Does Big Data have a place in the field of Aerodynamics?

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Data Science and Big Data are increasingly relevant in aerodynamics and the aerospace industry, leveraging modern instrumentation to capture vast amounts of data for analysis. The term "Big Data" has emerged as a marketing buzzword, often used to justify investments in advanced computing technologies. While data analysis is valuable, it is essential to understand the context and potential noise in the data collection process. Gathering data without a clear understanding of what it should represent can lead to misguided conclusions. Effective data analysis should resemble a controlled experiment, requiring thorough background knowledge and communication with stakeholders to ensure meaningful insights. Those interested in transitioning into Big Data from aerospace engineering should consider how to integrate their scientific background with programming skills, even if their current work does not involve Big Data practices.
jonathan1987
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I have been wondering lately, is the field of Data Science/Big Data used in the field of Aerodynamics? I know that Data Science has found great uses in areas like bioinformatics, finance, social media and sports. I am asking because the two fields I have grown interest in them. If you work in the aerospace industry and use big data, what is it like and how is the work environment? Any help would be appreciated thanks.
 
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"Big Data" is used everywhere because it has become a buzzword that at this point is just data analysis rebranded by C-Level managers.

Data analysis is useful everywhere.
 
With modern instrumentation, you can capture orders of magnitude more data that one could have before. This leads to databases that would appear "monstrous" by yesterday's standards. So to justify the purchase of some really cool, whacky-fast computer equipment; marketeers gave the information a tag so that corporate level people who have no idea what this is all about can understand the purchase. They called it "Big Data."

I deal with this working in a different arena, but one that is just as capable of generating ridiculously huge steaming heaps of nearly useless-- I mean "VERY VALUABLE"-- data.

Every generation has a few wide eyed dreamers with lots more vision than common sense. They tend to infest the hallways looking for people to talk to. They'll occasionally have lunch with sales and marketeering folk. Those clever marketeers then beginning to spew nonsense because they can't tell the difference between a wide eyed nit wit and someone who actually knows what will sell.

And that's how terms like "Big Data" get born.

Let me warn you up front about gathering data from the field. There are artifacts of the measurement process. These artifacts are usually caused by having many other priorities in the operational details. The people who gather data from many disparate sources on one very narrow parameter are actually gathering a great deal of noise. They're looking for patterns to reverse engineer someone's behavior when sitting down and talking to people is often more illuminating.

Is there still value in data analysis? YES, but before you go there, you REALLY need to spend time talking to the people and getting background data on what you're gathering and where. You have to have a very good idea of what you think the data should look like before you gather it.

I can not emphasize that last statement enough. If I had a dollar for every misguided study of "Big Data" that I've had to deal with, I'd be a wealthy man. Big Data analysis should be a lot like conducting a controlled experiment. If it isn't, you're just goofing around.
 
Hi,
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