Here's how you can analyze data and make data-driven decisions as an airport manager using logical reasoning.

Gather relevant data, analyze it for trends and patterns, use logical reasoning to interpret the findings, and then make informed decisions based on the insights gained. This approach ensures efficient operations and improves the overall airport experience.

We have 2 types of data as I could analyze, 1 being the data populated inside the airport and the other being the data which generated outside the airport but affect the operation. It is better to get all variables are captured in its entirety.

An ideal manager, as the name has it, is the one who manages his / her resources efficiently and proficiently. A major international airport is like a little country being subject to a lot of data processing, inputs and outputs. Compartmentalize your data flow, assign personnel to be responsible of each category, use an updated, reliable, accurate and comprehensive data collection, correlation and comparison system for your airport. Consolidate the final analyses between you and your trusted department leaders via an advanced, real-time, cyber-secure electronic communication system.

Data are the basic foundation behind every decision. Data collection, data processing and finally data analysing are the prime aspects govern the entire business system. The fundamental effort is based on accuracy of collecting quality data and it depends on various methods. Next is to storage and handling of data, which depends on the integrity & reliability of the system. So gathering data is a coordinated effort of all the processes involved.

This is the wrong first step. The first step to analyzing data is to understand what you are trying to find out. If you gather the wrong data because it does not match what you are looking for, you have to start all over. You have to understand what problem you are trying to solve. Asking questions about purpose, audience, where the results will go, etc. Then you gather data related to your identified problem.

This seems so random. You assume correlation has anything to do with the analysis. What if they only want to know how long to wait in line before going on an airplane. Correlation would be a waste of time to calculate. The missing step is to figure out what models fits best for what you are analyzing. This step is when you start calculating to know which variables you want to keep or toss in the model.

Why is this not the first step? If this is the not the first step, you wasted a ton of time collecting and analyzing data for no reason.

Es importante tener claro hacia dando se dirige el aeropuerto, para ello se debe trabajar en las operaciones diarias, realizar una evaluación de los vuelos diarios, cantidad de pasajeros, ciudades más solicitadas, reclamos, calidad de atención al cliente, costos adicionales por pasajero, cumplimiento de horarios, control de equipaje entre otros factores esenciales que nos permitirá realizar las mediciones necesarias para mejorar el rendimiento y el éxito del plan estratégico del aeropuerto.

Setting objective (s) is unquestionably the most important aspect of any endeavor. Seriously, if you don't have a clear cut between why you're doing something and how you intend to get it done and utilized to achieve the end results, then it may not be as discrete as it should've been. First things first!

Stating a clear goal is important as it will help to quickly achieve decision-making and also help in solving particular problems.

This should have been before data collection. This analysis seems to be wasting a lot of time. Sounds like a contractor paid by the hour.

You can only make a decision if you know what you were trying to calculate for in the beginning. Making decisions on wasted time will get wasted analysis. I don't want to see an airplane crash because you decided to move a plane to a spot where another plane is waiting.

Analyzing data and making data-driven decisions as an airport manager involves several steps. First, collect relevant data from various sources, including passenger feedback, operational records, and industry benchmarks. Next, use analytical tools to organize and interpret the data, identifying trends, patterns, and correlations. Then, apply logical reasoning to draw insights from the data, considering factors such as passenger preferences, operational efficiency, and financial implications. Finally, use these insights to inform decision-making processes, prioritizing initiatives that offer the greatest potential for improving airport operations and enhancing the passenger experience.

Excluding step1-step 6 which we need to finish, I think we also need reply a specific system to monitor the airport data since there are much data which related laggage, passagers, flight, weather and other factors. The system can help to monitor big volume data more effectively, we also can use basic database to get intuitive chart and graph to help management to make decision or learn the current situation.