Lecture: May 1, 2018


Data Revolution

Mike Dauber, Amplify Partners


Mike Dauber is a General Partner of Amplify Partners. He has more than nine years of experience as an early-stage investor and consigliere to founders. Mike spends time across Amplify’s focus areas of cloud, data & analytics, and cyber security. Mike is passionate about working with people who have passion for something. He’s focused on working with people who are the best in their field who strive to make an impact in a market where they have a deep understanding. Prior to joining Amplify as a General Partner, Mike spent more than six years at Battery Ventures, where he most recently lead early-stage enterprise investments on the West Coast. While at Battery, he was on the Boards of Cask, Duetto, Interana, and Platfora (acquired WDAY). Mike also lead Battery’s investment in Vera, which is also in Amplify’s portfolio. He previously invested in Splunk (SPLK) and RelateIQ (acquired CRM). He was named to Forbes’ Midas Brink List in 2014. He is a frequent speaker at conferences and is on the advisory board of both the O’Reilly Strata Conference as well as SXSW. Mike began his career as a hardware engineer at a start-up and later held product, business development, and sales roles at Altera and Xilinx. He earned a BS in Electrical Engineering from the University of Michigan in Ann Arbor and an MBA from the University of Pennsylvania’s Wharton School of Business.


The intelligent application of data and machine intelligence is changing the global economy before our eyes. Big data’s prologue was etched in high-performance silicon and transported over blazingly fast networks. Indeed, today’s entrepreneurs sit on the shoulders of giant breakthroughs in semiconductor, networking, and storage technology. Looking forward, rapidly decreasing prices and powerful new infrastructure make it is possible to ingest, store, and analyze data at phenomenal rates. These infrastructure improvements underlie similarly significant advances in the realm of machine learning, both in its operation at scale as well as the rebirth of deep learning. We believe the iconic companies to define the emerging Data Revolution will take shape along the following lines.

The next decade will usher a broad transition from data as storage cost to data as strategic asset. As such, enterprises will increasingly lean on machine learning to make business sense of their data. Luckily, academia and industry are both bursting at the seam with novel approaches to statistical learning: everything from new tensor methods and advances in NLP to a Cambrian explosion of techniques around deep learning. Whether these advances find their application in the rapid analysis of healthcare image data or serve as the backbone for intelligent bots in the enterprise, their arrival is a leading indicator of more to come.

Lecture Notes