Big Data Meets Big Compute

The promise of big data has ushered in an era of data intelligence. From machine data to human thought streams, we are now collecting more data each day, so much that 90% of the data in the world today has been created in the last two years alone. In fact, every day, we create 2.5 quintillion bytes of data — by some estimates that’s one new Google every four days, and the rate is only increasing. Our desire to use, interact, and learn from this data will become increasingly important and strategic to businesses and society as a whole.

Yet, while we are collecting and storing massive amounts of data, our ability to analyze and make use of the data is stuck in information hell. Even our most modern tools reflect an older, batch-oriented era, that relies on queries and specialized programs to extract information. The results are slow, complex and time consuming processes that struggle to keep up with an ever-increasing corpus of data. Quite often, answers to our queries are long outdated before the system completes the task. While this may sound like a problem of 1970s mainframes and spinning tape, this is exactly how things work in even the most modern Hadoop environments of today.

More data means more insight, better decisions, better cures, better security, better predictions — but requires re-thinking last generation tools, architectures, and processes. The “holy grail” will allow all people or programs to fluidly interact with their data in an easy, real-time, interactive format — similar to a Facebook Search or Google Search engine. Information must become a seamless and fundamental property of all systems, yielding new insights by learning from the knowns and predicting the unknowns.

That’s why we’re investing in Adatao, which is on the leading edge of this transformation by combining big compute and big data under one beautiful document user interface. This combination offers a remarkable system that sifts through massive amounts of data, aggregating and machine-learning, while hiding the complexities and helping all users, for the first time, to deal with big data analytics in a real-time, flexible, interactive way.

For example, a business user in the airline industry can ask (in natural language) Adatao’s system to predict future airline delay ratios by quickly exploring 20 years of arrival/departure data (124 million rows of data) to break down past delays by week, month, and cause. In the same way Google Docs allows teams all over the world collaborate, Adatao allows data scientists and business users to collaborate on massive datasets, see the same views and together produce a visual model in just three seconds.

The Adatao software would not be possible, if not for the incredible team behind the project. I first met Christopher Nguyen, founder and CEO, at a breakfast meeting in Los Altos and was blown away by his humble personality. I knew at that moment, I wanted to find a way to partner with him. Here’s a guy who grew up in Vietnam and came to the US with a desire to make a difference. Since then, Christopher has started several successful companies, was engineering director of Google Apps and earned a PhD from Stanford and a BS from UC Berkeley, and is a recipient of the prestigious “Google Founders Award”.

He’s assembled a crack technical team of engineers and PhDs in parallel systems and machine learning. They all want to change the world and solve the most pressing data and information issues of our generation.

I am honored to be joining the board and look forward to partnering with this incredibly talented team. Adatao’s approach, team, and spirit of innovation will usher in a new generation of real-time, information intelligence that we believe will be the future of big data.

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