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Data analytics is one of GCP's greatest strengths. Google pioneered technologies like MapReduce, Dremel, and Colossus that revolutionised how the world processes data. BigQuery — GCP's serverless data warehouse — is a direct descendant of these innovations.
BigQuery is a serverless, petabyte-scale data warehouse designed for fast SQL analytics over large datasets.
| Feature | Detail |
|---|---|
| Serverless | No infrastructure to manage — no clusters, no tuning |
| Petabyte scale | Analyse massive datasets in seconds |
| Standard SQL | Full ANSI SQL support |
| Columnar storage | Data stored in columns for fast analytical queries |
| Separation of compute and storage | Scale each independently |
| Built-in ML | Create machine learning models with SQL (BigQuery ML) |
A dataset is a container for tables, views, and routines. Datasets belong to a project and are located in a specific region.
Tables hold your data in rows and columns. BigQuery supports:
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