Google Cloud: Difference between revisions
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==Case Study== | ==Case Study== | ||
The [[GCDEC]] page gives an example of a case study that can be used to see how different parts of the Google Cloud platform come together in the kind of scenario a real company might face: | |||
[[Google Cloud/Case Study]] | [[Google Cloud/Case Study]] | ||
==Google Cloud Services== | |||
Notes on all of the various parts of the Google Cloud platform and the services available on it. | |||
===Introduction=== | |||
Google Cloud for Big Data | |||
* MapReduce | |||
* Spark | |||
* BigQuery | |||
Usage scenarios | |||
===Foundations=== | |||
Compute and Storage | |||
Data ingestion | |||
Data storage | |||
Federated analysis | |||
Compute engine | |||
Cloud storage | |||
===Data Analytics=== | |||
Cloud SQL | |||
Dataproc for machine learning | |||
[[Category:Google Cloud]] | [[Category:Google Cloud]] | ||
Revision as of 17:42, 15 September 2017
Notes for Google Cloud Data Engineer (GCDE) certification. See GCDE.
Links:
- Certification info: https://cloud.google.com/certification/data-engineer
- Sample case study: https://cloud.google.com/certification/guides/data-engineer/casestudy-flowlogistic
- Tutorials/Guides/Resources for all of Google Cloud: https://cloud.google.com/solutions/
Case Study
The GCDEC page gives an example of a case study that can be used to see how different parts of the Google Cloud platform come together in the kind of scenario a real company might face:
Google Cloud Services
Notes on all of the various parts of the Google Cloud platform and the services available on it.
Introduction
Google Cloud for Big Data
- MapReduce
- Spark
- BigQuery
Usage scenarios
Foundations
Compute and Storage
Data ingestion
Data storage
Federated analysis
Compute engine
Cloud storage
Data Analytics
Cloud SQL
Dataproc for machine learning