Agile Data Science

Jun 29 - 30, 2017 · Plano, United States of America

Russell Jurney returns to "talk up" the concept Agile Data Science. 

This is a joint event with DFW Data Science and MongoDB User Group - so - yes - this is posted in more than one place. 

 
In Russell's words:

Agile Data Science 2.0 covers the theory and practice of applying agile methods to the practice of applied research called data science. The book takes the stance that data products are the preferred output format for data science teams to effect change in an organization. Accordingly, we show how to "get meta" and build applications describing the applied research process itself. Then we show how to use 'big data' tools to iteratively build, deploy and refine applications. Technologies covered include Python, Apache Spark, Apache Kafka, MongoDB, ElasticSearch and Apache Airflow.


My name is Russell Jurney. I am 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. I’ve worked as a data scientist building data products for over a decade, starting in interactive web visualization and then segwaying towards data products, machine learning and artificial intelligence at companies such as Ning, LinkedIn and Hortonworks. I am a self taught visualization software engineer, data engineer, data scientist, writer. Social Media Links:

[masked] (fine to give out)

http://twitter.com/rjurney

http://linkedin.com/in/russelljurney

http://github.com/rjurney/Agile_Data_Code_2

http://bit.ly/agile_data_science

As usual, we will provide pizza, soda, beer.

Event organizers
  • DFW BigData

    Come join us for discussions, presentations, and networking for use-cases, design, technologies, etc centered around all things NoSQL and BigData! It also services as a HUG (Hadoop Users Group) for DFW. BigData? http://en.wikipedia.org/wiki/Big_data NoSQL? http://en.wikipedia.org/wiki/Nosql Example types of things we like to talk about: hadoop stack: HBase, HDFS, Hive, Pig, MapReduc...

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