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A while back I wrote a blog post suggesting that datacenter infrastructure would move from an on-premise operation to the cloud. It may have seemed counter-intuitive that the infrastructure itself would become available from the cloud, but that’s exactly what’s happening.

We’ve now seen everything from security to system management to storage evolve into as-a-service datacenter offerings, yielding all the benefits of SaaS — rapid innovation, pay-as-you-go, no hardware installation — while at the same time providing rich enterprise functionality.

As the datacenter gets dis-intermediated with the as-a-service paradigm, an interesting opportunity exists for the “big data” layer to move to the cloud. While big data is one of the newer parts of the infrastructure stack — and should have been architected and delivered as a service from the start — an estimated 90+% of Fortune 2000 companies carry out their big data analytics on-premise.  These on-premise deployments are complex, hard to implement, and have already become something of a boat anchor when it comes to attempts to speed up big data analytics. They perfectly define the term “big drag.”

Without question the time has come to move big data to the cloud and deliver this part of the infrastructure stack as a service. Enter Cazena — our latest investment in the big data sector. The Cazena founders were former leaders at Netezza, the big data appliance leader that went public and was acquired by IBM for $1.7 billion. Prat Moghe, founder & CEO of Cazena, previously led strategy, product and marketing at Netezza. Prat has teamed up with Jit Saxena, co-founder of Netezza, and Jim Baum, the CEO of Netezza — all leaders in the big data industry.

This team knows a great deal about big data and agility of deployment. Ten years ago (long before the term big data was being used), the Netezza team came up with a radically simple big data appliance. Appliances reduced the sheer complexity of data warehouse projects — the amount of time and resources it took to deploy and implement big data.

In the next decade, even faster deployment cycles will be required as businesses want data on-demand. Additionally, the consumption pattern has changed as the newer data stack built using Hadoop and Spark has broadened the use of data. A new cloud-based, service-oriented deployment model will be required. The Cazena team is uniquely positioned to make this a reality.

We could not be more thrilled to be backing the team that has the domain expertise and thought leadership to change the face of big data deployments. Big data is changing the way the world processes information, and Cazena is uniquely positioned to accelerate these efforts.

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.