nanaefua-analytics/ghana-adventures-tourism-analytics

Tourism business intelligence analysis of booking trends, revenue, tour package performance and customer behaviour using MySQL, Power BI, Power Query and Excel. # Ghana Adventures Tourism Business Intelligence Analysis This tourism business intelligence project uses booking and customer data to help Ghana Adventures understand demand, improve tour bookings, and make better commercial decisions. **Tools:** MySQL | Power BI | Power Query | Excel | DAX ## Business Context Ghana Adventures is a travel and tour business offering domestic tours, adventure trips, cultural tours, and related travel services. The analysis addresses inconsistent booking demand across periods, low repeat-customer activity, differences in tour package and destination performance, and the need to understand which booking channels contribute most to bookings and revenue. > How can Ghana Adventures use its booking data to understand demand, improve tour bookings and increase repeat customer activity? ## Project Objectives - Analyse booking and revenue trends. - Identify peak and off-peak demand periods. - Evaluate tour package and destination performance. - Analyse repeat-booking behaviour and booking-channel performance. - Identify opportunities to improve marketing, pricing, and customer retention. - Provide evidence-based recommendations for management. ## Dataset The source file contains **233 booking-level records** before the validation and cleaning steps defined in the database creation script. Its fields cover booking date, customer ID, tour package, destination, price, booking type, repeat-customer status, season, and booking channel. ## Data Preparation The MySQL preparation workflow converts supported mixed booking-date formats into valid dates, trims text fields, excludes invalid or placeholder records, converts customer IDs to numeric values, and removes commas from prices before decimal conversion. It also converts blank destinations and booking channels to `NULL` and uses `SELECT DISTINCT` when loading from the staging table to prevent duplicate records. ## SQL Analysis MySQL was used for exploratory and business analysis cover …