Data is the only Vertical

In the past few years we’ve seen software giants like Alphabet’s Google and Amazon.com penetrate more and more industry verticals. Google began as a search bar but now plays in the mobile (Android), media (YouTube), hardware (Motorola), transportation (Waze) and IoT (Nest) spaces as well. Likewise, Amazon.com was originally a site to sell books online, but now sells every product under the sun and operates the world’s largest public cloud through Amazon Web Services (AWS). In addition to the behemoths who have aggressively expanded in the past decade, we’ve witnessed new players barrel in and disrupt additional industries. Airbnb is now valued at $20 Billion – more than every hospitality company in the world except Hilton and Marriott, despite owning no hotels. Ride-sharing company Uber is worth more than legendary automotive brands like Honda, GM and Ford.

As Marc Andreessen stated, software is indeed “eating the world,” and no industry is safe. However, while software is eating the world, it’s also becoming more and more of a commodity. The rise of open source products means that those selling restrictive, proprietary stacks are likely to see themselves disrupted as well. In today’s world, the only truly defensible assets are a company’s relationships with its customer community, its domain expertise and the data it has. Fortunately, there’s a way to leverage software to better serve existing customer communities: data products.

What are data products?

Data products are applications based on machine learning and artificial intelligence (AI) that leverage an organization’s data to deliver unmatched insights. Rather than the traditional rules-based methods (if X then Y) of producing results, data products are smart applications that are able to use AI to recognize patterns. Chances are that you’ve already seen plenty of data products in action. Uber’s smart application changes pricing and driving routes on the fly. LinkedIn dynamically connects job seekers to relevant positions. Airbnb recommends pricing to hosts based on trends in their area and matches them with potential renters. Google Mail does a good job of rooting out spam from your inbox and flagging potentially dangerous emails.

Building data products requires a 360 degree approach including machine learning, visual intelligence, software engineering and domain knowledge. This business transformation unit is essential to building beautiful data products that can nurture communities and customers.

At H2O.ai we have built out a top-quality AI team right here in Mountain View. Our advisors include Stanford University professors Trevor Hastie, Stephen Boyd and Robert Tibshirani. These men are leaders in the field who developed the algorithms that serve as the basis for modern machine learning. Our team also includes Arno Candel, our Chief Architect with over a decade of experience in high performance computing, Statistician and Machine Learning Scientist Erin LeDell, Matt Dowle, the author of R’s data.table package for big joins and multiple Kaggle competition winning Data Scientist Mark Landry.

Finally, we have put together a rock star visual intelligence team including folks like Leland Wilkinson, the founder of Systat and author of the Grammar of Graphics, and Tony Chu, who is well-known for the R2D3 visualization, which received a Vizzie from the National Science Foundation. Our AI platform helps leading enterprises including Capital One, Zurich North America, Progressive Insurance and Nielsen Catalina Solutions develop in-house data products that allow them to take their offerings to the next level.

To find out more about how we can help transform your business through data products, visit us at www.h2o.ai or follow us @h2oai or on YouTube.