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#### Turn Streaming Data into Instant Dashboards with AWS & CrateDB

#### Join us in Vienna for a guided deep dive into real-time analytics on AWS, co-hosted with AWS and CrateDB. In this session, we’ll walk you through how modern, event-driven data pipelines turn streaming data into instant, actionable dashboards without the need to code or bring a laptop.

Together with experts from AWS and CrateDB, we’ll explore a fully managed analytics architecture on AWS, from event ingestion and real-time processing to storage, analysis, and visualization. Using Amazon MSK, AWS Lambda, CrateDB Cloud, and Grafana, we’ll demonstrate how cloud-native services work seamlessly together to deliver low-latency insights at scale.

As a highlight of the event, you’ll visit an Amazon distribution center, gaining first-hand insights into Amazon’s supply chain and operations. Using real-world examples from Amazon’s retail and logistics business, we’ll also show how data and artificial intelligence are used to improve customer experience, increase efficiency, and reduce operational costs.

Register now

## Why You Should Attend

  • Learn how AWS-managed services enable real-time, event-driven analytics with minimal operational complexity
  • Understand how streaming, time-series, and semi-structured data can be analyzed in real time using SQL
  • See how live dashboards and monitoring enable faster, data-driven decisions
  • Gain exclusive insights into Amazon’s logistics operations and data-driven innovation
  • Connect with peers from the data, cloud, and architecture community over drinks and refreshments ☕🍩

Join us

## Who Should Join

  • Developers and data engineers working with event streams or analytics pipelines
  • Solution architects designing modern, real-time platforms
  • Technology leaders exploring modern, cloud-native data platforms
  • Anyone eager to explore the next generation of streaming data technologies

Seats are limited. Reserve your spot now!

Related topics

Events in Wien
Big Data
Data Analytics
SQL
Open Source

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