From $100k to $1M: Decisions Powered by Data

Are There Still Startup Opportunities in Big Data?

5 Thought Leaders in Big Data

Today the significant opportunities for entrepreneurship currently exist in the application layer of the Big Data industry. The platforms and plumbing are already in place.

The most exciting opportunities are going to be available to those entrepreneurs who harness the power of big data, but couple it with intense domain knowledge in specific areas of business. These five thought leaders are good examples of how to do that.

• Mike Driscoll, CEO of Metamarkets – Marketing technologies are hot these days, and Metamarkets is doing some cutting edge analytics in the media buying area. Very interesting.
• Krishna Venkatraman, Senior Vice President of Analytics at OnDeck – The online lending industry is going through rapid changes with the advent of big data and machine learning in processing loan applications. Krishna discusses OnDeck’s workings.

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Thought Leaders in Big Data: Mike Driscoll, CEO of Metamarkets (Part 4)

Mike Driscoll: CMO’s are now waking up to the fact that when they spend their marketing dollars, they’re not just getting performance, but they also have a right to get the data about what performed, how, where, and when. As that realization is starting to percolate in this domain, CMO’s are recognizing how important data is and that they need to have the tools to bring disparate data from various channels together to make intelligent choices. I think we’re in the early innings of that process. It’s an enormously complex challenge.

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Thought Leaders in Big Data: Mike Driscoll, CEO of Metamarkets (Part 3)

Sramana Mitra: Interesting. With the real-time nature of your work, how do your customers take into account the signals that you’re providing and quickly act on them? What are the interfaces and APIs that you plug into to enable them to act on that?

Mike Driscoll: It is all about the action that people can take on behalf of insights they may get. Until yesterday when we made the announcement of our inaugural API, Metamarkets had historically been focused on interactive dashboards. The decisions that our clients are making are often human-mediated, much like traders on Wall Street looking at tickers and reacting in real-time. Having real-time UIs is just one step. They want to plug the data and the insights that they are gaining into their own workflows. >>>

Thought Leaders in Big Data: Mike Driscoll, CEO of Metamarkets (Part 2)

Mike Driscoll: Our key innovation early on was that we developed an in-memory database. It allowed us to scale out our offering and provide to a customer like AOL a way to point-and-click their way through a massive scale of data without having to write code and without having to use the traditional and slower Big Data and intelligence tools out there. Ultimately, the use cases that we’re serving with clients like AOL comes down to visibility. The value proposition for clients is that when they’ve got tremendous amounts of data, just getting operational awareness or understanding which publishers may have been knocked offline, understanding which advertisers have reduced or cut their spend because of software issues, and being able to do root cause analysis is what Metamarkets has facilitated. >>>

Thought Leaders in Big Data: Mike Driscoll, CEO of Metamarkets (Part 1)

Marketing technologies are hot these days, and Metamarkets is doing some cutting edge analytics in the media buying area. Very interesting.

Sramana Mitra: Let’s start by introducing our audience to Metamarkets and yourself.

Mike Driscoll: I’m the CEO and Founder of Metamarkets. We are a SaaS software platform that provides interactive analytics to the roles of leading programmatic media buying companies like AOL and Twitter. These companies use us to provide interactive analytics both internally and to buyers and sellers on their digital advertising markets. >>>

Thought Leaders in Big Data: Krishna Venkatraman, Senior Vice President of Analytics at OnDeck (Part 3)

Sramana Mitra: The next question I’m going to ask you is that you said you have different heuristics and different nuances from one segment to another. Could you give us some examples of what you check for one industry and how you structure another?

Krishna Venkatraman: If you’re looking at a landscape that has a seasonal pattern, you may see a very strong projection of revenue because it’s probably its peak season. The obligation that that landscaper will take on actually will extend past that summer. For that particular industry, you have to accommodate the fact that seasonality will play a role. Other businesses have a lot more stable profile. You have to customize those aspects for each business. You could use manual underwriting to get at this but the challenge with manual underwriting is there’s no guarantee of consistency. >>>