Analysing Foreigner Arrivals in Malaysia Using
Interactive Dashboards and Big Data Analytics.
Through data-driven visual exploration, this study highlights key arrival patterns and trends
to support deeper understanding of Malaysia’s tourism landscape.
Scroll down to explore further insights and research details below.
Let's dive into the dashboard for more details by click the button below!
View DashboardTotal Foreigner Arrivals
Singapore, Thailand, Indonesia
Data Coverage Period
Visual Analytics
This research explores patterns and trends of foreigner arrivals in Malaysia using interactive dashboards and big data analytics to support data-driven insights.
Key motivations behind analysing foreigner arrivals using big data analytics.
Tourism arrival data in Malaysia is high-volume, complex, and fragmented across multiple sources, making analysis difficult without proper structuring.
Conventional reporting methods are insufficient to reveal meaningful patterns and trends hidden within large-scale tourism datasets.
This research transforms raw tourism data into interactive dashboards that enable structured analysis and informed decision-making.
This research aims to bridge the gap between raw tourism data and meaningful analysis by leveraging big data processing and interactive dashboards to reveal patterns, trends, and insights on foreigner arrivals in Malaysia.
My name is Yahya Naim bin Md Rofiee, a final-year student at Universiti Teknologi MARA (UiTM) Arau, Perlis, currently pursuing a Bachelor’s Degree in Information Technology (Hons.). My Final Year Project research focuses on tourist insight in Malaysia.
Apache Hive is used to clean, transform, and manage large-scale tourism datasets efficiently.
Interactive dashboards allow users to explore trends by year, country, and arrival type.
Visual storytelling helps uncover patterns and insights from complex tourism data.