This page introduces the expect_column_values_to_be_of_type
test from the dbt-expectations package, which verifies that the data type of values in a specified column matches the expected data type. This test is vital for ensuring that data adheres to the schema requirements and for preventing errors in data processing that can arise from type mismatches.
How it Works
The expect_column_values_to_be_of_type
test checks that every entry within a selected column adheres to a designated data type. Ensuring the correct type within a column is crucial for the integrity and reliability of downstream processes such as calculations, reporting, and data integration.
Steps and Conditions:
- Column and Data Type Specification: The specific column to be tested is identified, and the expected data type is defined, such as
integer
,text
,boolean
, etc. - Data Type Validation: Each entry in the targeted column is checked to confirm that it matches the specified data type.
- Outcome:
- Pass: If all values in the column conform to the designated data type, the test passes, validating the column’s data type adherence.
- Fail: If any value in the column does not match the expected data type, the test fails, indicating a potential issue with data integrity or processing errors that need resolution.
Example Usage: Fintech
For a Fintech company managing financial transactions, maintaining the correct data type for each column in their databases is crucial to ensuring accurate data processing. Columns with monetary values, dates, or unique identifiers must have their data types strictly enforced to prevent calculation errors, misreporting, or system crashes.
Consider a scenario where a transactions
table includes a transaction_date
column that is expected to hold values only of the date type because dates are often involved in calculating durations or determining the sequencing of transactions.
In this example, applying the expect_column_values_to_be_of_type
test ensures that the transaction_date
column contains only date entries, preventing errors from operations such as sorting transactions chronologically or generating monthly financial reports.