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Long before passengers sit back, relax, and enjoy their flight, data has played a critical role in getting them to their seats. It has been a cornerstone of the aviation industry since the early days of air travel.

Indeed, from the early 20th century, data was collected through manual processes such as pilots logging information about weather conditions, navigation, and aircraft performance, and design engineers using this information to improve aircraft design and maintenance procedures. The entire network of manufacturers, large and small, pilots, planners, and investors have relied on data to design, build, and operate aircraft in a safe and efficient way.

Fast-forward to 2023, and many processes are fully automated. Data from fuel sensors is used to develop more efficient engines, airlines use data to improve their customer experience, and researchers use data to develop new ways of reducing aircraft emissions.

Data has been powering aviation since the industrys inception, and its only going to increase in importance.

Data is critical for the improvement of airlines and airports operations. On-time performance, for example, is a key performance indicator that aviation leaders pay close attention to, to see how well their organisation is operating and performing against competitors.

This isnt just a performance ranking of airlines and airports. This one metric serves as a valuable tool for self-improvement and a wake-up call to staff within an airline or airport.

Jet fuel prices are typically the most expensive cost item for airlines and they are increasing, at the time of writing. Even in times of inexpensive fuel, airlines are keen to measure fuel consumption and corresponding GHG emissions. Analysing datasets on weather conditions, air traffic, and aircraft performance helps airlines develop more efficient flight plans and potentially save millions in fuel costs.

A final example to draw on is optimising crew scheduling. Data analysis on crew availability, passenger demand, and flight schedules can create more efficient crew schedules that reduce costs and improve on-time performance.

The use of data in aviation is widespread and is used to complete routine tasks as well as the highly advanced.

For example, data is used to personalise passenger experiences, such as tailoring in-flight entertainment, or providing real-time information about their flight and destination.

On a more advanced level, airlines and aircraft manufacturers use data to develop predictive maintenance plans, using sensors to determine when maintenance on an aircraft is needed, and before a problem arises. This has positive impacts on cost and aircraft safety and reliability.

One of the principal uses of data in aviation is to manage the flow of real-time air traffic. Air traffic controllers use information about aircraft positions, altitudes, and headings to route aircraft safely and efficiently, and minimise delays. Industry experts have even suggested using data to manage airport arrivals and departures, scheduling aircraft to optimal wind conditions en route holding back some flights briefly in favour of others with the ultimate goal of an efficient system.

With new technologies such as AI and machine learning emerging at speed, the aviation industry will benefit from new, innovative ways of collecting and analysing data. (And, I might add that Cirium has long been hard at work harnessing these technologies to bring improvements to the industry.)

One area where advanced data collection and analysis will have a major impact is sustainability. Data can be used to improve the fuel efficiency of aircraft and operations and can be used to reduce the environmental impact of aviation, such as noise pollution and CO2 emissions.

Data is also critical in providing executives with the business intelligence they need to make informed decisions. If you have the right systems in place to capture and analyse a wide pool of data from different departments, it gives decision makers a broader view of key internal and external opportunities and challenges.

Big data is critical for effective cost management and operational efficiency in most industries and, in aviation, it has a far reaching, positive impact if it is processed and analysed correctly.

Yes, there are time and cost saving benefits from robust data analytics, but it can also help to improve safety protocols on aircraft, security in airports, and even the carbon footprint of organisations.

With emerging predictive technologies entering many industries, aviation is no exception, and it will be fascinating to see how it is used to improve the processes, functions, and flight plan of the industry.

For more information about Cirium and aviation analytics, visit: http://www.cirium.com

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The digital evolution in aviation: how big data and analytics are ... - Data Science Central

The three-year battle over Californias new math framework has produced calamity and confusion on all fronts. As fighting raged across op-ed pages and X (formerly known asTwitter), the fog of war obscured the inescapable truth: The data revolution is here and our kids are not prepared for it.

From ChatGPT to personal finance, nearly every decision we make in our daily lives is now dominated by data. Eight out of ten of the fastest-growing careers this year involve data science. A decade from now, it will be difficult to find any job that is not data-driven.

