HomeAirline CareerImportance of Data Science in the Aviation Industry- 2022

Importance of Data Science in the Aviation Industry- 2022

Data science has already taken over almost every aspect of our lives and now, it’s also making its way into the aviation industry. According to recent studies, data science professionals are going to be in great demand in the aviation industry over the next 10 years and there will be an average of more than 100,000 job openings due to an increase in demand for people with data science skills. It’s about time we take a look at how data science is changing the aviation industry so you can learn what you need to know before applying your data science skills to this industry.

Why is Data so Important to the Aviation industry?

According to Boeing, airlines make about one billion flight changes a year. That’s an average of 20,000 per day. Airlines change routes and revise schedules for a variety of reasons: fuel prices, weather conditions, and air traffic control restrictions are all examples of factors that can affect airlines on a daily basis. In order to keep up with so many last-minute adjustments each day, it’s important for aviation companies to have access to real-time data on demand—which is where big data comes into play.

Big data has changed how business works in our fast-paced global world, giving organizations instant access to real-time information on customer preferences and market trends. Airlines use data science to quickly process huge amounts of raw data from across their networks. This allows them to deliver more reliable services by anticipating travel patterns, Identifying early warning signs, and predicting problems before they happen.

Without data science, airlines wouldn’t be able to manage their businesses as effectively or efficiently as they do today. Using data science technology can help airlines generate new revenue streams by increasing customer satisfaction and loyalty while also lowering costs through smarter decisions across every aspect of their organization.

How Aviation Use Data Science?

Big data has been a buzzword for some time now, and businesses are starting to appreciate its value. Data science is more than just big data, though. It’s an interdisciplinary field that applies scientific methods and systems thinking to extract meaningful information from large sets of data.

To understand how aviation use data for their advantage, let’s look at what goes into creating a new flight plan.

A data scientist uses several sources of data to create a new flight plan: weather models (for local conditions), past weather patterns (to predict future patterns), and airline schedules (to figure out which flights can actually make it on time).

Data Science
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The data scientist takes all these pieces of information and inputs them into models, running tests until they finds one that fits—and then they check work with others before finalizing it. All of these steps help make sure airlines get their planes where they need to be on time—and if there’s any inaccuracy, data experts adjust until they find accuracy.

For safety reasons, planes cannot be manually flown through cloud cover. In fact, according to Skybrary, pilots should fly over known clouds but avoid them when possible; therefore, a pilot needs cloud-cover data before flying on routes that go above or near it.

If a pilot were to get rid of all his paper maps and instead relied solely on online weather reports with no training—or understanding—of what radar reflectivity meant for his specific flight path, he could make mistakes without knowing it until it was too late. But when pilots train with cloud-cover data collected by scientists using complex algorithms after studying radar reports from past flights under similar conditions, they’re much less likely to make these types of mistakes.

Who Uses This Information?

If you’re in aviation, you can use data science to make better predictions about things like fuel usage, weather patterns, and even crash-related information. Using these insights, airlines can reduce costs and be more environmentally conscious. Similarly, passenger safety is improved by being able to identify problematic behaviors via screening processes and customer service analytics.

For example, some airlines are using advanced data analytics to inform staffing and scheduling decisions, resulting in improved customer service. Additionally, training departments use data science methods to optimize flight training curricula and prevent accidents due to human error.

The aviation industry relies on high-tech sensors, GPS systems, and Technologies that capture a broad range of information. To manage all that data effectively, businesses need to hire data scientists who can provide relevant insights for specific needs. Data scientists can also help predict when accidents might occur by analyzing previous information gathered from similar situations. Airlines are already finding ways to leverage data science as they try to stay competitive in a crowded marketplace.

Data Science
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Future of Data Science in Aviation Industry

In an industry where everyone wants to get a clear view of how they can tackle challenges and problems, data science can provide answers that may help solve issues with applications like predictive maintenance, safety, security and more. Imagine when software solutions are combined with massive amounts of data.

By understanding how weather patterns affect flight paths, airlines can alter their scheduling strategies or add more flights to handle demand when adverse conditions occur. However, great information doesn’t always mean that you’ll be able to make actionable decisions from it – so it’s important for airlines to work with partners who have proven expertise in using information effectively. Doing so will likely produce results on par with those seen by American Airlines.

After implementing Microsoft Azure-based cloud services on its route planning system, American Airlines made predictions 4 percent more accurate and saw significant cost savings because it was able to eliminate expensive overnight runs between its key hubs. This resulted in savings estimated at $500 million per year due to a reduced number of schedule adjustments (American Airlines case study). For these reasons and many others we can see why aviation is being influenced by data analytics.

If you are reading this at end, then you realized how aviation experts are using data to turn their high cash-burn business into profit. If data makes you curious and if you are passionate about airplanes then going for a career in data science is best suits for you.

Mohammad Yusuf
Mohammad Yusuf is an aviation professional and a tech blogger based in Mumbai. Passionate about airplanes and a data science learner. To know more about him, Visit his LinkedIn profile.
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