Big Data has meant big money for many people in the technology industry, but nowhere is bigger than the Forbe’s Billionaire list. An increasing number of tech industry titans have made it on the list largely through their investments in big data technology and applications.
You already know about Jeff Bezos and Mark Zuckerberg, founders of firms that succeeded largely on the back of their ability to leverage huge volumes of data on individuals and transactions, something that allowed them to create new industries and mint money like a printing press.
But Amazon and Facebook stumbled into big data, they didn’t start with it. The realization that the traffic volume they were generating could be mined for further business interest came later.
In contrast, a select number of firms that have gone big have also started big. Their entire business platforms are premised on the ability to collect, analyze, and leverage data collection. And for these newly minted data science billionaires, that premise has paid off in a big way.
Forrest Li – Sea Limited – $??
Is Singapore’s shadowy Forrest Li a billionaire? It’s hard to say… the founder and CEO of Asia’s most valuable tech startup isn’t talking, and as a privately held company, the numbers are closely held. But Garena, the gaming company that forms the foundation of Sea Limited, has recently been valued at $2.5 billion, and with the big data play Li is making with the AirPay mobile payment system that is expected to take Asia by storm, it’s a good bet that he’s either the latest entry on the list of big data billionaires, or will be soon!
Lee Sang-Hyuk – Yello Mobile – $1 billion
Lee’s Yello Mobile is an upstart Korea-based tech incubator that has more than 80 firms in its portfolio, drawn together as a massive mobile media company with diverse big data plays such as mobile dating, online payments, and even an automated wake-up call service. Lee came to the big data world quite naturally, working at Korean search-engine giant Daum before founding Yello.
John Collison – Stripe – $1 billion
Patrick Collison – Stripe – $1 billion
A pair of twenty-something college drop-outs from Ireland are just about exactly who you would expect to find on a list of tech-industry titans. Their idea for leveraging big data to make online payment processing safe and affordable has skyrocketed Stripe to the number one position in Forbes’ Cloud 100 companies list. Using automation and machine learning-based fraud detection to sniff out sketchy transactions before they can do damage has allowed Stripe to dominate the industry without the heavy manual processes used by traditional processing firms.
Lucy Peng – Alibaba (Ant Financial Services) – $1.1 billion
Alibaba, China’s answer to Amazon in the e-commerce world, has minted a number of billionaires. Lucy Peng is one of the most recent, largely based on the success of her role as the executive chair of Ant Financial… better known as AliPay, the world’s largest mobile and online payment platform. Financial data is some of the most lucrative to manage, but it’s also some of the most sensitive. Peng’s reward for managing the growth and success of AliPay has paid off for her to the tune of more than a billion dollars so far.
Kevin Systrom – Instagram – $1.51 billion
Systrom mostly makes the list because Instagram, the photo-sharing service he created in 2010, was anointed as the chosen one in the social media space when Facebook purchased the company in 2012. Much of Systrom’s share of the bounty was in Facebook stock shares, and the ever-climbing valuation of that titan has done the rest. The world’s largest online photo library created the modern phenomena of hashtags and trending topics, all handled in real time, making Instagram one of the most influential social platforms in the world.
Alexander Karp – Palantir Technologies – $1.6 billion
Palantir is the big data company that you want to not have any of your data: the shadowy tech company operates primarily as the cutting edge private-sector research and analytics service for the United States Intelligence Community, culling trillions of data points from both secret and public data sources to create predictive analysis of individuals who may be up to no good. Spotting trends in data that no human analyst could hope to absorb, Palantir’s successes remain largely veiled behind layers of secrecy… except, of course, for the financial success that co-founder Alexander Karp has enjoyed from his role as CEO.
Vincent Viola – Virtu Financial – $2.2 billion
The son of a truck driver from Brooklyn might not be who you’d expect to see on a list of big data billionaires, but Viola eked out enough money to buy a seat on NYMEX in 1982 and did well enough for himself as a trader for decades to already be pretty rich by 2008. But that was the year big data came calling for him. Among others, Virtu realized that high-speed analysis of stock trade data and algorithmic prediction could effectively beat the market almost every time. Virtu Financial was born and put Viola on the list of billionaire’s created by big data.
Reed Hastings – Netflix – $2.5 billion
Getting your movie recommendations directly from your computer instead of trusted friends or media sources was a new phenomena for most people in 1995, when they were still spinning DVDs for their home entertainment purposes. Netflix, founded by Reed Hastings, was the company that made that happen, and it did so with careful tracking and analysis of your individual viewing habits. Based on what you watched and how you rated it, the company would suggest what you might like to watch next… with a surprising degree of success. That success gave Hastings himself something fun to watch: the ever-rising numbers in his bank account.
Travis Kalanick – Uber – $5.1 billion
Kalanick has stepped back from the daily operation of Uber in the wake of numerous scandals, but he took his money with him, all five billion dollars of it. The disruptive ride-sharing service has up-ended the process of hailing and hiring short-trips, and owes much of its success to the data wonks who build systems and algorithms to analyze and predict demand and dynamically put a price on trips. In the future, Uber expects to use primarily self-driving vehicles, which open up a whole new frontier of data absorption and analysis, from cameras to collision sensors.
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