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Demystifying event streams: Transforming events into tables with dbt

dbt Developer Hub

Let’s discuss how to convert events from an event-driven microservice architecture into relational tables in a warehouse like Snowflake. In this blog post we’ll dive into how we tackled one source of quality issues: directly relying on upstream database schemas. So our solution was to start using an intentional contract: Events.

Kafka 52
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Cloudera spotlights partner success at Strata Data with Partner Impact Awards

Cloudera

Cloudera aimed to demystify the “how” in the AI and big data equation at Strata Data through helpful sessions, anticipated keynotes, and new product announcements to alleviate the mystery associated with leveraging this revolutionary technology. Congratulations to all of our partner winners – we will see you next year at Strata 2019!

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Making Sense of Real-Time Analytics on Streaming Data, Part 1: The Landscape

Rockset

Introduction Let’s get this out of the way at the beginning: understanding effective streaming data architectures is hard, and understanding how to make use of streaming data for analytics is really hard. Stream processing or an OLAP database? What Is Streaming Data? Streaming data has been around for decades.

Kafka 52
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Data Engineering Weekly #139

Data Engineering Weekly

This blog post will delve into these questions, tackle common misconceptions, and give you an intuitive understanding of how to think about GPUs. The blog classifies the pattern of prompt engineering from its experience building Github CoPilot. The blog overviews potential information leakage and how to minimize it.