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Join us for an Apache Kafka meetup on Wednesday February 13th from 6:30pm, hosted by codecentric in Berlin. The address, agenda and speaker information can be found below. See you there!
Agenda:
6:30pm: Doors open
6:30pm – 7:00pm: Networking
7:00pm – 7:45pm: Presentation #1: Title TBC, Pere Urbon Bayes, Confluent
7:45pm – 8:30pm: Presentation #2: ATM Fraud Detection with Apache Kafka and KSQL, Robin Moffatt, Confluent
8:30pm – 9:00pm: Networking, Pizza and Drinks
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Speaker 1:
Pere Urbon Bayes
Bio:
Pere is a Technology Architect for Confluent out of Berlin, Germany. He has been working with data and architecting systems for more than 15 years as a freelance engineer and consultant. In that role he was focused on data processing and search, helping companies build reliable and scalable data architectures. His work sits usually at the crossroad of infrastructure, data engineers and scientists, ontologist and product. Prior to that he was part of Elastic, the company behind Elasticsearch, where he was part of the Logstash team, helping companies build reliable ingestion pipelines into Elasticsearch. When not working, Pere loves to spend time with his lovely wife and kids and to train for a good long distance race or duathlon.
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Speaker 2:
Robin Moffatt
Bio:
Robin is a Developer Advocate at Confluent, the company founded by the creators of Apache Kafka, as well as an Oracle Groundbreaker Ambassador and ACE Director (Alumnus). His career has always involved data, from the old worlds of COBOL and DB2, through the worlds of Oracle and Hadoop, and into the current world with Kafka. His particular interests are analytics, systems architecture, performance testing and optimization. He blogs at http://cnfl.io/rmoff and http://rmoff.net/ (and previously http://ritt.md/rmoff) and can be found tweeting grumpy geek thoughts as @rmoff. Outside of work he enjoys drinking good beer and eating fried breakfasts, although generally not at the same time.
Title:
ATM Fraud Detection with Apache Kafka and KSQL
Abstract:
Detecting fraudulent activity in real time can save a business significant amounts of money, but has traditionally been an area requiring a lot of complex programming and frameworks, particularly at scale. Using KSQL, it’s possible to use just SQL to build scalable real-time applications.
In this talk, we’ll look at what KSQL is, and how its ability to join streams of events can be used to detect possibly fraudulent activity based on a stream of ATM transactions. We’ll also see how easy it is to integrate Kafka with other systems—both upstream and downstream—using Kafka Connect to stream from a database into Kafka, and from Kafka into Elasticsearch.