Real-Time Detection and Alerting of Unwanted Credit Card Charges

Sep 25, 2019 · New York, United States of America

Please join us for an evening event at the Press Lounge rooftop with a 360-degree view of the mighty Manhattan skyline and the Hudson River! We will discuss an enterprise real-time streaming data use case for detection and alerting of unwanted credit card charges. This use case is not only the foundation for other use cases in financial services but will be inspiring for other use cases in other verticals as well.

RSVP Details: You must have your full name as it appears on your ID on your meetup account to pass beyond building security. Guests must join the NYC Advanced Analytics Meetup.

Schedule:

6:00 - 6:30 pm - Networking over pizza and drinks
6:30 - 7:15 pm - Talk by Slim Baltagi
7:15 - 7:30 pm - Q&A and networking

Sponsors:

• Striim (http://www.striim.com/) is hosting the event and is offering pizza and drinks.

Talk description:

This first part of this talk is about the business problem and potential benefits of the solution to end users as well as service providers.

The second part is about the solution architecture, implementation options and tools selection.

The third part is about building the solution with the end-to-end Striim platform: a single platform that combines real-time ingestion, stream processing and real-time delivery of streaming data while overcoming the complexity and higher cost of stitching together disparate tools.

Speaker's bio:

Slim Baltagi (https://www.linkedin.com/in/slimbaltagi/ ) is a Director of Big Data and Machine Learning at Cervello, an A.T. Kearney company.
Slim is an IT leader with many years of extensive Big Data experience and more recently Machine Learning. As director, architect and engineer he delivered many end-to-end data projects to major Fortune 500 companies in many verticals.
Slim enjoys being considered a thought leader, speaking at many conferences and organizing many advanced analytics meetups at major tech hubs in US cities and abroad.

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