BigQuery Data Types
BigQuery Data Types
BigQuery offers a variety of data types to accommodate different types of data. The common data types supported in BigQuery include INTEGER for whole numbers, FLOAT for decimal numbers, BOOLEAN for true/false values, STRING for text, TIMESTAMP for date and time values, and ARRAY for lists of data, among others. These data types allow users to store and manipulate data efficiently within BigQuery, making it a powerful tool for data analysis and querying tasks.
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- BigQuery data types are used to define the type of data that can be stored in a column within a BigQuery table.
- - The data types in BigQuery include simple types like INTEGER, FLOAT, BOOLEAN, STRING, and TIMESTAMP.
- - BigQuery also supports complex types like RECORD (structs), ARRAY, and GEOGRAPHY.
- - INTEGER data type is used for storing whole numbers, FLOAT for decimal numbers, BOOLEAN for true/false values, and STRING for text data.
- - TIMESTAMP data type is used for storing dates and times in UTC format.
- - RECORD data type is used to create nested structures allowing for organizing data in a hierarchical manner.
- - ARRAY data type allows storing lists of values within a single column.
- - GEOGRAPHY data type is used for representing geographical locations and shapes.
- - Understanding the different data types in BigQuery is essential for efficient data storage and querying operations.
- - By offering a training program on BigQuery data types, students can learn how to effectively structure and analyze data within BigQuery tables.
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