Data science, Statistics, Machine Learning or Analytics; however, you may coin the term but it is one of the fastest growing disciplines in the digital world at the moment. Data Science is a collection of abilities which entertains a gradual increase in computational power. This field has now made its way into various professionalism disciplines including areas like engineering, mathematics, computer science, medical science, statistics and a whole lot more.

In short, data science has left a remarkable impact on just about every professional industry.

Fun Fact: Do You Know That Data Science Was Used to Predict the Deaths of Game of Thrones Characters?

Taylor Larkin created an interesting algorithm in order to predict the death of some of the most prominent characters in the “Game of Thrones” series. He leveraged the book, “Song of Ice and Fire” and information from the Wiki created by different fans. Larkin’s death predictions were a little deviating from the actual show but they were closely related to the book.

Here are the results from the Game of Thrones data analysis done by Larkin’s algorithm:

Daenerys Targaryen–83.77% chance of death
Jaime Lannister–72.91% chance of death
Tyrion Lannister–70.76% chance of death
Bran Stark–66.02% chance of death
Cersei Lannister–60.39% chance of death
Jon Snow–58.99% chance of death
Euron Greyjoy–54.95% chance of death
Sansa Stark–50.28% chance of death
Arya Stark–49.04% chance of death
Gendry–39.87% chance of death

I, for one, definitely adored such a creative use of the amazing data science. Perhaps, you too are interested in learning more about this amazing discipline.

Here are some surprisingly amazing facts about data science which can help you grow in business.

You Spend Most of Your Time in Cleaning & Preparing Data

Here’s one of the first and foremost fact which needs attention. As a data scientist, most of your time will be spent on simply cleaning and processing data for the algorithm so it can predict more accurate results. It usually becomes an agitating task for industry specialists in the field of data science.

Having superior information and a brilliant outlook on various machine learning methods, almost three-fourths of an individual’s time is well-spent in resolving data which ultimately becomes a waste of talent and time.

Repetitive tasks can often lead you to commit errors and when you pay less of an attention, even the most sophistically designed algorithms can backfire and produce unwanted and inaccurate results. If you do not have the will to focus on the big picture, then perhaps data science is not the right career choice for you.

More than 90% of the Tasks do Not Require Deep Learning

Deep learning or Data Science is right now at its infancy. However, truth be told, most real-life problems do not require any advanced analytics capabilities. A problem doesn’t get solved by a number of algorithms, it involves identifying the problem, robust decision making, end-user feedbacks, and brisk actions. What makes the needle move quickly is better than something which is accurate and pure.

In fact, statisticians claim that, at times, even the simplest models such as linear regression, logistic regression, and k-Means clustering can do wonders when it comes to data formulation. You will simply amazed to learn that even complex problems can be simply resolved using these simple models; all it requires is a bit of a labor-intensive approach.

Big Data Can Add up to 6 Million Jobs in the World (Especially U.S.)

According to Gartner research, Big Data can add more than 6 million jobs to the U.S. Economy. Furthermore, Evans Data Corporation confirms that currently, more than 6 million developers are working on the Big Data associated projects worldwide. This industry is expansively massive and shows how inclined users are at the thought of transforming how exactly the world works.

At an estimate, Big Data has incurred a total amount of $57 billion dollars only in gathering the technology used for assembling the big data for various big data backed projects around the world alone in 2017.

More than 30% of Big Data Workloads will Leverage the Cloud

SNS Research indicated last year that almost 30% of all big data workload will move to the cloud. As more and bigger data is becoming scaleable, it is increasing the chance of establishing better consumerization of enterprise software solutions. Developers are more inclined at the idea of creating more user-friendly software for data analytics.

What’s more is that businesses are not anymore interested in creating a room full of supercomputers running with 50 cores and more than half a dozen GPUs running on Linux which only a single guy can understand. As cloud makes its way into the business world, things will not only streamline for processing but it will also take off additional loads such as maintenance cost and initial setup cost off their shoulders.

Everything will become capable of being done off the premise and can be organized into a reporting interface for easy explanation through graphs and statistics during presentations.

Fortune 1000 Companies can Make an Additional $65 million

There is no denying the fact that Data Science is making great changes in the world we live in. It has brought AI into reality, delivered advanced medicine, made governments more efficient and a whole lot more. In simpler terms, better data results in delivering better returns on investments.

A London web design agency researched that personalized website designs are dearly accepted among clients. Websites which are more inclined at understanding the need of customers are more likely to survive in the business for the long run.

When you are playing with data science, the opportunity to experiment recognize no bounds. Just ask yourself this particular question, aren’t all great discoveries a by-product of a couple of geeks working on innovation? That’s what data science is for the future. It is the Innovation of the next generation.