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modified, which included assigning suitable data types to

numerical and date fields to enable precise calculations and

temporal studies.

The main objective of this phase was to convert the unprocessed
dataset into a structured and analytically feasible format. In contrast

to traditional cleaning procedures, this step did not include the

elimination of duplicates, the resolution of missing values, or the
validation of data correctness against external sources. The focus

was on developing a well-organized and functional dataset that is
prepared for the subsequent stages of the data analysis process.

After the cleaning process, the dataset transformed into a well-
structured Excel file, distinguished by a coherent layout that

facilitated effective data manipulation and intelligent analysis. This
step was crucial in preparing the data for visualisation tools and

guaranteeing that following analyses would be conducted on a
pristine and well-structured dataset. The structure of the dataset

following the cleaning procedure is shown in Figure 4.29.

Figure 4.29 Stroke Mortality Malaysia dataset after cleaning process.

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