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Pattern on top

I had the privilege of joining our customer Datastax at their Cassandra Summit 2015 last week at Levi’s Stadium in Santa Clara. The Cassandra Summit is an amazing achievement, growing faster in terms of attendance than Dreamforce did in its early days. Datastax tells us the total attendance was 8,000, including in-person and virtual attendees, making it the world’s largest NoSQL conference. The event showcased the growth of the NoSQL and open source movements, and highlighted the way companies are reinventing their data strategies with distributed computing in the face of big data and skyrocketing data volume.

Given Leadspace’s focus on aggregating big data and employing predictive analytics to help companies find prospects that match their profile of an ideal customer, here are a few takeaways I found particularly interesting.

Complex data can provide simple answers

Wrangling large datasets into actionable intelligence doesn’t have to provide complicated answers to be powerful. In fact, simple answers derived from complex data can be just as valuable. British Gas shared a great case study on their Connected Homes initiative, demonstrating how they used regression analysis to identify with reasonable accuracy which electrical appliances in a house were using the most power, based on aggregate power usage data. Just because the answer is simple (“It’s the fridge”) doesn’t mean it’s not valuable.

This kind of analysis can be hugely informative for customers, driving retention and customer satisfaction. In a mobile, connected, app-driven, big data world, more and more consumers will come to expect insights like this. The ability to analyze and present big data in simple and useful terms will become a competitive differentiator for utility companies, telcos, service providers and other enterprise companies.

Although I use the term as liberally as anyone else, one of my favorite quotes from the Cassandra Summit came from Jim Anning of British Gas, who opined that if he heard one more person say “big data,” he might be driven to violence. “I prefer the term ‘not inconsiderable amounts of data,’” Jim said.

Analytics power users don’t like black boxes

You need a great platform to aggregate data, derive actionable information and provide core analytics, yes. But large companies still want to give their internal data scientists the ability to customize the platform to create “bespoke” analytics. This combination of platform and bespoke analytics can be very powerful, and will increasingly be a differentiator among predictive analytics vendors.

Be nice to your data scientists

I was reminded over and over at the summit of another key theme: it is increasingly hard to hire top data scientist talent. That role may not always be clearly defined, but here’s a description I particularly liked: “They know more about statistics than a software engineer, and more about software engineering than a statistician.”

Finding these people presents a unique challenge. We’re lucky at Leadspace to be able to recruit talent both in California and Israel (two of the world’s best tech talent pools), but it’s a timely reminder to me as CEO to keep on pushing innovative approaches to grow our team of analysts as we continue to scale.

Try to work a hammer into your demo

My final takeaway may be a bit more primal than the others. I’ve seen a lot of trade show demos, but I won’t quickly forget the sight of the Datastax team taking hammers to a server — while it was running, during the keynote — and seeing the demo continue to run smoothly even as they were raining blows down upon the machine. A great demo of the power of distributed computing. And hammers.

Editor’s Note: If you’d like to see the Cassandra Summit 2015 Keynote, you can watch it on the Datastax homepage.

Image courtesy of Datastax

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