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This repository showcases my data analysis on businees problem of a airlines company using python and sql

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Business Problem

Our company operates a diverse fleet of aircraft ranging from small business jets to medium-sized machines. We have been providing high-quality air transportation services to our clients for several years, and our primary focus is to ensure a safe, comfortable, and convenient journey for our passengers.However, we are currently facing challenges due to several factors such as stricter environmental regulations, higher flight taxes, increased interest rates, rising fuel prices, and a tight labor market resulting in increased labor costs.

Objectives

  1. Increase occupancy rate: By increasing the occupancy rate, we can boost the average profit earned per seat and mitigate the impact of the challenges we're facing.

  2. Improve pricing strategy: We need to develop a pricing strategy that takes into account the changing market conditions and customer preferences to attract and retain customers.

  3. Enhance customer experience: We need to focus on providing a seamless and convenient experience for our customers, from booking to arrival, to differentiate ourselves in a highly competitive industry and increase customer loyalty.

Basic Analysis

The basic analysis of data provides insights into the number of planes with more than 100 seats, how the number of tickets booked and total amount earned changed over time, and the average fare for each aircraft with different fare conditions.

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Upon analysis of the chart, we observe that the number of tickets booked exhibits a gradual increase from June 22nd to July 7th, followed by a relatively stable pattern from July 8th until August, with a noticeable peak in ticket bookings where the highest number of tickets were booked on a single day.

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Therefore, we can see a similar trend in the total revenue earned by the company throughout the analyzed time period. These findings suggest that further exploration of the factors contributing to the peak in ticket bookings may be beneficial for increasing overall revenue and optimizing operational strategies.

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We were able to generate a bar graph to graphically compare the data after we completed the computations for the average costs associated with different fare conditions for each aircraft. The graph Figure 3 shows data for three types of fares: business, economy, and comfort. It is worth mentioning that the comfort class is available on only one aircraft, the 773. The CN1 and CR2 planes, on the other hand, only provide the economyclass

Analyzing occupancy rate

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Airlines can assess how much their total yearly turnover could improve by providing all aircraft a 10% higher occupancy rate to further examine the possible benefits of raising occupancy rates. This research can assist airlines in determining the financial impact of boosting occupancy rates and if it is a realistic strategy.

Conclusion

  1. To summarize, analyzing revenue data such as total revenue per year,average revenue per ticket, and average occupancy per aircraft is critical for airlines seeking to maximize profitability. Airlines can find areas for improvement and modify their pricing and route plans as a result of assessing these indicators.

  2. A greater occupancy rate is one important feature that can enhance profitability since it allows airlines to maximize revenue while minimizing costs associated with vacant seats.

  3. The airlineshould revise the price for each aircraft as the lower price and high price is also the factor that people are not buying tickets from those aircrafts.

  4. They should decide the reasonable price according to the condition and facility of the aircraft and it should not be very cheap or high.

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This repository showcases my data analysis on businees problem of a airlines company using python and sql

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