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 is a journey. Typically, it might start out as a cluster that’s used to support data scientist to do some analysis to better understand some aspects of the business. It tends to rapidly move into more of the application space where it takes production data and integrates analytics and processes them together.

There’s over 50 different use cases in a single customer. 18% of our customers have 50 or more use cases running on a single cluster. It can be quite diverse not only across customers, but even within a customer. Some of those relate to top line. How do they roll out new products and services? How do they optimize current revenue activities? Typically, those have recommendation engine at its core in terms of helping to understand and influence customers by looking at what customers purchase.

Second is cost reduction. Just looking at the rate of data growth and the relative flat growth of IT expenditures, there’s a real pressure to look at how they can lower the cost associated with processing and analyzing Big Data. Here, Hadoop has a huge advantage because we’re taking commodity hardware and disks and using that for the storage. The innovations with MapR is making those commodity disk space solutions look and present like high-end enterprise storage with the same snap shot, disaster recovery, and high-availability features that you see in the most expensive enterprise storage components. We’re doing that at hundreds of dollars per terabyte instead of tens of thousands of dollars per terabyte. That alone is a big source for cost reduction. You see organizations putting data into MapR instead of doing long-term stores.

There’s also activities related to reducing operational cost by leveraging sensor information, understanding supply chain issues and maintenance issues, and improving their efficiency. Because Hadoop platform provides a better understanding that the Hadoop platform provides in terms of recognizing patterns and detected anomalies. That’s the second bucket.

The third bucket is under risk mitigation. We’re used by some of the top security companies in the world for intrusion detection, antivirus, and threat detection. It’s really about expanding the data that’s being collected and understood. Instead of looking at just a narrow time frame, you’re looking at longer time frames and being able to detect threats that are done over a long period of time. Also, being able to better understand unknown threats and respond quickly to those. These are companies like Cisco that’s using MapR as part of their networks security solutions. We’re also used by companies that really care about protecting their customer’s information and security. These are banks, healthcare companies, and government agencies.

This segment is part 3 in the series : Thought Leaders in Big Data: Jack Norris, CMO of MapR
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