Big query is helpful for serverless warehouse
A lot of features for a data analytics platform: big query ML, BI engine, GIS, Omni (outside of Google Cloud, part of the Kubernetes ecosystem)
Big query ML allow to create ML model in SQL
Linear Regression, Matrix factorization, Boosting tree, Tensorflow, AutoML (params search and algo search for you with good performances)
Hyperparams tuning is much easier
No need to export data, no need to be proficient with Python or Java
Create model
SQL
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CREATE MODEL `our_model`
OPTIONS (
(model_type='linear_reg',
input_label_cols=['weight_pounds']
) AS
SELECT
weight_pounds,
feature_1,
feature_2,
...
FROM big_query.dataset
WHERE filter ...
Predictions
SQL
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SELECT
predicted_weight_pounds
FROM
ML.PREDICT(
MODEL `our_model`,
(
SELECT
is_male,
gestation_weeks,
mother_age,
...
FROM big_query.dataset
WHERE filter ...
)