
The concepts and architectures of a data warehouse, a data lake, and data streaming are complementary to solving business problems. Unfortunately, the underlying technologies are

The concepts and architectures of a data warehouse, a data lake, and data streaming are complementary to solving business problems. Unfortunately, the underlying technologies are

Apache Kafka became the de facto standard for processing data in motion. Kafka is open, flexible, and scalable. Unfortunately, the latter makes operations a challenge
The article discusses what stream processing is, how it fits into a big data architecture with Hadoop and a data warehouse (DWH), when stream processing
Slides from my talk “Hadoop and Data Warehouse (DWH) – Friends, Enemies or Profiteers? What about Real Time?” at JAX 2014 (Twitter #jaxcon) in Mainz
In this blog post, I will show you how to „ETL“ all kinds of data to Amazon’s cloud data warehouse Redshift wit Talend’s big data