Chapter
Chapter 1: Google Cloud and Google BigQuery
Getting started with Google Cloud
Overviewing Google Cloud Platform services
Google Cloud storage and its features
Getting started with Cloud SQL
App engine standard environment
App engine flexible environment
Chapter 2: Google Cloud SDK
Installing Google Cloud SDK
Installing Google Cloud SDK on Windows
Installing Google Cloud SDK on macOS
Installing Google Cloud SDK on Linux
gsutil for Google Cloud Storage
Using the bq utility for BigQuery
Connecting to Cloud SQL using gcloud
Authorizing the client machine via Google Cloud Console
Connecting using a proxy script
Exporting Cloud SQL databases and tables
Deploying to Google App Engine
Chapter 3: Google BigQuery Data Types
When to transform your data? Before or after loading to BigQuery?
Regular Expression Functions
Functions for transformation
Mastering transformation with User-Defined Functions
Some considerations when using UDFs
Chapter 4: BigQuery SQL Basic
Commenting in BigQuery SQL
Qualifying tables in query
Joining tables in BigQuery
UNION, UNION ALL, and UNION DISTINCT
Adding your own data in BigQuery
Inserting data to a table
Deleting data from a table
Chapter 5: BigQuery SQL Advanced
Creating a partition table using a GUI
Creating a partition table using Google Cloud SDK
Querying data in a partition table
Using partition tables in your projects
Querying external data sources using BigQuery
Creating the table definition
Querying data from external data sources
Querying nested and repeated records
Chapter 6: Google BigQuery API
Accessing Google BigQuery
Introducing Google APIs explorer
Getting credentials for API access
Creating a service account
Programming with BigQuery API in C# .NET
Authenticating the service account
Listing all datasets and all tables in the project
Creating a new dataset in the project
Creating a new table within a dataset
Loading data from a file in Google Cloud Storage to a BigQuery table
Executing a query and displaying the result
Executing the query and saving the result in a new table
Programming with BigQuery API in Python
Listing all datasets and all tables in the project
Creating a new dataset in the project
Creating a new table within a dataset
Importing data from a file in Google Cloud Storage to a BigQuery table
Executing a query and displaying the result
Execute query and copy results to a new table
Chapter 7: Visualizing BigQuery Data
Why is data visualization important?
The danger of summary statistics
Making data visualization work for you
Three tools for visualizing BigQuery data
Simple yet basic – Google Data Studio
Making a scatterplot in Data Studio
Making a map in Data Studio
Other features of Data Studio
Simple, fairly flexible, but with a cost – Tableau
Create a word cloud in Tableau
Complex but with considerable flexibility – the R programming language
Chapter 8: Google Cloud Pub/Sub
Getting started with Cloud Pub/Sub
Cloud Pub/Sub via Google Cloud Console
Cloud Pub/Sub via Google Cloud SDK
Importing message data into BigQuery
Learning Google BigQuery
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