Dawid Wysakowicz works as a Data Engineer at GetInData working to help people and companies succeed with Apache Flink. Actively participates in the Flink community what resulted in becoming a committer. First interested with Big Data technologies in 2015 while writing Master Thesis on Distributed Genomic Datawarehouse. Recently had helped to extract value from large datasets at mBank.
Topic: Streaming analytics better than batch – when and why
While a lot of problems can be solved in batch, the stream processing approach currently gives you more benefits. And it’s not only sub-second latency at scale. But mainly possibility … to express accurate analytics with little effort – something that is hard or usually ignored with older batch technologies like Pig, Scalding, Spark or even established stream processors like Storm or Spark Streaming. In this talk we’ll use a real-world example of user session analytics (inspired by Spotify) to give you a use-case driven overview of business and technical problems that modern stream processing technologies like Flink help you solve, and benefits you can get by using them today for processing your data as a stream.