Mapflatlands - data engineering resources This is the start of a collection with resources for data engineering. Over time, the plan is to grow the collection to cover the most relevant topics in data engineering, with a focus on holistic views and on practical advice for building products - information beyond the usual Spark and Hadoop tutorials, necessary to generate sustainable business value from data streams.
The first piece is a curated reading and watching list for anyone aspiring to build data processing systems at scale.
Essential resources for data engineers This resource list has moved to scling.com. The contents below are left as a reference, but will not be updated.
This is a curated recommended read and watch list for scalable data processing. It is primarily aimed towards software architects and developers, but there is material also for people in leadership position as well as data scientists, in particular in the first section. The content has been chosen with a bias towards material that conveys a good understanding of the field as a whole and is relevant for building practical applications.
