6 Applications of Real-Time Data Analysis in the Modern WorldLuke January 25, 2019 0 COMMENTS
Thanks to the ongoing developments in information technology, real-time data analysis has become one of the most powerful tools that businesses of all shapes and sizes can leverage in order to achieve efficiency, growth, stability, and financial success.
For example, by tracking daily trends in customer purchases in real time, a retail company can figure out which among their products are selling the fastest, thus allowing them to focus their production efforts on those particular SKUsso as to maximize their profits.
In another example, a manufacturing enterprise can track the nature and amount of negative feedbacks that their call centers receive about their products in real time.
This lets them zero in on the key sources of the complaints, which then allows them to formulate strategies aimed at improving the quality of their products, in addition to protecting their bottom lines.
These and many other use case scenarios exist every day in the business world, proving that real-time data analysis is not just a mere fad.
What are the other real-world applications of real-time analysis? This short list will help fill you in on some of them.
Real-time data analysis helps save lives
Hospitals deal with voluminous amounts of data, and healthcare workers use them all the time in order to fulfill their roles of caring for the sick, the injured, and the infirm.
Without having quick and easy access to the data they need, the doctors, nurses, and staff employed in these hospitals would find it difficult—if not impossible—to do their duties.
As an example, if a doctor is not able to access a specific patient’s correct and updated medical records quickly, then there’s a chance that they might not be able to provide the care required for patient’s current condition.
The administration of medicine to which a patient is allergic to, for instance, could result in the patient’s condition being exacerbated, and it may even have potentially fatal consequences.
Furthermore, hospitals must also keep analyzing the data they’ve accumulated for insights that could lead to better and more effective treatments across population groups.
This analysis, if done manually, can take up so much time and resources that the insights they provide might prove to be outdated or useless by the time the analysis is completed.
Real-time data analysis has been used to easily address such concerns and more besides. By having specially coded and automated programs that analyze huge libraries of patient records and medical information using artificial; intelligence and machine learning, hospitals can get the insights they need faster and more accurately, allowing them to come up with more effective and less costly treatment courses for their patients.
Meanwhile, real-time data analytics and replication software can be used together to provide doctors and medical staff the information they need, when they need it.
Analytics solutions can automatically bringup all the relevant data about patients being examined, while also providing insights that could lead to a more accurate diagnosis.
Data replication on the other hand ensures that the information being used is updated in real time, and is faithfully replicated for all the databases that store a copy of it.
Other significant areas of medicine where real-time data analysis has made a positive impact include the study of new diseases, the discovery of new treatments, and the detection and prevention of cases of insurance fraud and medical malpractice.
Real-time data analysis helps protect against financial fraud and other crimes
Banks have been known to use real-time data analysis for fraud prevention, and to great effect. How it works is simple: the real-time data analysis application is integrated into the bank’s information database.
Using artificial intelligence and machine learning, such a solution can then detect patterns in customer behaviors in real time, patterns that it can intelligently associate with potential or currently occurring criminal activities.
For example, let’s say someone is attempting to commit credit card fraud with a stolen credit card. The computer application can immediately detect that the purchases being made with the credit card doesn’t seem to match the original owner’s recorded purchasing habits—i.e. they are being made from a wildly different location than usual, or that there are more high-value purchases being made in a short amount of time.
This strange behavior is quickly flagged by the system, allowing the bank’s staff to suspend the charges and investigate further on whether or not there is an instance of fraud. If there is, then further steps can be taken to notify the original owner of the bank account and prevent more purchases from being fraudulently made.
This very same system can also help prevent more serious and costly financial crimes, such as money laundering, embezzlement, and funding of terrorist activities.
By having such a reliable and agile system at work, the bank is able to better protect itself and its customers, while also helping bring these criminals to justice.
Real-time data analysis can help make dangerous workplaces safer
Hazardous jobs that require working in risky or even downright dangerous working environments can be made safer through real-time data analysis. Miners, for example, can cut down the risk of fatal tunnel cave-ins and accidents by having sensors deliver real-time updates and analysis on the integrity of the tunnels they are entering, or the working condition of their equipment.
Data analytics can also help them predict and detect where the richer veins of the material they’re mining are situated, allowing them to find more profitable and safer directions to keep mining.
Other dangerous working environments and occupations where real-time data analysis could prove useful include offshore oil rigs, open sea fishing boats, naval ships, construction sites, biochemical labs, and so on.
These occupations rely heavily on information about their surroundings as well as the condition of their equipment to keep their human workers as safe as possible. By being able to gather important insights in real time, organizations can make occupational hazards more easily manageable, preventing tragic injuries or deaths from occurring.
Real-time data analysis can help creatives protect their rights to their works
YouTube and other content hosting platforms have made it very easy for anyone to self-publish and monetize their own creative content without any upfront costs, besides the equipment, materials, other production expenses that content creators need in the first place.
However, this also makes it very easy for opportunistic individuals to steal creative content from others and monetize it without the former’s authorization.
Thankfully, platforms like YouTube are increasingly making use of real-time data analytics solutions that can help detect and flag instances of intellectual theft, notifying the content owners and allowing them to either have the replicated content taken down, or the money being made from that incident to be funneled to them instead.
Real-time data analysis can help government agencies be more efficient
Many government agencies across the world are notorious for being slow to take care of their constituents’ needs, not only because of bureaucratic red tape but also due to the amount of people and resources that they have to govern and serve in the first place.
More often than not, people that truly need government assistance to go about their daily lives—or even survive—have to endure long lines in government offices in order to plead or demand for aid. And this is after they have already been neglected for far too long.
Real-time data analysis can help government agencies better serve these ailing sections of the population, providing them the assistance they need. By integrating real-time systems into their population databases, governments’ can better keep track of their constituents, especially those that are aging, sick, or impoverished.
The insights that real-time analytics can provide will enable these institutions to predict which individuals or populations will need aid in the future.
This will allow them to eschew the need for lengthy review processes that could delay life-saving treatments for people, for example.
Another use case involves governments being able to identify inefficient public services or degenerating public infrastructure much more efficiently, either through the automatic sifting of reports and complaints, or finding suspicious clues in their data that can lead to the detection of corruption or malfeasance in the government.
Real-time data analysis can help consumers make better and more cost-efficient buying decisions
Thanks to real-time data analysis, those who are looking to spend their daily budgets in a wiser and more cost-effective manner can now more easily do so.
Consumer shopping apps that collect and analyze price lists from multiple vendors and sellers all at once can immediately recommend the most valuable deals nearest to the consumer.
These apps can also collate and analyze feedback from other consumers on whether or not a particular establishment is worth patronizing or if it should be avoided, or if a certain product is known for having serious quality control issues right out of the box.
These and other applications allow paying customers to have a better handle at managing their finances and balancing their expenditures.
Real-time data analysis: changing the world for the better
The real-world applications of real-time data analysis do not end with this list. As time goes on, we shall find that more and more aspects of our world that can be improved in terms of productivity, safety, or efficiency with the right implementation of real-time data analytics.
This only proves how significant this technological breakthrough is and how beneficial it is, not just in improving a business’s bottom line but also in improving the quality of life for common people.