (EDA) has been conducted to determine the pattern of each independent attribute, followed by an assessment after the data story is modelled and integrated on a dashboard. The questionnaire has been distributed and the visuals were assessed by giving respondents a few tasks to interpret stories based on their comprehension. The result shows that the data stories have been interpreted in a similar narrative by all the respondents. The overall mean score is 4.71, and this significantly shows that the respondents agree and strongly agree that the visual objects help in communicating patterns and stories. The overall process gives researchers experience and guidelines for future work. Overall, the objectives of the study have been met. Nevertheless, it gives researchers a lot of experience in interpreting data, cleansing and transformation, analysis, modelling the visualisation by selecting suitable charts, and integrating the objects together into a dashboard. © 2023 American Institute of Physics Inc.. All rights reserved.
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