Data Science is Nowhere Near “Dead” – And This Click-Bait Article Proves It

The modern age’s tell-tale sign of an area of interest gaining steam is the prevalence of click-bait article titles. It’s true. It happened with politics. It happened with cat memes. It happened with BitCoin. And now, it is happening with big data.

On the surface, there is little wrong with click-bait titles. The internet as it currently exists rewards those with high unique visitors, page views and click-thrus. A website needs people on their site to make money — and they need a lot of them, and often, to make a profit. Click-bait headlines, then, are just a sound business practice. After all, if you have good writers and a solid opinion, readers won’t be disappointed when they click.

However, the problem with click-bait headlines is that they only start to appear when topics reach a certain velocity on the web — that is, when more and more people start clicking on and then sharing the non-click-bait articles. With some publications getting increased traffic, and as the Google keyword starts to rise in rankings, publications writing on said topic growing in velocity need to stand out above the crowd. To do so, articles they publish need a solid, unique point of view. And a headline that dismisses discussion, a declarative if you will, is the perfect fodder for the digital space.

Miko Matsumura’s recent piece on Slashdot, “Data Science is Dead,” checks off every point on the click-bait headline list:

– it opposes the common perception in the industry
– it touches on a growing topic of concern (that of big data and its management)
– people’s livelihood is involved — and exaggerated
– and, while there are tidbits of truth throughout, the overall statement simply isn’t valid

Because data science is not dead. In fact, it has hardly even seen its heyday.

Facebook alone collects more than 500 terabytes of data a day. As of 2013, there are 667 exabytes of data flowing over the Internet annually. Big data management platforms like Krux, BlueKai and Palantir are being used in the world’s biggest corporations — at levels spanning executives to the interns.

Obama used big data to get re-elected, despite disparaging numbers that showed he had a subpar approval rating.

Big data is here to stay — and it is growing at a velocity faster than cute cat memes could ever. Ignore big data, and your business will fail. Don’t invest in the data scientists to handle that data and, more importantly, secure it, then you might has well have ignored it to begin with.

But Matsumura’s piece isn’t all wrong.

“We create more data in a single day today than all the data in human history prior to 2013. Unfortunately, unless this is structured data, you will be subjected to the data equivalent of dumpster diving,” wrote Matsumura.

True. Structured and actionable data is a necessary piece to the puzzle when it comes to making big data investments pay off. Because of this, most large corporations do not need (read that again: do not need) a data scientist. All they need is a big data platform that segments the data points they are interested in, connects the dots between what would have previously been undiscoverable points of information about customers, and then makes that information actionable enough to affect the bottom line.

Umbel does that. And you know who we have working on our back-end to make sure that happens?

Data scientists.

There’s the truth. Data science is not dead. Instead, it is growing and becoming an ever-more needed enterprise in today’s economy. Because no CEO is going to become a data miner. Because no journalist is going to sort through millions of data points. Because no one has time for spreadsheets on spreadsheets of numbers and names. This is why data scientists are needed. This is why data science is not dead.

Because we all need platforms that do the dirty work for us. And only data scientists know how to build them.

Want more information on how Umbel’s platform puts the power of a data scientist at your fingertips? Check out a demo — and see what our very own data scientists have been up to.