Google Cloud Professional Data Engineer
Google Cloud Professional Data Engineer Certification (Jan 2021)
Disclaimer: Non official content, errors and omissions excepted
Exam Knowledge Areas
Pre Exam Notes
- Kryterion Sentinel software (Windows/Mac) installation requires administrator rights
- Kyterion system check - do this at least a day before to be on the safe side
- No breaks during two hour exam
- Do the practice exam to build some confidence
- (Try and) get a good nights sleep before the exam
- The exam is multiple choice, so work out the wrong answers first!!
Post Exam Notes
- Pretty comprehensive overview of using data on Google Cloud.
- Lots of questions on handling data - generally quite thought provoking
- Some complexity in the questions, but most written to be clear
- Still no feedback beyond pass/fail
- 50 Questions
- A couple of stinker permission questions - ProTip, read the question backwards
General list of topics that are potentially covered based on the exam criteria:
- BigData
- Databases
- Storage
- Networking
- Compute
- Operations
Training Material
The material I used to get ready for the exam.
| Source | Type | Description | Rating |
|---|---|---|---|
| Linux Academy | Course | Exam specific content, good practice questions | 4/5 |
| Coursera | Course | Data Engineering, Big Data and Machine Learning | 3/5 |
| Pluralsight | Course | Data Engineering, Big Data and Machine Learning | 3/5 |
| Perform Foundational Data, ML and AI tasks in Google Cloud | Hands On Labs | Good content | 4/5 |
| Engineer Data in Google Cloud | Hands On Labs | Good content | 3.5/5 |
| Google Cloud Docs | Docs | Very detailed | 4/5 |
| Google Cloud Platform | YouTube | Treasure trove of informative sessions - very helpful | 4/5 |
| Professional Data Engineer | Book | Very detailed overview of exam syllabus | 4/5 |
| Awesome GCP Certification | Links | Good list of materials and sources | 4/5 |