Databricks Certified Data Analyst Associate free question 1 / 10 · Domain 1: Understanding of Databricks Data Intelligence Platform (Lakehouse Platform)
A team has several pipelines that were written for Delta Live Tables (DLT) before the product was renamed. The Exam Guide now lists the component as Lakeflow Declarative Pipelines (DeltaLive tables). What does the documentation say about the existing pipeline code?
- It has to be converted with a migration tool before its next update runs.
- It must be rewritten as Lakeflow Jobs tasks, since DLT was merged into Jobs.
- It runs only on classic compute until the import statements are changed.
- It keeps working as it is; renaming the APIs is optional and recommended.
Show the answer and explanation
Answer: D
Why this is correct
The documentation page "What happened to Delta Live Tables (DLT)?" says the product formerly known as DLT has been updated to Lakeflow pipelines, and that if you have previously used DLT there is no migration required: your code will still work. In Python, import dlt can be replaced with from pyspark import pipelines as dp, with matching decorator changes, but these are recommended changes rather than requirements. The pipelines are built on Apache Spark Declarative Pipelines and run on the Databricks Runtime, so the rename reflects that open framework.
Why the other options are wrong
"It has to be converted with a migration tool before its next update runs." … The page states the opposite: there is no migration required to use Lakeflow pipelines. The changes it describes are ones you can make to take better advantage of the product and to gain compatibility with Apache Spark Declarative Pipelines, not a required conversion step.
"It must be rewritten as Lakeflow Jobs tasks, since DLT was merged into Jobs." … The rename page describes Lakeflow pipelines as built on Apache Spark Declarative Pipelines, a declarative framework for batch and streaming pipelines, and lists only Python name changes. Lakeflow Jobs remains a separate product for workflow automation, so nothing asks for pipelines to be rebuilt as jobs.
"It runs only on classic compute until the import statements are changed." … The page does not tie the old names to a compute type. It says Python APIs that used dlt in the name can still be used; only the classic SKUs keep the DLT prefix, which is a billing name and not a limit on where code can run.
Names you will see side by side
The Exam Guide writes Lakeflow Declarative Pipelines (DeltaLive tables), while the current documentation says Spark Declarative Pipelines on Lakeflow or Lakeflow pipelines. Some DLT names also remain on purpose, such as event log schemas with dlt in the name. Treat all of these as the same component: a declarative framework for batch and streaming pipelines in SQL and Python.