Big Data

4 Industries in the Midst of Major Disruptions, Thanks to Data

In these cases, disruption is a good thing.
4 Industries in the Midst of Major Disruptions, Thanks to Data
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6 min read
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Research suggests that some 90 percent of the data in the world today was created within the last two years, and our current output is an estimated at 2.5 quintillion bytes per day.

Hiding in those virtually endless strings of ones and zeroes, we suppose, are all kinds of insights, ready to help improve the way we do business and live our lives. All we need is good business intelligence, which is what allows our best and brightest, to convert data into ideas we can actually act on.

Big data is useful in nearly every industry, but over the past year, it's been making a statement and disrupting the standard in four industries in particular. As 2018 approaches, let’s take a look at how analytics can continue to shape these verticals.

Related: How is Big Data Streamlining Business Operations

1. Urban planning.

In just over 30 years, the United Nations predicts that two-thirds of the world's population will live in urban areas, with the greatest expansions happening in developing regions of Asia and Africa. Cities in these areas will be challenged to meet the needs of their citizens, so it's important to understand not just how cities will grow, but how to make them smarter and sustainable as they do.

Using a simulation like the classic SimCity game, where you build a virtual city and watch it grow and evolve, can be helpful in developing new urban areas, but it isn't a perfect solution because of the way it uses generalizations about how the people and organizations within the city behave. These simulations can be useful as general guides, but without nuanced, intelligent accuracy, it can't be as helpful as we need it to be.

For example, MasterCard recently worked in collaboration with Cubic Transportation Systems to develop a new data analysis platform. They combined MasterCard's transaction data with Cubic's transportation data, analytics and visualization platform to develop the Urbanomics Mobility Project to provide insight into the way transit and economic activity are linked together in cities.

2. Education and job training.

Job training is a necessary and potentially costly endeavor for businesses. On-the-job training is a good solution since it allows for being trained while working. But supervisors and more experienced employees may not have the skills for training others. Just because they were good at their work and earned a promotion doesn't make them effective teachers.

Using e-learning in conjunction with training can make the difference. E-learning is a massive industry. In 2015, the market was worth somewhere around $165 billion. At a 5 percent increase every year, we should be hitting a $182 billion market this year and reaching close to $240 billion by 2023. As it continues to grow, we can expect to see data collection and analysis change the face of education as we know it.

While education traditionally relies on test scores to determine how well a student has learned the material, not everyone learns the same way, and exams can easily be cheated, so grades are not necessarily an accurate reflection of someone’s ability to do the work.

Related: Big Data, Big Deal! 5 Ways It's Going to Be Revoluntionized In 2018

This is why today’s e-learning firms are turning to solutions like Cloud Assessments, a virtual workspace designed to observe students to see if they can apply what they’ve learned in the same settings they would see on the job. The platform partnered with Sisense, a business intelligence and data analytics firm, to pull insights from the complex data and metrics so they could more clearly see how students were performing.

The data can easily be shared with and understood by employers so they can learn more about the real skillsets their employees (and potential hires) have. It can help keep training budgets in line -- since the evaluations can be used before paying for any kind of training, such as bonuses and application fees for industry certifications. And students benefit because they have a tangible way to explore their skills, learning what kind of additional training they may need to reach their career goals.

3. Aviation.

The flight industry faces some serious challenges in the form of outdated technology, increasingly complex FAA rules and infrastructure issues. Innovations in the industry have been mediocre at best over the last few decades, but business intelligence is beginning to change all of that.

In 2015, there were 23 work-related fatalities among those working in air transportation, and 6.2 percent of aviation industry employees reported sustaining some kind of injury. The more we can automate processes in aircraft manufacturing, the smaller the window for human error becomes, thus reducing the risk of injury.

Boeing spent more than a year analyzing data and making process improvements to build their Fuselage Automated Upright Build (FAUB) system. It's a network of assembly robots, working in pairs, to install the 60,000 rivets into each fuselage on their 777 aircrafts. This means all the humans have to do is guide the fuselage panels into their correct positions.

In the 1980s, there were only 9,000 detectable faults on a Boeing 767. Now, thanks to the use of intelligent sensors, it's possible to find 45,000 faults on a Boeing 787. Using the Aircraft Health Monitoring Systems (AHMS), data from a single aircraft that detects a fault can be used to scan the entire fleet for the same problem.

Related: In the Next Wave Of Innovation, Big Data Is Your Competitive Advantage

4. Healthcare.

There's certainly no shortage of data in the healthcare industry, as many patient records have now gone digital and conventional x-ray film has been replaced by computerized images. Until recently, the issue has been how to analyze all the data, and what to do with the insights we pull from it.

Right now, we see big data analysis becoming a priority for more in the industry. One report shows 83 percent of pharmaceutical companies plan to make analytics solutions a priority in the coming year. We also see it in advice databases such as Healthline, which provides more consumers with easier access to health information, a key component of improving preventative care.

In the future, using machine learning and big data could mean your doctor works with information delivered via AI, delivering a diagnosis based on your symptoms and individual genetic code. While it will take quite some time for the industry to get to that point, it seems likely to make for more efficient and improved care.

Big data changes the world.

Industry disruption doesn't always have to be a bad thing. Whether we like it or not, data is collected and stored at an alarming rate. It makes sense to put it to work to improve speed and efficiency, doesn't it?

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