It’s no longer news that data has risen like Lazarus from the dead. Yes, data has always been with us but the unprecedented huge availability of data in recent time is what drives us towards it. Like an oracle or agent of divinity, we now look towards data to make meanings of our environments.
The understanding of data now helps us learn more about our behaviors. Prior to now, it was as though things happened randomly, but learning from data, we can now see that there are patterns in things; there are patterns in our world.
A lot has been said about the rise of data but in this article we want to look at some remarkable ones, perhaps the ones that drive attention to data science, making people change their career paths while paving way for those who are at crossroads.
According to the founder of 365datascience.com, Iliya Valchanov, he wrote that for Data Science, “the demand is really high and supply is low, so the salaries are still very high and people are very much willing to get into data science.” (Forbes, 2017). He compared this to the way computer programming was when the computer science field was just evolving, and further stated that data science was driven by technological advancement which was unavailable in the last two decades due to low computational power and primitive programming languages.
Data science, as you may or may not know, is now the darling of many people in the IT world and is even making more people switch to the IT industry. Businesses now call upon this mysterious energy to analyze their businesses and improve upon their marketing and advertisement strategies.
The following are the top 5 remarkable statements that make data science boom in the last decade:
1. Data is the New Oil
In 2006, a UK Mathematician and the co-founder of Dunnhumy, Clive Humby was widely credited as the first to make the statement, “Data is the new oil”. Clive Humby currently serves as the Chief Data Scientist at Starcount Ltd (Medium, 2016). His full statement was this:
“Data is the new oil. It’s valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastics, chemicals, etc to create a valuable entity that drives profitable activity; so must data be broken down, analyzed for it to have value”.
After Clive Humby, many other professionals have reiterated this phrase but often fashioned in different statements.
Abhishek Mehta, the CEO of Tresata, for instance, stated in 2013 that, “Just like oil was a natural resource powering the last industrial revolution, data is going to be the natural resource for this industrial revolution. Data is the core asset, and the core lubricant, for not just the entire economic models built around every single industry vertical but also the socioeconomic models”.
Another is the comment by the founder of Under Armour, Kevin Plank, who said, “Data is the new oil. The companies that will win are using math.”
2. Data is the Sexiest Job of the 21st Century
In October 2012 issue of Harvard Business Review, Thomas H. Davenport, a President’s Distinguished Professor in Management and Information Technology at Babson College and D.J. Patil, a data scientist in residence at Greylock Partners, wrote about the rise of Data Science with the title: “Data Scientist: The Sexiest Job of the 21st Century”.
The writers began the article by analyzing how Jonathan Goldman, a principal scientist at LinkedIn, employed data science to increase the click-through rate of users. This article went viral and the statement quickly became one of the remarkable statements that place Data Science skills on high demand (Havard Business Review, 2012 Issue).
3. Data Science is the No. 1 Best Job in America for 2016
Another remarkable statement that made Data Science boom came from job employment analysis by some career-related companies. In 2016, Career Cast ranked Data Science as the No. 1 profession. It was stated that, “the high demand for data scientists and statisticians comes from a growing emphasis on collecting and evaluating massive quantities of data”.
The career ranking site also ranked Statisticians as the No. 2 profession while Mathematicians comes 6th, showing enormous opportunities for people who are good at crunching figures and data, and making sense of the raw chunks of information.
In addition, in this 2019 Glassdoor ranked Data Science as the No. 1 job within median base salary of $108,000, job openings of 6,510 and 4.3 on a scale of 5.00 job satisfaction.
4. There is a Shortage of Data Scientists in the US
While the previous comments look at the opportunity and career satisfaction that abounds in Data Science, Gartner Predictions, a research firm, predicted in 2012 that there was going to be a shortage of 100,000 data scientists in the US by 2020. This prediction was one of the comments that created the cravings for people looking to break into a new field.
Corroborating Gartner Predictions, the popular consulting firm, Accenture, declared that 90% of its clients have plans to recruit data scientists. However, most of those clients revealed lack of people with the required technical knowhow of data analytics.
Forbes also wrote that since 2012 Data scientist roles have grown by over 650 percent, but currently 35,000 people in the US have data science skills, while hundreds of companies are hiring for those roles.
Later in 2016 Canada Updates asserted that Data Science jobs in the US would have exceeded 490,000 by 2018. As there is an increase in data, the demand for data scientists is likely to exceed supply by nearly 50% or even more globally.
5. Where there is data smoke, there is business fire
While data smoke can easily be likened to the abundance of raw data, business fire can be related to business intelligence and business analytics performance. In his book “Data Driven: Profiting from your most important business asset”, Thomas Redman, the Data Doc and President of Navesink Consulting group, commented: “where there is data smoke, there is business fire”.
This is one of the major remarks that spurred more businesses into utilizing data analytics tools for improving their businesses. E-commerce now uses machine learning algorithms to improve their customers’ experiences; health practitioners use data analytics tools to improve medical care given to patients; crimes can also be detected before they happen; and so on.
Thank you for reading.
If you also know any other remarkable statements about this exciting and thriving field, you can add it in the comment section below.
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