Introduction to BigQuery#
BigQuery is a serverless, highly scalable, cost-effective, and fully managed cloud data warehouse for analytics.
In this first section, we will upload a file to BigQuery to use as input for our DP query. We will use the same input data as for the Tumult Analytics tutorial, which is provided as a CSV file.
Go to the BigQuery interface
Create a new dataset by clicking on the three dots on the right of your project name and selecting “Create dataset”
Name the dataset
Create a new table by clicking on the three dots on the right of the dataset name and selecting “Create table”
In the table creation page, select “Upload” under “Create table from” and select the CSV file you downloaded from https://tumult-public.s3.amazonaws.com/library-members.csv
Name the table
Select the file format as “CSV”
Under Schema, select “Auto detect”
Click on “Create table”
With our data in place, we can explore the data in BigQuery. We can expand the dataset we previously created, open up the table to see the schema, and query the data in the query editor using SQL.
Now that we’ve set up our environment in BigQuery, let’s move on to the next part of the topic guide and see how we would modify a simple Tumult Analtyics program to be able to run in BigQuery.