Abstract Businesses have long relied on data analytics in ways to improve operational efficiency. To fully benefit from these advantages, a thorough comprehension of the subject is required. The study analyses taxi travel data in a city using exploratory data analysis and advanced statistical approaches. It aims to identify patterns, trends, and insights in ride-hailing data, which could be useful for urban mobility planning, optimizing taxi service operations, and understanding user behaviour. The project uses Mage for ETL operations, analysing ride-hailing data, and storing it in Google BigQuery for efficient management and scalability, with SQL queries for trip details and passenger counts. The study uses Looker Studio to transform analysed data into interactive dashboards, enabling stakeholders to discover trends and improve services across platforms, integrating ETL techniques, cloud data warehousing, SQL analysis, and visualization tools.
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Kumawat et al. (2024) studied this question.
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