What is BigQuery?
BigQuery is a fully managed petascale data warehouse.
It can process huge amounts of data very quickly.
BigQuery is a serverless managed data lake. Once you load the data, operational tasks and availability are automated.
BigQuery use cases:
- Big Data
BigQuery antipattern use cases:
Our BigQuery Blogs
- BigQuery Demystified
- bigquery bq load error- “cannot determine table described”
- Quick Start on GCP BigQuery – 5 rules of thumb
- Google BigQuery Demystified
- BigQuery Cheat Sheet
- BigQuery CLI Cheat Sheet
- K Means Via BQ ML Demystified
- Parsing the last 4 days of google analytics table GA_sessions in google BigQuery
- what really happens when you unnest customDimentions in ga_sessions_* (hint data inaccuracy)
- When to use BigQuery? When not to use BigQuery?
BigQuery cost reduction
- GCP Cost Reduction in a nutshell
- what is the cheapest ways to parse GA_sessions at big query? What is the fastest way to parse GA_sessions at big query? What is the simplest way to parse GA_sessions at big query?
- DFP Data Transfer Files Use Case | BigQuery 93% Cost Reduction demystified
- How can I get BigQuery cost per query per user?
BigQuery "how to"
- Keep your data encrypted in BigQuery
- How to export data from Google Big Query into AWS S3 + EMR hive or AWS Athena
- AVRO and BigQuery example
- Big Query CTAS partitioned by Date or Int example
- How to debug BigQuery query failure in Airflow DAG?
- How can I connect BigQuery and GCP Cloud SQL ? | GCP Cloud SQL federated queries