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HOT TOPICS
- The Accelerator Conundrum
- The Startup Velocity Question
- Platform as a Service
- Man and Superman
- Web 3.0 = (4C + P + VS)
- The Future: End of Capitalism
- Capitalism 2.0
jack norris
Thought Leaders in Big Data: Jack Norris, CMO of MapR (Part 5)
Sramana Mitra: Do you have some sort of a program where you invite or encourage entrepreneurs to build on top of the MapR platform? Jack Norris: According to industry analysts like Gartner, the knowledge acquisition for Hadoop is the biggest hurdle for adoption. That’s an area that we’ve really invested heavily in. Just last quarter,
Thought Leaders in Big Data: Jack Norris, CMO of MapR (Part 4)
Sramana Mitra: For the last set of questions, I’d like you to put on an industry thought leader hat. What trends do you see in the market as it pertains to where you are operating? What’s coming out on the horizon? What are you anticipating? What are some open problems as it pertains to those
Thought Leaders in Big Data: Jack Norris, CMO of MapR (Part 3)
Sramana Mitra: If you were to synthesize some of the top use cases, it sounds like you have a mission-critical use case in retail and other kinds of Internet applications. Could you double-click on that and outline some of the mission-critical use cases? Jack Norris: If you look at how organizations are using it, Hadoop
Thought Leaders in Big Data: Jack Norris, CMO of MapR (Part 2)
Sramana Mitra: What does MapR sell? Jack Norris: We’re a software company. We’re providing the distribution so that organizations can leverage this and impact their business. Sramana Mitra: You’re selling software on top of Hadoop? Is this an application on top of Hadoop? Jack Norris: Hadoop is not just a single thing. It’s a series
Thought Leaders in Big Data: Jack Norris, CMO of MapR (Part 1)
MapR has innovated on the Hadoop Open Source building blocks to build a suite of products currently used by hundreds of customers across verticals. This interview double clicks down on some of the use cases, as well as entrepreneurial opportunities in the Big Data field. Sramana Mitra: Let’s start with introducing our audience to MapR.
