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BigQuery#

BigQuery is a powerful SQL-based data warehouse that allows you to process, load, and analyze large datasets efficiently using SQL queries.

Why Use BigQuery?#

  • Quickly preprocess and explore large datasets using SQL-like query.
  • Simplifies aggregation, feature extraction, and preparation for ML models.
  • You can directly load data from a GCS bucket into an SQL-based data warehouse (BigQuery). It supports all types of data — structured, semi-structured, and unstructured; including tsv, csv, parquet, avro, xlsx, and many more.
  • To use BigQuery with a client library, please follow this link for detailed guide.

Setting Up and Using BigQuery#

Ensure that you have completed How to Use GCP before starting this process.

Loading Data into BigQuery#

  • From GCS:

    bq load --source_format=CSV <DATASET_NAME>.<TABLE_NAME> gs://<BUCKET_NAME>/<FILE_NAME>

Querying Data#

  • Use BigQuery's web interface or CLI to run SQL queries for data cleaning, feature engineering, and exploratory analysis.

  • Example:

    SELECT * FROM `project_id.dataset_name.table_name` LIMIT 10;

Follow the instructions on this page to learn more about BigQuery.