Not your typical accelerator: Data Elite launches a big data lab with the backing of Silicon Valley luminaries
Building a big data software company requires far more than elite engineering and data science skills. It requires the ability to collect and implement market feedback. It requires the ability to build and manage a sales force. It requires the ability to raise money and attract an elite team. For even the best and brightest technical minds, these are often entirely foreign concepts, especially in the case of first time entrepreneurs.
It’s with all of this in mind that several Silicon Valley’s most notable founders and investors have banded together to create Data Elite, a first of its kind big data startup lab cum accelerator.
The list of backers is like a dream dinner party for every aspiring entrepreneur. Founded by former Aster Data (acquired by Treadata for $300 million in 2011) founder Tasso Argyros and tech M&A veteran Stamos Venios, Data Elite is backed by Andreessen Horowitz, The Social+Capital Partnership, Formation8, Ron Conway, and Anand Rajaraman.
Data Elite won’t be structured like your traditional accelerator. The goal is to identify the brightest minds in the big data field, many of which are locked away in academia with no concept of creating a commercial venture, and surround them with the talent, mentorship, and other resources necessary to create successful companies.
According to a company statement released today:
[The program] is intended to fill the gap that exists in the startup ecosystem specifically around big data startups. Despite the plethora of early stage funds & incubators, so far entrepreneurs that are experts in big data have avoided those vehicles; rather, they most often attempt to bootstrap their companies on their own. The reason is that the support and resources that may appeal to founders in spaces like mobile apps or social media are too generic and inadequate to make a difference for a big data startup founder.
Getting accepted into Data Elitewill require at least five years big data experience or a prior data-related exit among the founding team. Initially, the program will target five to 10 companies over a 90 day period, but both these numbers are flexible based on demand, according to Venios. Participating companies will receive a minimum of $150,000 investment in the form of either common stock purchases or convertible notes and access to office space in San Francisco. Data Elite is in a beta phase today, working with select companies in an informal capacity. The official first class of the program will kick off on January 15, 2014 (applications close December 15), with a demo day following three months later.
The key differences between Data Elite and your typical accelerator is the caliber and structure of its mentorship program. At launch the company will have 12 “partners,” each of which will commit to a minimum of five hours per week of office hours where they will be available to participating companies. The list which Data Elite describes as the “A-team of big data,” includes (descriptions provided by Data Elite):
Ken Rudin – Head of Analytics, Facebook
Daniel McCaffrey – General Manager, Platform and Analytics at Zynga
Jeff Magnusson – Manager, Data Science Platform Architecture at Netflix
Anand Rajaraman – Investor and computer science professor at Stanford, teaching Stanford’s graduate data mining class. In the past, Anand was the founder and head of Kosmix which became WalmartLabs in 2011.
Jonathan Goldman – Founder, Level Up Analytics. Jonathan was also the head of the Analytics team at Aster Data, and prior to that a founding member of LinkedIn’s data science team, having done pioneering work such as the first social ‘People You May Know” feature at LinkedIn.
Nicholas Wakefield – Data Scientist and Strategic Advisor. Recently, Nick was the Director of Decision Sciences atLinkedIn.
Eric Colson – Chief Algorithms and Analytics Officer, StitchFix. Prior to this role, Eric was the VP of Data Science Engineering at Netflix.
Ashish Tushoo – Co-Founder & CEO at Qubole. Ashish was the co-founder of the Apache Hive project while he was building and running Facebook’s data service to over 25PB.
Mark Parrish – Investor and advisor at Parrish Advisors, and is the former VP of membership and customer retention at Barnes and Noble.
Steven Mih – VP Business Development at Couchbase
Stephen Reade – Operating Advisor, Global Strategic Business Group at Actian Corporation
Jerome Boulon – Technical Director, Data Services at Riot Games
“There are many funds, incubators, and accelerators out there that entrepreneurs can turn to today for general business advice. However, none of these programs have the industry knowledge to help highly technical founders in the data sciences to commercialize their research or build out their products,” says The Social+Capital Partnership Founder and Managing Partner Chamath Palihapitiy in a statement today.
The question is, are big name investors and advisors enough to overcome the perception of accelerators among the most promising founders? For many, participating in these programs is unseemly and can be viewed as little more than a glorified fundraising roadshow. My bet, however, is that the prospect of unfettered access to the names on the above list will be enough to attract interest from would-be founders. Longer term, the appeal of Data Elite, like that of all accelerators, will come down to the success of its portfolio and the feedback of those founders who have participated previously.
We are at the earliest stages of the big data era, as companies and engineers are just now grasping the full potential of this new field of innovation. It’s not surprising that an accelerator (or several) would pop up to capitalize on this trend. What is impressive, however is the caliber of names surrounding Data Elite.
As companies continue to tackle bigger and bigger problems through data science, there will be a greater need for support structures to usher early stage ventures from idea stage to company stage. Data Elite makes as compelling of a case as any group I’ve encountered for why it will contribute meaningfully to the next generation of big data companies. But like the best startup ideas, it always looks good on paper. Now it’s time to deliver on these lofty promises.
[Image via DARPA]