Overview
For this project, I explored a global dataset of publicly available dengue cases spanning nearly a century, from 1924 to 2023, and covering over 100 countries. My objective was to uncover meaningful insights and tell a compelling story through data visualization. The aim was not just to present statistics but to reveal the trends, patterns.
In addition to the main dataset, I used supplementary data to further enhance the narrative. This additional information provided valuable context, helping to highlight the factors that influence dengue cases, such as climate change.
Alteryx Workflow
For this analysis, I used Alteryx to get the data in shape for meaningful insights. The workflow involved two main datasets: dengue cases and weather patterns. First, I imported Spatial_extract_V_1_2_2.csv, which had global dengue data. I filtered it down to focus only on the years between 2000 and 2010, giving me a decade’s worth of data to work with.
Next, I worked with weather data, which I sourced from Kaggle. This dataset was specifically focused on Bangladesh, containing essential information on temperature and rainfall. I applied the same year filter to align it with the dengue data and added the country code “BGD.” This step was crucial to ensure I could easily link both datasets in Power BI later. Additionally, I reformatted the month field to keep everything consistent.
Power BI DATA MODEL
In my Power BI model, I’m using the Country Table as the central fact table to streamline country-based analysis. The Dengue Table includes information like case counts, dates, and country codes, which link back to the Country Table for consistent geographical insights. Similarly, the Weather Table holds rainfall, temperature, and year data, also connected to the Country Table and the Year Table. Using the Country Table as the hub helps unify the datasets, making it easier to explore how weather patterns may influence dengue outbreaks over time. The Year Table supports time-based filtering, allowing for smooth trend analysis across both datasets.
Power BI Report
