DATA SCIENCE – ONLY A BUZZ OR A ONCE IN A LIFE-TIME OPPORTUNITY?
Who knew that in future numbers would lead to predictions about weather changes, internet Trends. And, we all would be fantasized by virtual –reality!! Data science is a term given to the art of analyzing raw data in any form, (structured, or unstructured) to discover any hidden patterns. Various applications and tools such as machine learning, coding in various computer languages PHP, C++, SQL, HTML, etc. and sophisticated algorithms are all used in this process.
- DATA SCIENCE – ONLY A BUZZ OR A ONCE IN A LIFE-TIME OPPORTUNITY?
- Why do we need Data Science?
- 1. Airline Route Optimization
- 2. Digital – Marketing/ Targeted- Advertising
- 3. Internet – Surfing
- 4. Gaming
- 5. Image and Speech recognition
- 6. Building Customers
- 7. Banking Frauds Detection
- 8. Detecting medical issues/disorders
- What is the Future?
- The Final Answer
Why do we need Data Science?
In today’s virtual era, there is a growing mass of unstructured data. Studies have revealed that about 80% of data in enterprises lack any structure. To have a close look and unravel any pattern in these large sets of data, we need advanced tools. Hence we need more efficient analytical tools to handle all the information.
Below are some of the important uses of Data science that we didn’t even notice in our every day’s regime.
1. Airline Route Optimization
Applying vital decisions for new airline routes, whether to take a halt in between are some of the important factors for airline decision making.
For this type of analysis key points such as :
- Airliners route distance,
- Availability on seats/freight/mails and,
- Fuel quantity and buffer – check are being considered.
All of these data are processed in profitability models by performing Big Data Analytics.
2. Digital – Marketing/ Targeted- Advertising
If you think how come your online-stores recommend the right things for you, here is a bubble-breaker!
By doing Data Analysis!
Starting from the display signup forms on various websites to the recommended videos or movies, almost all of them are decided by using data science algorithms.
Yes, you read it right!
This is the reason why digital ads have been able to get much higher traffic and CTR as compared to conventional advertisements.
They can be targeted based on a user’s past behavior and past- searches.
This is the reason why you might see ads for Clothing stores while I see an ad for Online courses in the same place at the same time.
3. Internet – Surfing
If I ask you to make a list of the 10 most popular music schools around you, What will you do?
Yes, But what is it?
It is a search engine that lets you search for anything. Have you noticed how they achieve so many results within a fraction of a second?
The answer is by applying Data-Science Algorithms.
Games are now designed using machine learning (ML) algorithms which improve/ upgrade themselves as the player moves up to a higher level. Isn’t that amazing?
On each level, the computer analyzes your previous moves and reforms its shape and movements.
5. Image and Speech recognition
On social media whenever you write posts or upload group pictures, there are immediate- suggestion boxes that ask you to tag your friends.
This is a consequence of recognizing images/faces as humans do.
This is the power of Data Science!
6. Building Customers
Yes, the pop-up messages or assisting virtually 24/7 are all due to Data Science.
Virtual Onboarding in B2B Saas Firms helps to build clients and, more importantly retaining them for a longer time.
They provide you with a roadmap that features a path from your
current position till your destination that assures your work to be completed much before the deadline.
7. Banking Frauds Detection
Banking people had a lot of data that use to get collected during the initial paperwork while sanctioning loans.
So, they decided to bring in data scientists to rescue them from losses.
Nowadays, banks and financial institutions are much more aware of risks and frauds and can predict them much before a disruption in the economy.
Moreover, it also helped them to push their banking products based on customer’s purchasing power, and that gave them a lot of clarity in their work.
8. Detecting medical issues/disorders
Last but not least, we have AI in Healthcare.
According to the PwC, “AI is estimated to contribute an addition of over $15 trillion to the world economy by 2030, the greatest impact of which would be seen in the field of healthcare.”
The exponential growth of AI in the medical sector over a short period can be attributed to two major factors –
- The high availability of medical data and our healthcare history makes the implementation of AI easy, as AI uses algorithms like deep learning and machine learning that require tons of big data.
- The growing complexity of data sets and the introduction of complex algorithms with high dimensions in character variables could
- be unpuzzled by the methods of deep learning and neural networks.