We need to equip our students for this new reality by teaching them basic data literacy in K-12. We can all see this, but somehow the politics of the moment have turned this idea into a raging debate.

The new critics of data science instruction seem to have three common objections. Their first claim is that data science programs are somehow watering down math. That is indeed possible, especially if districts treat data-related classes as a form of remediation, but this should not be the case. Data science is a very challenging subject, combining traditional math, statistics, computer programming, and complex datasets. In many ways, it demands more of students, requiring critical thinking, creativity, and a nuanced understanding of the context within which data have been generated.

A second objection is that learning data science in high school is somehow illegitimate because students wont yet have the mathematics skills required of professional data scientists. This is an odd argument. Can high school students never learn anything about physics because they dont understand differential calculus? Can they not find beauty in a Shakespearean sonnet if they dont know the rules of iambic pentameter?

The third claim is that data science coursework will crowd out calculus or some of the other math required for college STEM degrees. This is an important concern, but it assumes that every part of todays curriculum is absolutely critical to that path. Do we really think that is true? Having spent many nights at the kitchen table helping my kids with their homework, I suspect its not. And we (parents) shouldnt ignore the more than 130 college disciplines that now require data and statistics basics as the world changesincluding math and engineering.

We adults can stand around and dither, but young people are not waiting for us to figure this out. In college, students are rushing toward data science courses with astonishing speed. The number of data science undergraduate degree programs has exploded nationallyandin every state. At the University of Wisconsin, Madison, it has quickly becomethe fastest-growing major. Not to be outdone, UC Berkeley recently launchedan entire collegededicated to the subject. Our own institution, the University of Chicago, has hired 25 faculty in data science to keep up with student demand.

Sixteen other states have already officially launched or recommended data science in K-12. Some are creating full-year courses, while others are completely redesigning their math pathways. Leading STEM high schools throughout the country are teaching their students the UC Berkeley Data8 program, one of the best collegiate data science courses in the country. Just recently, a group of AP Statistics teachersorganizeda national data science challenge that attracted more than 5,000 students.

Without leadership from policymakers and educators, this revolution will still happen, but the benefits will go disproportionately to the students who are already advantaged. Wealthy parents and tech employees will teach their kids these skills through summer and after-school programs. Is this what we want? Or do we want to ensure that every child gets at least a basic level of data literacy?

If this all rings true to you, if you believe that a modern K-12 education requires at least some data science instruction, then you can help move us toward action. Ask your local school to incorporate data across school subjects throughout K-12. Ask your teachers to bring modern data tools into the way they teach. And ask your school leaders to offer data-focused math coursesand support their educators with the right resources to do so.

Lets put down our weapons in this math war and start fighting again for our kids futures.

StevenLevitt is an economist, the founder of The Center for Radical Innovation for Social Change (RISC) at UChicago, and the author of Freakonomics.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs ofFortune.

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Freakonomics author: Objections to data science in K-12 education make no sense - Fortune

Dante Haywood has been named director of data science for Cape Fear Collective.

Haywood has been with CFC since January 2021. He was originally drawn to the organization because of its commitment to using data to make unique positive impacts, according to a news release.

"It was not just that CFC had a data mission, it washowthat data would be collected, store, and used. Too often, data is an inaccessible and mysterious field of work, but during my interviews and conversations, CFC was breaking down those barriers to demonstrate that we can make more impact by humanizing the story of data in our everyday lives," Haywood said in a news release.According to the release, Haywood's proudest accomplishment at CFC was engineering the programming scripts that keep theCommunity Data Platformrunning.

"His favorite part of his job is the ability to remove technical barriers, secure funding and collaborate with peopleto achieve more than either party initially thought possible," the release stated.

Looking into the future, Haywood's goal is to use his new role to further strengthen CFC's data science capabilities and social impact measurement, according to the release.

"Data science is a swiftly moving field with new technologies always around the bend," he said in the release. "We have a huge horizon for bringing these technologies to the public. I want to rally our partners in a way that creates the most systemic impact."

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Haywood promoted to director of data science at Cape Fear Collective - Greater Wilmington Business Journal