Harry says, there are nothing but open problems in his space, and highlights some of them! Read on to see what may warrant a new company.
Sramana Mitra: Let’s start by introducing our audience to yourself as well as to Periscope.
Harry Glaser: I’m the Co-Founder and CEO of Periscope Data. Periscope is about five years old. We now have about a thousand customers and we make a platform for data professionals. That’s teams of data analysts, data scientists, and data engineers. We bring those folks together and enable them to really accelerate and turbo charge the kinds of analysis that they do to unify their work flows on one platform and to provide a complete picture of the business to the internal and extrenal business stakeholders.
We’ve raised about $37 million in venture capital. I have about 130 employees that are headquartered in San Francisco. Prior to founding this company with my Co-Founder Tom O’Neill, I was a Product Manager at Google for a couple of years and really saw how probably the most data-driven company in the world operates when making business decisions.
Sramana Mitra: Let’s double-click down on the customer problems that you’re solving. Pick whatever customer that best represents your technology and problem solving. Let’s do a few use cases.
Harry Glaser: One of my favorite customers is Flexport. They’re a freight forwarder. That means that if Apple were a Flexport customer, they would be using Flexport to ship iPhones from factories in China to stores all over the world. Flexport would handle the logistics around which ships to use and which airplanes to use. Flexport is a great company because they are totally disrupting that industry by bringing a much more data-driven and technology approach to the problem.
Patrick is their Director of Data Science and he is our top user and champion there. One story I really love is that, one day, Patrick woke up and discovered that somewhere in the world there was a port strike. All the ships that were carrying goods for Flexport customers were stuck.
What Patrick had to do was come up with a way to re-route all of these goods all around the world in a way that maximizes the customer experience for Flexport customers and also didn’t leave Flexport bankrupt paying for the margins on all of these different shipping lanes.
Patrick had this problem at 9AM and he had to submit a solution to the executive team at Flexport by noon. He and a couple of his data analysts went to work modeling different routes around the world for all of these different goods and came up with a plan for routing all the goods around the world by noon. They were able to save the customer experience and also not lose money. That’s the kind of problem that data analysts and data scientists solve in Periscope Data every day.
Sramana Mitra: What is the Big Data angle of this use case?
Harry Glaser: They are serving many customers. They have all the data on all the different shipping lanes. They have to come up with an analysis in real-time in order to figure out what the right thing to do is. The data volume is one aspect of it. Elasticity is another aspect.
They had to get those compute and memory resources in order to perform that analysis on the fly. Remember the day before, Patrick had no idea that he was going to have to do this analysis. Forget about year-end planning the year before, right? The ability to pull in the necessary resources on the fly is a critical part of being able to respond like this.