A utility company processes meter readings using Apache Spark in Azure Synapse Analytics. Some readings have missing values for the consumption column. You need to fill these missing values with the average consumption for the same meter type and day. What should you do?

Drop all rows with missing consumption values.

Use the imputer function from Spark MLlib to fill missing values with the mean of the entire column.

Use the fillna function with a constant value of 0.

Use a window function partitioned by meter type and day to calculate the average, then use coalesce to replace nulls.

A finance company stores transaction data in Azure Synapse Analytics. Analysts frequently run queries that join a large fact table with several dimension tables. The queries are slow because of the number of joins. You need to improve query performance by reducing the number of joins while maintaining data accuracy. What should you do?

Use a T-SQL query that performs the joins at runtime without any pre-aggregation.

Create a materialized view that pre-joins the fact and dimension tables and is refreshed automatically.

Create a non-clustered index on each foreign key column in the fact table.

Normalize the fact table further by splitting it into multiple smaller tables.

A telecommunications company uses Azure Stream Analytics to process call detail records (CDRs) from a Kafka cluster. The CDRs are encoded in Avro format. The company requires that each CDR is processed exactly once, even if the source produces duplicates. You need to configure the Stream Analytics job to handle this. What should you do?

Use a JavaScript UDF to decode the Avro data and then use a GROUP BY on the CDR ID.

Use an input with Avro serialization and enable 'Exactly Once' delivery in the job settings.

Use an Event Hub input and set the partition key to the CDR ID.

Use a reference data input to filter out duplicates before processing.

What is the primary purpose of Azure Data Factory (ADF)?

To host web applications in the cloud

To provide a fully managed relational database service

To create and manage data integration pipelines that ingest and transform data from various sources

To offer a big data analytics engine for interactive queries

Microsoft Certified:Azure Data Engineer Associate

Domain 2Objective 1

Ingest and Transform Data DP-203 Practice Questions (Page 4)

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 16–20

16foundation · easy
Which of the following is a core abstraction in Apache Spark that represents a distributed collection of data?
Select an answer first
17application · medium
A utility company processes meter readings using Apache Spark in Azure Synapse Analytics. Some readings have missing values for the consumption column. You need to fill these missing values with the average consumption for the same meter type and day. What should you do?
Select an answer first
18application · medium
A finance company stores transaction data in Azure Synapse Analytics. Analysts frequently run queries that join a large fact table with several dimension tables. The queries are slow because of the number of joins. You need to improve query performance by reducing the number of joins while maintaining data accuracy. What should you do?
Select an answer first
19application · medium
A telecommunications company uses Azure Stream Analytics to process call detail records (CDRs) from a Kafka cluster. The CDRs are encoded in Avro format. The company requires that each CDR is processed exactly once, even if the source produces duplicates. You need to configure the Stream Analytics job to handle this. What should you do?
Select an answer first
20foundation · easy
What is the primary purpose of Azure Data Factory (ADF)?
Select an answer first

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Ingest and Transform Data DP-203 Practice Questions (Page 4)

Questions 16–20

Which of the following is a core abstraction in Apache Spark that represents a distributed collection of data?

A utility company processes meter readings using Apache Spark in Azure Synapse Analytics. Some readings have missing values for the consumption column. You need to fill these missing values with the average consumption for the same meter type and day. What should you do?

What is the primary purpose of Azure Data Factory (ADF)?

Keep studying — Develop data processing