With the increase in sophistication of AI at doing what humans do, but with greater efficiency and lower costs, it has become a large part of the healthcare ecosystem.
Now let’s dive in detail into how this works!
1. Detecting Early
AI plays a major role in the early predictions of medical conditions like heart attacks. AI-based easy-to-wear health trackers like those from Fit-bit, Apple, and Garmin, helps to monitor the health of a person and display warnings when the device detects something unusual.
For instance, the Apple watch collects data like the person’s heart rate, sleep cycle, breathing rate, activity level, blood pressure, and so on and keep a record of all these measures 24×7, which are then processed and analyzed by machine learning and deep learning algorithms to predict the risk of a heart attack, and it reports whenever there is a risk.
According to the American Cancer Society, a high proportion of mammograms (X-Ray pictures of breasts) falsely detect cancer in 1 of 2 healthy women. However, the use of AI enables their review and translation of those mammograms 30 times faster, with 99% accuracy, thereby it reduces the need for unnecessary biopsies (removal of small tissues by surgery).
The increasing use of medical devices along with AI enables doctors to detect and monitor potentially life-threatening diseases better, like heart diseases, cancer in their earlier stages that could prove to be a life-saver for someone.
According to Global Market Insights, medical imaging and diagnosis powered by AI should witness more than 40% growth to surpass USD 2.5 billion by 2024. Another important application of AI in medical diagnosis is the MRI scan, which is now being made much simple than ever before. Otherwise, was very hard to analyze because of the information that it contained and could have taken several hours of research.
AI helps the implementation of cognitive technologies like computer vision, speech recognition, Machine learning to unlock a large amount of medical data, and perform power diagnosis.
For instance, Nuance, which is a production service provider, uses AI to predict the intent of a particular user and helps in developing personalized user experiences, which facilitates better decision making to enhance customer experiences. It also helps in storing, collecting, and re-formatting data that provides more consistent access to data to facilitate further diagnosis or analysis.
3. Giving Medical Assistance
With the increasing need for medical assistance, the development of AI-based virtual nurses has increased. According to a recent survey, virtual assistance nursing corresponds to a maximum near-term value of USD 20 billion by 2027.
4. Diagnosing Disease
AI has helped improve decision making not only in the area of healthcare but has also has improved businesses by studying the customer needs and by evaluating potential business risks.
The use of surgical robots that can minimize errors and any variations to help increase the efficiency of the surgeons is a powerful tool used in – case of AI in decision making. For instance, the Da Vinci, a surgical robot, allows surgeons to perform a range of complex procedures with much greater control than conventional approaches. Da Vinci provides surgeons with an advanced set of instruments and helps in translating the surgeon’s hand movements at the console in real-time as well as provides highly magnified and high-definition views of the surgical area.
What is the Future?
Self Driving Cars
Self-Driving Cars are a craze for the young generation today.
Just think about it, capturing the data about the weather conditions, road conditions,The path, destination, traffic in between, turns, traffic lights and processing it like a human
I think Data science has turned a blessing to us
Just enjoy the power of Virtual reality by sitting back in your car, doing whatever you want. Now, your car knows how to drive and where to take you safely.
Data Science v/s Robotics
The tie-up between these two fields is generating world-changing technologies.
We are not only making human robots to a limited extent but we replacing manpower with robots.
They would replace us all in our workplaces with 100 % precision, accuracy, and ultimate reliability.
The Final Answer
When we put this question that data science is only a buzz or, a once in a lifetime opportunity, the solution is that data will last forever as long as eternity.
And therefore, the use of data to predict events like weather forecasts, routes, frauds, customer behavior would grow as years pass by.
Data Science would evolve as we evolve emerging with new technologies, tools, advanced algorithms, and much more.
Being an ironical term in its own way, tons of Data in our personal computers can be of no use but, for Saas Firms, Online Shops, Social media agencies, the PR people it is pearls and diamonds. They make millions through predicting your searches and recommending the right products at the right time.
Data Science is not only a Storm that would go away! It’s a revolution that has come into existence from now onwards and will continue until the end of man’s kind.
We can see it like Science has no endpoint, and data in any form has no end too. So the intersection between the two would never come to an end.