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本周先学习如下
A Beginner’s Guide to Data Engineering (Part 1): A very popular post on data engineering from a data scientist at Airbnb. The author first explains why data engineering is such a critical aspect of any machine learning project, and then deep dives into the various component of this subject. I consider this a compulsory read for all aspiring data engineers AND data scientists.
A Beginner’s Guide to Data Engineering (Part 2): Continuing on from the above post, part 2 looks at data modeling, data partitioning, Airflow, and best practices for ETL.
A Beginner’s Guide to Data Engineering (Part 3): The final part of this amazing series looks at the concept of a data engineering framework. Throughout the series, the author keeps relating the theory to practical concepts at Airbnb, and that trend continues here. A truly exquisitely written series of articles.
O’Reilly’s Suite of Free Data Engineering E-Books: O’Reilly is known for their excellent books, and this collection is no exception to that. Except, these books are free! Scroll down to the ‘Big Data Architecture’ section and check out the books there. Some of these require a bit of knowledge regarding Big Data infrastructure, but these books will help you get acquainted with the intricacies of data engineering task |