Big data could disrupt almost any conceivable industry this year, but some sectors are more likely than others to see significant shakeups due to this technology.
Here are six of them.
1.
Cybersecurity Hackers continually improve their methods for attacking victims and infiltrating networks.
Fortunately, cybersecurity experts constantly enhance their efforts, too.
The same techniques used to analyze data for business purposes are often useful for detecting cybersecurity attacks and mitigating the damages.
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display(div-gpt-ad-1439400881943-0); }); Frequently, that’s possible due to specialized tools that recognize patterns.
If an analysis of the data indicates something different from the norm, cybersecurity professionals know to take a closer look because something may be amiss.
2.
Health Care The health industry adopted big data later than some other sectors, but analysts think 2019 will be the year health care entities take a more mature approach to data management.
They may realize, for example, that proper use of data gives them a strategic advantage in the marketplace, or that it’s beneficial to use data models to continually update information about providers and network coverage.
Physicians could also turn to big data when assessing treatments for patients.
For example, they might enter the characteristics of a diagnosis into a big data platform and to view statistics that indicate how likely the patient is to respond favorably to the treatment based on the given variables.
3.
Music The music industry has come a long way since Napster sent major record labels into a panic and made executives wonder how to remain profitable.
Now, thanks to platforms like Apple Music and Spotify, people are willing to pay for music again.
Especially in the case of Spotify, there are ample opportunities to use big data to learn about what people want to hear.
As of 2018, 45 percent of Spotify users were on paid plans.
And Spotify knows that relevancy is a key to making the service worthwhile for its users.
That’s why it offers daily personalized playlists, plus gives suggestions on albums or artists to check out based on listening history.
Beyond Spotify, there are exciting possibilities for using big data to plan or promote live concerts, especially when determining which markets have the most fans or how much to charge for concert merchandise.
Music industry leaders know that the ways in which they appealed to fans in the past are no longer relevant.
They focus on making profits as the sector evolves, and big data will help them stay relevant — whether when choosing release schedules for albums or singles, or concluding if the time is right to sign an emerging artist.
Spotify proved there are effective ways to use music industry data.
In 2019, it’s up to other brands in the field to follow suit.
4.
Higher Education The results of a 2018 Gallup poll published in October 2018 revealed decreased confidence in higher education among American adults.
More specifically, only 48 percent said they had “a great deal” or “quite a lot” of confidence in the sector.
Although there are undoubtedly numerous reasons for these sentiments, higher education entities could — and should — use big data to find out more about their strengths and weaknesses.
It’s also possible to utilize big data to identify a student’s strengths and learning progress.
Point Loma Nazarene University helped students become aware of their achievements by building electronic portfolios throughout their academic careers and then giving them opportunities to publicly discuss segments from these portfolios during a senior-year presentation.
Besides urging students to recognize their achievements, the electronic portfolios aided university staff members in keeping tabs on students and giving them feedback about how to improve.
Universities could also use big data to facilitate the recruitment process and determine the likelihood of certain students to accept offers.
Or, they could depend on big data to learn which foods students like best in dining halls or the most appropriate hours for a main campus library to operate during finals week.
5.
Manufacturing This won’t be the first calendar year where the manufacturing sector relies on big data.
But advancements in sensors, interfaces and other technologies collectively urge manufacturing plants to see how big data could take their operations to higher levels.
Davy Brown is the Vice President and Chief Technology Officer at TE Connectivity, a company that manufactures sensors and related products.
While weighing in with his predictions for 2019, Brown noted: “We will continue to see the progression of Industry 4.
0 evolve from a topic of industry forums to full-fledged reality.
Easy-to-install sensors — particularly those that do not always need to be installed inside equipment, such as audio or video capture systems — will become a critically important part of the connected factory of the future.
” Those sensors give users real-time information about production levels, speeds, potential equipment faults and more.
When manufacturing brands understand how and why to use big data platforms, they gain insights that wouldn’t otherwise be possible.
6.
Retail Although many people love to shop, they usually hate waiting in lines.
Fortunately, retailers can depend on a variety of technological solutions based on big data to minimize such delays during 2019.
In a case study at Kroger stores, the supermarket brand used thermal cameras in 2,400 locations along with software to analyze the data the cameras captured.
The brand then reduced wait times to under four and a half minutes.
Another possibility is that retailers deploy sensors or cameras to track the areas of a store customers use most at certain times, and then depend on big data to help managers make scheduling and hiring decisions.
Big data platforms can show the probability of products selling out or remaining in stock, too.
Big Data Technology Could Help Industries Profit These sectors might differ in their priorities and the customers they serve, but it’s beyond doubt that big data and analysis tools could help them get ahead and meet the needs of their customers and other stakeholders.
About the Author Contributed by: Kayla Matthews, a technology writer and blogger covering big data topics for websites like Productivity Bytes, CloudTweaks, SandHill and VMblog.
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