Episode 52: Graph Databases In Action with Dave Bechberger

Show Notes(2:10) Dave talked briefly about his Electrical Engineering study at Rensselaer Polytechnic Institute back in the late 90s.(4:03) Dave commented on his career phase working as a software engineer across various companies in Bozeman, Montana.(7:38) Dave discussed his work as a senior architect and tech lead at Expero, a Houston-based startup that develops custom software exclusively for domain-expert users.(11:26) Dave briefly defined common big data frameworks (Hadoop, Apache Spark) and databases (Apache Cassandra, Apache Kafka).(13:37) Dave went over the challenges during his time as a chief software architect at Gene by Gene, a biotech company focusing on DNA-based ancestry and genealogy.(20:00) Dave shared the common patterns and anti-patterns of using graph databases (in reference to his talk “A Practical Guide to Graph Databases”).(26:16) Dave walked through the three categories of graph technologies: Graph Computing Engine, RDF TripleStore, and Labeled Property Graph (in reference to his talk “A Skeptics Guide to Graph Databases”).(33:03) Dave discussed his move to DataStax’s Global Graph Practice team as a solutions architect and graph database subject matter expert.(36:00) Dave explained the design of DataStax’s enterprise solution called Customer 360, which collapses data silos to drive business value.(41:16) Dave talked about his current experience as a Senior Graph Architect at AWS.(43:51) Dave mentioned the challenges while writing "Graph Databases In Action" (published last October).(47:25) Dave explained the open-source Apache TinkerPop framework and the Gremlin language used in the book for the uninitiated.(51:04) Dave discussed trends in big data and distributed systems that he is most excited about.(55:06) Closing segment.His Contact InfoWebsiteTwitterLinkedInGitHubHis Recommended Resources"Graph Databases In Action" (Associated Code Repository)Martin Fowler (Founder of ThoughtWorks)Martin Kleppmann (Author of "Designing Data-Intensive Applications")Andrew Ng (Professor at Stanford, Co-Founder of Google Brain and Coursera, Ex-Chief Scientist at Baidu)"Pragmatic Programmer" (by Andy Hunt and Dave Thomas)"The Five Dysfunctions Of A Team" (by Patrick Lencioni)"How To Observe Scientific Advice for Common Real-World Problems" (by Randall Munroe)

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Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe.

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