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4.3.1 Dashboard Module

The development of the dashboard module focused on visualizing stroke
mortality data comprises several pivotal stages, commencing with data

cleansing, advancing through the Extract, Transform, Load (ETL) process,

and culminating in the creation of the dashboard within Power BI.

4.3.1.1 Data Cleaning

This section focuses on data cleaning, a crucial step in preparing datasets

for analysis. This part details how stroke mortality-related datasets are
downloaded, reviewed, and refined to ensure data quality for effective

visualization on the dashboard.

i. Global Stroke Mortality Dataset

The datasets, encompassing stroke mortality, total annual deaths,

daily smoking prevalence, population growth, and hypertension
prevalence, were meticulously curated through a thorough cleaning

process to enhance their quality for in-depth analysis. Initially

downloaded in CSV format, each dataset was examined and
organized in Microsoft Excel. During this process, unnecessary

columns were systematically identified and removed, ensuring that
only essential data was retained for analytical purposes. This

careful pruning and organization led to the merging of these

individual datasets into a single, comprehensive dataset, optimized
for analysis.

The initial dataset, named "stroke-death-rate.csv," was acquired

from OurWorldInData.org. It consists of the following columns:

Entity, Code, Year, Deaths: Stroke; Sex: Both; Age: Age-
standardised (Rate). The column 'Deaths - Stroke - Sex: Both - Age:

Age-standardised (Rate)' was changed to 'Total Death' in order to
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