Some missing sections? #2
Description
Hi,
First of all, congratulations on the awesome work. I have been in the Data engineering space for some time and this is one of the best written roadmaps / guides to learning the area! It is both excellent in content and appealing in presentation.
I did have a couple of suggestions though where I felt it was missing some key resources and wanted to see if you like the idea, I can submit a PR.
- Any discussion of Data Engg today without reference to offerings in the 3 major Cloud providers or other related cloud technologies in the space (such as Amazon Glue, Apache Beam, etc.) seems incomplete
- A touch of the Periscope, Mode, Looker, Superset world would also help complete the picture since the line between these and Data Engg is sometimes blurry
- No reference to modern ETL / ELT tooling such as dbt, Stitch, Fivetran etc.?
- Touching on data storage formats - Avro, Thrift, Parquet
- Mention of Pulsar
- Mention of Prefect, Dagster as upcoming challengers to Ariflow
Thanks!