DP-203 Exam Dumps : Data Engineering on Microsoft Azure

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 into Table1 and azure Data Lake Storage Gen2 container named container1.

You plan to insert data from the files 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: In an Azure Synapse Analytics pipeline, you use a Get Metadata activity that retrieves the DateTime of the files.

Does this meet the goal?

What should you recommend using to secure sensitive customer contact information?

You are designing an Azure Data Lake Storage solution that will transform raw JSON files for use in an analytical workload.

You need to recommend a format for the transformed files. The solution must meet the following requirements:

Contain information about the data types of each column in the files.

Support querying a subset of columns in the files.

Support read-heavy analytical workloads.

Minimize the file size.

What should you recommend?