Data science the profession of the future?

If you are into computer science profession, you must be hearing this buzz words a lot these days.

“Data science is the profession of the future”
“Data science is a lucrative profession to be in”

So why being data scientist is a great deal? What’s the proof that it is going to ensure my future? Well, the best way to proof this is through the Data Science itself. Data scientists talk with stats, with facts, with numbers, so nobody can point to them and that’s what we are going to do here today.

Reports suggests

By 2005 since the time of inception, humans had produced 130 ExaBytes of data. Well, my MS Office has already started showing me red line under this fancy word “ExaByte” and it must since I also didn’t know how much data an Exabyte can hold until Kirill Eremenko showed me in his Udemy course.

He started with a letter, “A” which is 1 byte. A thousand page book containing 1000 characters on each page makes it 1000*1000 = 1000k byte.

What about human genome which can fit in less than 1 GB? Yes, a whole human can be fit in 1 GB.

1000GBs is 1 TeraByte by the way, and 1000 TeraBytes is a PetaByte. And you must have already guessed it 1000 PetaBytes makes 1 ExaByte, and that was 130 ExaBytes of data which had been produced by the year 2005.

Now pardon me to write this line in small case but by the year 2010, we had produced 1200 ExaBytes of data. And by the time I am writing this that is the year 2015, it is said to be around 7900 ExaBytes and expecting to reach 40,900ExaBytes of data produced by the year 2020.

Now interesting thing is, we can’t hold all of it. We can’t hold it anyway since our machines are not that good and what the profession believes is that we don’t have to hold all of it, even a smaller portion of this data would do our job.

Data science enables to read patterns about anything through the relevant data. Looking at your personal data, a scientist might be able to guess your next word, and that’s not even a lie that’s how data science works on research and probabilities.

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Originally published at on December 4, 2015.