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Report for Airline-Data-Analysis-Using-SQL-Python

Business Probelm

Our company has provided high-quality air transportation services for several years, ensuring a safe and comfortable journey for our passengers. However, we are facing challenges that are impacting our profitability: stricter environmental regulations, higher flight taxes, rising interest rates, increased fuel prices, and a tight labor market driving up labor costs. To address these issues, we plan to analyze our database to identify opportunities to increase the occupancy rate, thereby improving the average profit per seat.

Key Obstacles

  1. Stricter environmental regulations: The airlines industry is facing increasing pressure to reduce its carbon footprint, leading to the implementation of more stringent environmental laws. These regulations not only raise operating costs but also restrict the potential for expansion.

  2. Higher flight taxes: Governments worldwide are imposing heavier taxes on aircraft as a means to address environmental concerns and generate revenue. This increase in flight taxes has raised the overall cost of flying, subsequently reducing demand.

  3. Tight labor market resulting in increased labor costs: The aviation sector is experiencing a scarcity of skilled workers, leading to higher labor costs and an increase in turnover rates.

Analysis

The basic analysis of the data provides insights into the number of planes with more than 100 seats, how the number of tickets booked and the total amount changed over time, and the average fare of each aircraft with different fare conditions. These findings will be useful in devloping strategies to increase the occupancy rates and optimize pricing for each aircraft. Table 1 shows the aircraft with more than 100 seats with actual count of seats.

Table 1:
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In order to gain a deeper understanding of the trend of ticket bookings and revenue earned through those bookings, we have utilized a line chart visualisation. Upon analysis of the chart, we observed that the number of tickets booked exhibits a gradual increase from (June 22nd - 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 (Figure 1). It is important to note that the revenue earned by the comapny from these bookings is closely tied to the number of tickets booked (Figure 2:). Therefore, we can see a similar trend in the total revenue earned by the company througout the analysed 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

Figure 1:
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Figure 2:
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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 was worth mentioning that the comfort class is available on only one aircraft, the 773, whereas the CN1 and CR2 planes, on the other hand, only provide the economy fares. When different pricing circumstances within each aircraft are compared, the charges for business class are consistently greater than those for economy class. This trend may be seen across all planes regardless of fare conditions.

Figure 3:
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Analysing Occupancy Rate

Airlines must thoroughly analyze their revenue streams in order to maximize profitability. The overall income per year and average revenue per ticket for each aircraft are important metrics to consider. Airlines may use this information to determine which aircraft types and itineraries generate the most income and alter their operations appropriately. This research can also assist in identifying potential for pricing optimization and allocating resources to more profitable routes. The below (Table 2:) shows the total revenue, total tickets and average revenue made per ticket for each aircraft. The aircraft with the highest total revenue is SU9 and from the figure 3 it can be seen that the price of the business class and economy class is the lowest in this aircraft. This can be the reason that most of the people bought this aircraft ticket as its cost is less compared to others. The aircraft with least total revenue is CN1, and the possible reason behind this is it only offers economy class with very least price and it might be because of its poor conditions or less facilities.

Table 2:

image

The average occupancy per aircraft is another critical number to consider. Airlines may measure how successfully they fill their seats and discover chances to boost occupancy rates by using this metric. Higher occupancy rates can help airlines increase revenue and profitability while lowering operational expenses associated with vacant seats. Pricing strategy, airline schedules, and customer satisfaction are all factors that might influence occupancy rates. The below (Table 3:) shows the average booked seats from the total number of seats for each aircraft. The occupancy rate is calculated by dividing the booked seats by the total number of seats. Higher occupancy rate means the aircraft seats are more booked and only few seats are left unbooked.

Table 3:

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Airlines can show much their total yearly turnover and it could be provided through a 10% higher occupancy rate to further enhance the effectiveness of raising occupancy rates. This research mainly intends on determining the financial impact of boosting occupancy rates and if it is a realistic strategy. Airlines may enhance occupancy rates by revenue while delivering greater value and service to consumers below competitive pricing and other operational considerations. The below figure shows how the total revenue increased after increasing the occupancy rate by 10% and it gives the result that it will increased gradually so airlines should be more focused on the pricing strategy.

Table 4:

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Conclusion

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

Furthermore, boosting occupancy rates should not come at the price of consumer happiness or safety. Airlines must strike a balance between the necessity for profit and the significance of delivering high-quality service and upholding safety regulations. Airlines may achieve long-term success in a highly competitive business by adopting a data-driven strategy to revenue analysis and optimisation.

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SQL and Python-powered analysis of airline data to uncover insights on occupancy rates, revenue performance, and pricing strategies for improved profitability.

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