What we’re about
Full Stack Data Science is the capability for the data-driven future we all know is coming. We also know that the world needs more data scientists and full stack developers. While we wait for more to hatch, we need to make more of our own because it is good for all of us to do so. The Full Stack Data Science Meet-up is oriented towards promoting a “full stack” approach to data science bringing much needed integration to the data science conversation across multiple disciplines ("defragging" data science, so to speak). How do you scale data science capabilities to serve the enterprise? Topics of discussion are centered on tough (and surprisingly common) challenges around data management; collection and ingestion; data architecture; exploratory, advanced, and secondary analytics; knowledge presentation and visualization; access and security, and measurement and assessment. Full Stack Data Science is meeting the data explosion head on and hungry to identify new relationships and opportunities in our data. In the end, the goal of Full Stack Data Science is help organizations, and the people in them, build a sustainable capability to improve performance, optimize investments, manage risk, and gain competitive advantage.
Full Stack Data Science is a Community Member of Data Community DC, Inc.
Upcoming events (1)
See all- Scaling text ETL & model deployment for data-driven policy analysisExcella, Arlington, VA
We're back!
Join us for our monthly Full Stack Data Science Meetup where we will discuss Data Science Developer Workflows!
In this meetup, we'll explore the tools and best practices that data scientists can leverage to be more effective at developing production-ready data solutions.
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Agenda:
5:30-6:15 - Networking and refreshments
6:15-6:30 - Introductions
6:30 - 8:00 Presentations & DemosPresentation: Scaling text ETL and model deployment for data-driven policy analysis.
Description: The Center for Security and Emerging Technology is a think tank at Georgetown University that studies security implications of emerging technologies, including data-driven analyses across bibliometric, patenting, and investment datasets. Jennifer Melot, technical lead of the Emerging Technology Observatory effort at CSET, will describe their data infrastructure based on Apache Airflow and Beam running on the Google Cloud Platform that orchestrates ETL and various data enhancements including model deployment. She will also share some comments and lessons learned from building data pipelines on a small data team."