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Data Science Meetup: Using Graphs to Expose Corruption from Some of World's Largest Data Leaks

  • Hub101 31416 Agoura Rd #105, (map)

Data Engineers and Scientists are always intrigued by new data sources. From spreadsheets and SQL to No-SQL sources such as MongoDB and XML. We will hear from Neo4j, provider of a native graph (think network) database. As any practitioner of AI and Machine Learning knows, relationships provide critical insights to our understanding and forecasting capabilities. Learn how you can leverage these insights to work for you.

With the assistance of Neo4j's graph experts, the International Consortium for Investigative Journalism won the Pulitzer Prize for exposing the complex relationships hidden away in the Panama Papers (largest data breach of unstructured data) of the wealthy, their money, government officials, and tax havens. Neo also provided them with expertise for analyzing the subsequent Paradise Papers. More recently, Neo helped MSNBC use graph techniques to successfully identify the Russian Trolls responsible for over 200k fake tweets during the 2016 election. Discover the techniques used in these projects and how they are being used successfully by many global organizations for their cybersecurity, identity resolution, and fraud use cases.


Justin Fine is based in Los Angeles, CA and is a Field Engineer working mainly in the SoCal region. His academic background is applied mathematics and has worked with graphs for over 12 years in many different verticals while consulting (federal, telecoms, financial, etc). During this time as a consultant his focus was mainly advanced analytics utilizing NoSQL technologies. He recently comes from Microsoft's Azure team where he was a Data Solution architect and is very excited to be part of the Neo4j family! When Justin isn't nerding he enjoys scotch, cigars, and reading with his cat Penny.

Earlier Event: June 6
Freelancers Academy
Later Event: June 13
Freelancers Academy