Summer 2017 has officially begun. As temperatures continue to rise, so does the use of data science across dozens of industries. In fact, IBM predicts the demand for data scientists will increase by 28 percent in just three short years, and our own survey recently revealed that 96 percent of company executives conclude data science is critical to business success. While it’s clear that health care providers, financial institutions and retail organizations are harnessing the growing power of data science, it’s time for more industries to turn up the data science heat. We take a peek below at some of the up and comers.  

Summer 2017 has officially begun. As temperatures continue to rise, so does the use of data science across dozens of industries. In fact, IBM predicts the demand for data scientists will increase by 28 percent in just three short years, and our own survey recently revealed that 96 percent of company executives conclude data science is critical to business success. While it’s clear that health care providers, financial institutions and retail organizations are harnessing the growing power of data science, it’s time for more industries to turn up the data science heat. We take a peek below at some of the up and comers.  
 
Aviation and Aerospace
As data science continues to reach for the sky, it’s only fitting that the aviation industry is also on track to leverage this revolutionary technology. Airlines and passengers generate an abundance of data everyday, but are not currently harnessing the full potential of this information. Through advanced analytics and artificial intelligence driven by data science, fuel consumption, flight routes and air congestion could be optimized to improve the overall flight experience. What’s more, technology fueled by data science could help aviation proactively avoid some of the delays and inefficiencies that burden both staff and passengers—airlines just need to take a chance and fly with it! 

Cybersecurity   
In addition to aviation, cybersecurity has become an increasingly hot topic during the past few years. The global cost of handling cyberattacks is expected to rise from $400 billion in 2015 to $2.1 trillion by 2019, but implementing technology driven by data science can help secure business data and reduce these attacks. By focusing on the abnormalities, using all available data and automating whenever possible, companies will have a better chance at standing up to threatening attacks. Not to mention, artificial intelligence software is already being used to defend cyber infrastructure. 
  
Construction
While improving data security is essential, the construction industry is another space that should take advantage of data science tools to improve business outcomes. As an industry that has long resisted change, some companies are now turning to data science technology to manage large teams, improve efficiency in the building process and reduce project delivery time, ultimately increasing profit margins. By embracing data analytics and these new technologies, the construction industry will also have more room to successfully innovate. 
 
Ecology
From aviation to cybersecurity to construction, it’s clear that product-focused industries are on track to leverage data science. But what about the more natural side of things? One example suggests ecologists can learn more about ocean ecosystems through the use of technology driven by data science. Through coding and the use of other data science tools, these environmental scientists found they could conduct better, more effective oceanic research in significantly less time. Our hope is for other scientists to continue these methods and unearth more pivotal information about our planet. 
 
So there you have it. Four industries who are beginning to harness the power of data science to help transform business processes, drive innovation and ultimately change the world. Who will the next four be? 

 


About the Author

Christine Doig

Sr. Data Scientist, Product Manager

Christine is a Senior Data Scientist at Anaconda. She has over five years’ experience in analytics, operations research and machine learning in a variety of industries, including energy, manufacturing and banking. At Anaconda, she worked …

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