Implement and Manage Data Quality Constraints in Unity Catalog DP-750 Practice Questions (Page 7)

Questions 31–33

1. 31expert · hard

   A financial data platform has a `trades` table with a strict schema. A new regulatory requirement mandates adding a `trader_id` column, but the team is concerned about breaking existing downstream reports that do not expect the new column. They also need to ensure that the new column does not contain nulls for all future writes. The table currently has millions of rows. What is the best approach?

   • AAdd the `trader_id` column with `ALTER TABLE ... ADD COLUMNS`, then add a CHECK constraint `trader_id IS NOT NULL`.
   • BUse a Lakeflow pipeline with an expectation that `trader_id` is not null, and set `onViolation` to 'warn'.
   • CDrop and recreate the table with the new schema and backfill all historical data.
   • DEnable schema enforcement and rely on it to reject writes that do not include `trader_id`.
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2. 32foundation · easy

   In Databricks, which function can be used to check if a value can be cast to a specified data type?

   • Atry_cast
   • Bisnull
   • Ctypeof
   • Dcast
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3. 33expert · hard

   A retail company has a `products` table with a schema that includes `product_id`, `name`, and `price`. A new source system sends data with an extra `color` column and also sends `product_id` as a string instead of an integer. The team wants to accept the `color` column but reject the `product_id` type change. They are using a Lakeflow pipeline. What is the best approach?

   • AEnable schema evolution in the pipeline to add the `color` column, and add an expectation that `product_id` is an integer, with `onViolation = 'fail'`.
   • BSet the table property `delta.columnMapping.mode` to 'name' to allow both changes.
   • CDisable schema enforcement and use a `MERGE` to add the `color` column and cast `product_id` to integer.
   • DUse a CHECK constraint on `product_id` to enforce it is an integer.
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