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Real Life (Structured) Streaming & Customer Lifetime Value
July 27, 2017 @ 6:30 pm - 9:00 pm
Please come along to our next summer Meetup! We have a couple of really interesting talks from our community this time and as usual there will be free beer and pizza courtesy of our sponsors Capgemini so please do come along!
Web development to big data. A journey
Speaker: Sam Elamin
Writing streaming applications is very hard. At first glance, building a distributed streaming engine might seem as simple as launching a set of servers and pushing data between them. Unfortunately, distributed stream processing runs into multiple complications that don’t affect simpler computations like batch jobs. In this talk Sam Elamin will relate his real life experience writing streaming applications to Kineses and Google Big Query, and delve deeper into the new structured streaming API that was released with Spark 2. In the end of the talk you should have an idea of what exactly is a continuous application and what are its benefits
Sam Elamin is a Big Data Engineer as well as a Software Craftsman and Apache Spark evangelist. Sam is interested in Big Data, Metrics Driven Development, Continuous Delivery and is currently exploring Real Time Analytics, as as well as streaming tools and frameworks like Apache Spark, Kinesis, Kafka and Google Big Query.
Attributed Customer Lifetime Value
Speaker: Sri Perangur (Skyscanner)
In the Growth side of the business, she is designing metrics to optimize marketing investments. Her latest project, Attribution of CLV, is aimed at enabling the use of Customer Lifetime Value (CLV) in marketing investments through multi-touch attribution.
Today she will speak about how Apache Spark has been fundamental in enabling her project to be applicable at scale. The architecture behind it and why it compares better to other tools like Redshift. Subsequently how using Spark is becoming the norm for Data Science @ Skyscanner.
Sri² ( short for Sri Sri) is a Data Scientist @ Skyscanner HQ in Edinburgh UK.
Academically, she comes from a computing and A.I. background from University of York. After some years in BAE Systems Applied Intelligence Labs, finance Capital Markets sector she started her Data Scientist career with (state.com) a Social Network where she worked with user Opinion and Sentiment graphs.
Then she moved to Skyscanner as their first formal Data Scientist, working on the Growth side of the business.