Google Platform Fundamentals Overview.
Google Cloud Platform Big Data Products.
CPUs on demand (Compute Engine).
A global filesystem (Cloud Storage).
Lab: Set up a Ingest-Transform-Publish data processing pipeline.
Stepping-stones to the cloud.
Cloud SQL: your SQL database on the cloud.
Lab: Importing data into CloudSQL and running queries.
Spark on Dataproc.
Lab: Machine Learning Recommendations with Spark on Dataproc.
Fast random access.
Lab: Build machine learning dataset.
Machine Learning with TensorFlow.
Lab: Carry out ML with TensorFlow
Pre-built models for common needs.
Lab: Employ ML APIs.
Message-oriented architectures with Pub/Sub.
Creating pipelines with Dataflow.
Reference architecture for real-time and batch data processing.
Where to go from here