Dale Kim View Bio
Apache Hadoop is emerging as a distributed platform for handling large and fast incoming streams of data. Predictive maintenance, supply chain optimization, and internet-of-things analysis are examples where Hadoop provides the scalable storage, processing, and analytics platform to gain meaningful insights from granular data that is typically only valuable from a large-scale, aggregate view. One architecture useful for capturing and analyzing streaming data is the Lambda Architecture, representing a model of how to analyze real-time and historical data together. This presentation will cover the practice of capturing canonical data “as it lands” as a baseline for accommodating future analytics requirements.
Dale is the Sr. Director of Industry Solutions at MapR. His background includes a variety of technical and management roles at information technology companies. While his experience includes work with relational databases, much of his career pertains to non-relational data in the areas of search, content management, and NoSQL, and includes senior roles in technical marketing, sales engineering, and support engineering. Dale holds an MBA from Santa Clara University, and a BA in Computer Science from the University of California, Berkeley.