Estimating Fare Evasion on Public Transit and Spark Overview + Demo

Talks will start at 6:30pm and end around 8:15pm. Show up around 6pm to network and have a drink.

If you are looking for a job or looking for engineers, bring your resume, business card, or job posting! We'll have a pin board for you to advertise.

We are looking for speakers for upcoming meetups! Email the organizers or talk to us at the meetup to volunteer.

Note that we have the same gracious hosts but the location has moved across town to 3700 O'Donnell Street, Suite 100.

Parking is available in the purple shadded areas of the map below. The yellow X marks the building location.

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Talk 1: Analytic Use Case: Estimating Fare Evasion on Public Transit

Have you ever boarded the Light Rail without buying a ticket? If your answer is yes, you are not alone. Fare evasion on public transportation is a major problem that transit agencies are trying to better understand and address. This talk will cover a recent analytic exercise performed by Spry (http://spryinc.com/) that provided an estimate of fare evasion rates through data analysis, instead of manual methods. We will cover the end-to-end analytic process: the initial business question, data exploration, implementation, and final visualizations.

Kristen Hardwick
Vice President of Big Data Solutions | Spry, Inc.

Talk 2: Adding Spark to Your Hadoop: Spark Overview and Live Demo

Some background on Spark, its Resilient Distributed Dataset (RDD) abstraction and methods. We will use the Enron email set in Avro format and compare Hadoop vs. Spark processing to ask a basic question. Along the line we explore the Spark's API.

Markus Dale
Software Developer | DoD

Markus Dale is a software developer with DoD where he focuses on large scale data processing. He also developed and taught a Hadoop for developers class for UMBC Training. His blog is http://uebercomputing.com (http://uebercomputing.com/)