How Big Data Analytics Is Used In Everyday Life Around Us
How Big Data Analytics Is Used In Everyday Life Around Us
Ever wondered how Google these days assists you in writing an email or how Amazon shows you variations of precisely what you browsed on the net a few days back or how you always find the right kind of Google ads on your screen which invariably help you buy more?
For those who thought something creepy was going on or thought someone was eves dropping, there’s an easier explanation. Big Data Analytics which along with AI helps you do things better than you could ever have done on your own!
Many among us still think Analytics is still some distance away. What they don’t realize is that it already is upon us, and that industry is using it in some form or the other. Today we give you instances of how industry is using Big Data, and what it’s outcome could be.
The Banking Sector
If there is one sector which needs and stores information by truckloads, it is the banking sector. From opening accounts to money deposits, withdrawals, loans and mortgages, everything can be attributed to the banking sector. And where there is big business and that too which deals with money, there is every possibility of frauds. Defrauding the banking sector can help the offender earn in million. With the right incentive that remains alive for as long as the bank is around, this is one place that is increasingly using big-data to analyze trends and stay two steps ahead of those who think they are smart. Pre-empting a fraud besides, banking in most places is one industry that is seeing competition not only from within but also from bodies which till a while back weren’t banks at all, including telecom companies. To retain customers, banks are increasingly turning to technology to get an edge over competition by making their services affordable, simple and universal. One way to go about is to know their clients’ requirement and pitch things accordingly. Big Data helps in big ways!
The Transportation Sector
App-based services including Ola and Uber are the best examples of how big-data is helping make transport more efficient and feasible for an ever-increasing number of users. In fact, using all the data available on routes, distances, vehicles, types and the likes, Uber has created a service out of thin air without owning a single vehicle. What it owns is the cloud-based software which specializes in reading patterns from available data to place the vehicle nearest to the place of need of the service. The same these days is being used to provide service in the goods transportation industry.
The Education Sector
It we take the case of India in the context of education, there couldn’t be a better example! We are short of primary education whereas in higher education, seats go empty because what they teach is not what people want to learn. Bridging this gap is big-data analysis which may help do the following:
- Reframing learning programs. India is notorious for rote learning which unfortunately does little to prepare a student for real-life situations. This calls for reframing learning programs right from school all the way to PG such that education while providing information also teaches essential life-skills which helps students get gainful employment. Using big-data analysis, government can know what needs to be taught to bring the best out of students and make them capable, independent citizens of the future.
- Bringing about new courses. Our education system prepares specialists very late in their student life, almost towards the end. Sometimes in fact, students learn essential skills on the job. All these result in costs and time over-runs to the industry which remains perennially uncompetitive when compared to other countries where new courses teach special skills quite early. Knowing what to teach, when and in what depth is something which comes across when you have the right information, squarely in the domain of big data and analytics
- Better teaching and evaluation. Continuing with the example of India, with the sheer volumes of students, it’s rather difficult to know how to effectively teach and what to teach within a short span of time. Analyzing big data of adequate vintage is helping both governments and private bodies arrive at ways and means to teach effectively as also evaluate students’ output in an objective manner which infuses quality while taking much less time and efforts.
The Healthcare Sector
The Covid-19 pandemic has shown the efficacy of digitized information that can be analyzed efficiently in order to arrive at conclusions which result in resolute action. It can be taken with a degree of assurance that henceforth, taking lessons from the present pandemic which in itself has generated humongous data of every aspect of a pandemic, Governments and Healthcare providers would be better prepared to face-off and win the battle.
As for the miracles of Big Data already taking place in the field of healthcare, the most notables ones are those of wearable devices. From reading one’s pulse to heart-rate to analyzing sweat samples to even injecting medications at the right time, wearables using big-data have done away with the need for a regular checks, admittance into hospitals with the slightest symptoms and even generalized system of administering medications. Henceforth, using information derived from big-data thru devices, patient care can be individualized down to each individual’s unique bodily needs.
The best example here would be of a big data analytics tool developed at the University of Michigan Rogel Cancer Center. It combines multiple datasets to help turn information into meaningful clinical insights out of an overwhelming amount of data on cancer. Called TransPRECISE, it uses data from 7,714 patient samples across 31 cancer types, combined with 640 cancer cell lines from the MD Anderson Cell Lines Project and drug sensitivity data representing 481 drugs from the Genomics of Drug Sensitivity in Cancer model system. A dynamic digitally-assisted process, it helps analyse new data as it comes in.
“Now that we have tens of thousands of tumors on these patients, we can evaluate what might be the potential therapeutic efficiency of these drugs. The key idea was to develop an analytic tool to do that,” said Baladandayuthapani, who is also director of the Rogel Cancer Center’s cancer data science shared resource.
Things become better in time because there is a past to look at and gain knowledge. The trick is in knowing what to look for and where. For every endeavor in the future where there is an element of repetition, humanity couldn’t have a better friend that Big Data Analytics which with every passing day promises to become better, sharper and more incisive!