More Resources

The advent of Apache Hadoop™ has led many organizations to replatform their existing architectures to reduce data management costs and find new ways to unlock the value of their data. There’s undoubtedly a lot to gain by modernizing data warehouse architectures to leverage new technologies, however Hadoop projects are often taking longer than they need to create the promised benefits, and often times problems can be avoided if you know what to avoid from the onset.

As it turns out, the key to replatforming is understanding the implications of building, executing and operating dataflow pipelines.

This guide is designed to help take the guesswork out of replatforming to Hadoop and to provide useful tips and advice for delivering success faster.




About StreamSets

Big data doesn't need to be hard. Whether using Apache Hadoop, Spark or Kafka, leading companies are leveraging StreamSets to streamline their big data journey and deliver success. StreamSets focuses on simplifying the process of building, executing and operating dataflow pipelines. The StreamSets platform combines award-winning open source software for the development of any-to-any dataflows that uniquely handle data drift with a cloud-native control plane that centralizes building, executing and operating dataflow topologies at enterprise scale. Whether you're just starting with big data, or consider yourself an expert, StreamSets can help extend the value of your deployment to deliver greater results for your business.



 
Facebook link