This is a book review of ‘Data Science on the Google Cloud Platform: Implementing End-to-End Real-Time Data Pipelines: From Ingest to Machine Learning’ by Valliappa Lakshmanan.
The book is an interesting read about the inner workings of using Google Cloud services with real-world data science case studies. Valliappa is a Tech Lead for Google Cloud so the author is highly qualified to discuss the subject.
As a bonus, you can follow the code examples in the book by grabbing the code on github.com.
Chapter one is an absolute must read for data analysts, database administrators, data scientists and systems programmers escpecially those pondering career moves.
Some interesting thoughts and concepts just from chapter one…
- Future role of DBA’s and other IT data professionals will include creating data science models.
- Data science models will be implemented as scaleable, high-quality, production systems.
- Specialized job functions that exist today will not be needed in the future since the cloud offers many pre-configured resources that used to be performed by various specialists.
- You collect data to do data analysis that leads to making better decisions.
- Data driven decisions can be better than heuristics.
I give this book a thumbs up for using real world case studies and providing the code on github.com to solve the problems as you follow the book’s dialog.