Free Access Snowflake.DEA-C01.v2026-09-04.q215 Practice Test (Page 43)

Question 206

A company is developing machine learning (ML) models. A data engineer needs to apply data quality rules to training data. The company stores the training data in an Amazon S3 bucket.
Which solution will meet these requirements with the LEAST operational overhead?

A.Create an AWS Lambda function to check data quality and to raise exceptions in the code. Run the function when data is added to the S3 bucket. Create an Amazon CloudWatch alarm for exceptions in the code.

B.Create an AWS Glue DataBrew project for the data in the S3 bucket. Create a ruleset for the data quality rules. Create a profile job to run the data quality rules. Use Amazon EventBridge to run the profile job when data is added to the S3 bucket.

C.Create an Amazon EMR provisioned cluster. Add a Python open source data quality package to the EMR cluster. Use the Python package to write code for data quality rules and to copy the data from the S3 bucket to the EMR cluster. Copy the data from the S3 bucket to the EMR cluster. Run the data quality rules.

D.Create AWS Lambda functions to evaluate data quality rules. Use AWS Step Functions to orchestrate a workflow that publishes notifications when the data fails to meet data quality rules.

Question 207

A company uses Amazon DataZone as a data governance and business catalog solution. The company stores data in an Amazon S3 data lake. The company uses AWS Glue with an AWS Glue Data Catalog.
A data engineer needs to publish AWS Glue Data Quality scores to the Amazon DataZone portal.
Which solution will meet this requirement?

A.Create a data quality ruleset with Data Quality Definition language (DQDL) rules that apply to a specific AWS Glue table. Schedule the ruleset to run daily. Configure the Amazon DataZone project to have an Amazon Redshift data source. Enable the data quality configuration for the data source.

B.Create a data quality ruleset with Data Quality Definition language (DQDL) rules that apply to a specific AWS Glue table. Schedule the ruleset to run daily. Configure the Amazon DataZone project to have an AWS Glue data source. Enable the data quality configuration for the data source.

C.Configure AWS Glue ETL jobs to use an Evaluate Data Quality transform. Define a data quality ruleset inside the jobs. Configure the Amazon DataZone project to have an Amazon Redshift data source. Enable the data quality configuration for the data source.

D.Configure AWS Glue ETL jobs to use an Evaluate Data Quality transform. Define a data quality ruleset inside the jobs. Configure the Amazon DataZone project to have an AWS Glue data source. Enable the data quality configuration for the data source.

Question 208

Snowflake does not treat the inner transaction as nested; instead, the inner transaction is a separate transaction.
What is term used to call these Transaction?

A.Inner Transaction

B.Nested Scope Transaction

C.Atomic Transaction

D.Scoped transactions

E.Enclosed Transaction

Question 209

A company is building a data lake for a new analytics team. The company is using Amazon S3 for storage and Amazon Athena for query analysis. All data that is in Amazon S3 is in Apache Parquet format.
The company is running a new Oracle database as a source system in the company's data center. The company has 70 tables in the Oracle database. All the tables have primary keys.
Data can occasionally change in the source system. The company wants to ingest the tables every day into the data lake.
Which solution will meet this requirement with the LEAST effort?

A.Create an Apache Sqoop job in Amazon EMR to read the data from the Oracle database.
Configure the Sqoop job to write the data to Amazon S3 in Parquet format.

B.Create an AWS Glue connection to the Oracle database. Create an AWS Glue bookmark job to ingest the data incrementally and to write the data to Amazon S3 in Parquet format.

C.Create an AWS Database Migration Service (AWS DMS) task for ongoing replication. Set the Oracle database as the source. Set Amazon S3 as the target. Configure the task to write the data in Parquet format.

D.Create an Oracle database in Amazon RDS. Use AWS Database Migration Service (AWS DMS) to migrate the on-premises Oracle database to Amazon RDS. Configure triggers on the tables to invoke AWS Lambda functions to write changed records to Amazon S3 in Parquet format.

Question 210

A company utilizes AWS Glue for ETL (Extract, Transform, Load) jobs to process large volumes of data stored in Amazon S3. Recently, they have been experiencing performance issues with their Glue jobs, resulting in longer processing times and delays in data delivery. Upon investigation, they found that the bottleneck occurred during data extraction from S3. Which of the following could be the potential cause of this performance issue?

A.The Glue job's configuration lacks optimization for parallelism, causing inefficient data extraction from S3, leading to longer processing times.

B.The underlying network bandwidth between AWS Glue and Amazon S3 is insufficient, causing slow data transfer rates and impacting job performance.

C.There are issues with the IAM (Identity and Access Management) roles associated with the Glue job, leading to permission errors or delays in accessing S3 data.

D.The size and structure of the S3 data files are causing overhead during data extraction, resulting in longer processing times for Glue jobs.

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