You have an Azure Synapse Analytics pipeline named pipeline1 that has concurrency set to 1.

To run pipeline 1, you create a new trigger as shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the [graphic.

NOTE: Each correct selection is worth one point.

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You have an Azure Synapse Analytics dedicated SQL pool that contains a table named Table1.

You have files that are ingested and loaded into an Azure Data Lake Storage Gen2 container named container1.

You plan to insert data from the files in container1 into Table1 and transform the data. Each row of data in the files will produce one row in the serving layer of Table1.

You need to ensure that when the source data files are loaded to container1, the DateTime is stored as an additional column in Table1.

Solution: You use an Azure Synapse Analytics serverless SQL pool to create an external table that has an additional DateTime column.

Does this meet the goal?

You have an Azure Databricks workspace and an Azure Data Lake Storage Gen2 account named storage!

New files are uploaded daily to storage1.

• Incrementally process new files as they are upkorage1 as a structured streaming source. The solution must meet the following requirements:

• Minimize implementation and maintenance effort.

• Minimize the cost of processing millions of files.

• Support schema inference and schema drift.

Which should you include in the recommendation?