Chapter 18Bora Beran: Vast Amounts of Data Are Key for AI and Automation
Bora Beran, director of product management, MongoDB
Source: Photography by Ayla Beran.
Bora holds a PhD from Drexel University and is a reviewer of several scholarly journals in the area of technical computing. Prior to joining MongoDB, he worked at Descartes Labs, Tableau Software, Windows HPC Server, and Microsoft Research, developing tools and infrastructure for visualization, knowledge representation, large-scale computational modeling, and machine learning.
Alexander:You are the director of product management at MongoDB. What is your mission?
Bora: At MongoDB, our goal is to build a database that “just works.” Historically, data management has been a painful process. Too much up-front design, difficult to scale, difficult to respond to changing requirements, too many knobs to manually tune, works in one scenario but not so well in others hence requiring you to maintain multiple copies of your data on different systems … we basically make these problems go away so you can focus on analyzing data and building your applications regardless of scale and where it needs to be: on-premises, in the cloud, or Internet of Things (IoT) devices on the edge.1 We offer the best-in-class developer experience, built-in seamless syncing between distributed edge devices, automatic scaling, automatic healing ...
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