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TRY_TO_DATE

As explained in Snowflake Data Engineering

TRY_TO_DATE is a Snowflake conversion function that returns a date when conversion succeeds and NULL when it fails.

TRY_TO_DATE converts input to a date when possible and returns NULL instead of an error when the value does not match the date type. This protects ingestion pipelines from invalid source dates. section 4.2

Protecting a JSON ingestion query

Replace a strict cast such as customer_orders:"Order date"::date with TRY_TO_DATE(customer_orders:"Order date") when source values may contain invalid dates. Valid values become dates; invalid values become NULL, allowing ingestion to continue. section 4.2

Listing 4.2 Selecting values from keys at the highest level of the hierarchy
select 
  customer_orders:"Customer"::varchar as customer, 
  customer_orders:"Order date"::date as order_date, 
  customer_orders:"Orders"
from ORDERS_PARK_INN_RAW_STG;

Compare the strict ::date conversion used for the highest-level Order date field with the error-handling alternative. section 4.2

How Snowflake Data Engineering covers it

How deep it goes
Explains successful conversion and NULL-on-failure behavior, but does not detail date-format rules or validation workflows.
Examples
Uses an Order date extracted from JSON and contrasts strict ::date conversion with error-handling conversion.
What it assumes
Assumes familiarity with Snowflake SQL, JSON key extraction, and basic data type conversion.
What you can do after
Apply TRY_TO_DATE to keep ingestion running when source date values fail conversion.
How it connects
Connects date conversion with JSON, VARIANT values, data ingestion, and relational-table transformations.
Cover of Snowflake Data Engineering
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Related concepts

This explainer was generated by Manning's knowledge graph from the text of Snowflake Data Engineering. The section links point to the parts of the book it draws on.