Introduction to Google Cloud's Big Data and Machine Learning Functions through hands-on labs using Qwiklabs to process Big Data at scale for Analytics and Machine Learning, Exploring the fundamentals of building new Machine learning models and Creating streaming data pipelines and dashboards.
Objectives: Query a public dataset, Create a custom table, Load data into a table and Query a table
Populating rentals data in Cloud SQL for the rentals recommendation engine to use. The recommendations engine itself will run on Dataproc using Spark ML.
Create a Cloud SQL instance, Create database tables by importing .sql files from Cloud Storage, Populate the tables by importing .csv files from Cloud Storage, Allow access to Cloud SQL and Explore the rentals data using SQL statements from Cloud Shell.