From the course: Build a No-Code ETL Pipeline with Google BigQuery
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How data is organized in SQL - BigQuery Tutorial
From the course: Build a No-Code ETL Pipeline with Google BigQuery
How data is organized in SQL
- [Instructor] To build effective data pipelines, you need a solid understanding of how data is organized and structured in SQL. When you think of business data, your mind might jump to spreadsheets, like Google Sheets or Excel, simple rows and columns where each cell can contain any type of data. But with SQL, data is structured in a much more systematic way, providing reliability, efficiency, and scalability. The key to SQL's reliability is the schema. A schema defines the structure of a table. It specifies the names of the columns and the data type of each column. This ensures data consistency and integrity, preventing errors that can happen when working with unstructured data. And here are the main data types in SQL. On the left column of this table, you see the name of the type in BigQuery, and on the right you see what that type is meant to contain. So a STRING column is meant to contain text. An INT64 column is expected to contain whole numbers, whereas the DECIMAL column is…
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