A healthcare analytics team uses Azure Databricks to process patient records. The data contains inconsistent date formats, null values in critical fields, and some duplicate patient IDs. You need to cleanse the data before loading it into a curated layer. What should you do?

Use Spark SQL to cast all date columns to string and leave nulls as-is to preserve data.

Use Spark DataFrames to parse dates with a consistent format, drop rows with null critical fields, and deduplicate by patient ID keeping the latest record.

Use a UDF to parse dates and then write the data without handling nulls or duplicates.

Use the dropDuplicates function on all columns to remove any row that is an exact duplicate.

What does 'shredding' JSON data mean in the context of data processing?

Splitting JSON data into multiple files

Encrypting JSON data to protect it

Compressing JSON data to reduce size

Extracting nested fields into a flat, tabular structure

What is the primary role of Azure Synapse Pipelines in a data processing workflow?

To visualize data in dashboards

To orchestrate data movement and transformation activities

To store data in a columnar format

To provide a machine learning model training environment

Which of the following is a valid approach to handle missing data?

Ignoring the missing values and not documenting them

Replacing missing values with the maximum value in the column

Converting missing values to text strings

Removing rows with missing values if the proportion is small

Microsoft Certified:Azure Data Engineer Associate

Domain 2Objective 1

Ingest and Transform Data DP-203 Practice Questions (Page 3)

Part of the Develop data processing domain, which accounts for 40–45% of the DP-203 exam. Microsoft does not publish an official question count, but from its 100-minute exam (~40–65 total, ~16–29 in this domain), expect 4–7 from this objective — we provide 57 practice questions to prepare you well beyond it. (estimate)

57questions here

12free pages

18concepts

40–45%of the exam

Questions 11–15

11application · medium
A healthcare analytics team uses Azure Databricks to process patient records. The data contains inconsistent date formats, null values in critical fields, and some duplicate patient IDs. You need to cleanse the data before loading it into a curated layer. What should you do?
Select an answer first
12foundation · easy
What does 'shredding' JSON data mean in the context of data processing?
Select an answer first
13foundation · easy
What is the primary role of Azure Synapse Pipelines in a data processing workflow?
Select an answer first
14foundation · easy
Which of the following is a valid approach to handle missing data?
Select an answer first
15foundation · easy
Which component within an Azure Synapse Pipeline defines a unit of work, such as a data copy or a stored procedure execution?
Select an answer first

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