Presented By O'Reilly and Cloudera
Make Data Work
March 13–14, 2017: Training
March 14–16, 2017: Tutorials & Conference
San Jose, CA

Office Hour with Russell Jurney (Data Syndrome)

Russell Jurney (Data Syndrome)
11:00am11:40am Thursday, March 16, 2017
Location: Table B

Join Russell to discuss the analytics methodology outlined in his book Agile Data Science 2.0 and the creation, deployment, and iterative improvement of a real-time predictive system using Python, Spark MLlib, Spark Streaming, Kafka, MongoDB, and JQuery.

Photo of Russell Jurney

Russell Jurney

Data Syndrome

Russell Jurney is principal consultant at Data Syndrome, a product analytics consultancy dedicated to advancing the adoption of the development methodology Agile data science, as outlined in the book Agile Data Science 2.0 (O’Reilly, 2017). Previously, he worked as a data scientist building data products for over a decade, starting in interactive web visualization and then moving toward full stack data products, machine learning, and artificial intelligence at companies such as NING, LinkedIn, Hortonworks and Relato. He’s a self-taught visualization software engineer, data engineer, data scientist, writer, and most recently teacher. In addition to helping companies build analytics products, Data Syndrome offers live and video training courses.

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Picture of Russell Jurney
02/09/2017 3:14pm PST

I look forward to talking about the theory and practice of agile data science. The theory is that all data science is iterative application development where we get “meta” and build an application describing the applied research process itself. The application component is a guide to practicing agile data science to develop a full-stack “big data” application using an example stack with some of the most popular and desirable tools: Kafka, Spark, Spark Streaming, MongoDB, Elasticsearch, Airflow, Python, Flask and d3.js. I look forward to an active, engaged conversation with data science and data engineering practitioners and fans.