Kalyan chakravarthi Janaki

Join this interactive chalk talk to explore best practices for building high-performing, cost-efficient Spark applications using AWS analytics data processing services.

Streaming data pipelines make it possible to access and extract value from your data before it loses its shelf life, and customers today are increasingly looking for scalable, efficient and cost-effective ways of building real-time data pipelines that can provide immediate data availability in the desired format and…

Streaming data pipelines make it possible to access and extract value from your data before it loses its shelf life, and customers today are increasingly looking for scalable, efficient, and cost-effective ways of building real-time data pipelines that can provide immediate data availability in the desired format and…

Real-time recommendation engines for gaming help developers attain better gameplay metrics based on user cohorts. However, this type of AI/ML solution requires expertise in data science and infrastructure.

One of the best ways to get timely insights and react quickly to new information that you receive from your business and your applications is to analyze streaming data. In this session, learn how, with a single click, you can start an Amazon Kinesis Data Analytics Studio notebook powered by Apache Zeppelin and Apache Flink to interactively analyze data in your stream using SQL, Python, or Scala.