A data engineer needs to build an enterprise data catalog based on the company's Amazon S3 buckets and Amazon RDS databases. The data catalog must include storage format metadata for the data in the catalog.
Which solution will meet these requirements with the LEAST effort?
A. Use an AWS Glue crawler to scan the S3 buckets and RDS databases and build a data catalog. Use data stewards to inspect the data and update the data catalog with the data format.
B. Use an AWS Glue crawler to build a data catalog. Use AWS Glue crawler classifiers to recognize the format of data and store the format in the catalog.
C. Use Amazon Macie to build a data catalog and to identify sensitive data elements. Collect the data format information from Macie.
D. Use scripts to scan data elements and to assign data classifications based on the format of the data.
Show Answer
Correct Answer: B
Explanation: AWS Glue crawlers can scan Amazon S3 and supported Amazon RDS data stores to populate the AWS Glue Data Catalog. Glue classifiers automatically detect storage formats (such as CSV, JSON, Parquet, Avro, etc.) and store the detected metadata in the catalog, minimizing manual effort. Amazon Macie is for sensitive data discovery rather than building a data catalog, and custom scripts or manual stewardship require more effort.
Question 133
A financial company recently added more features to its mobile app. The new features required the company to create a new topic in an existing Amazon Managed Streaming for Apache Kafka (Amazon MSK) cluster.
A few days after the company added the new topic, Amazon CloudWatch raised an alarm on the RootDiskUsed metric for the MSK cluster.
How should the company address the CloudWatch alarm?
A. Expand the storage of the MSK broker. Configure the MSK cluster storage to expand automatically.
B. Expand the storage of the Apache ZooKeeper nodes.
C. Update the MSK broker instance to a larger instance type. Restart the MSK cluster.
D. Specify the Target Volume-in-GiB parameter for the existing topic.
Show Answer
Correct Answer: A
Explanation: The RootDiskUsed CloudWatch metric reflects root disk utilization on MSK brokers. If broker storage usage is approaching capacity after adding a new topic, the appropriate remediation is to expand broker storage and enable automatic storage scaling to prevent future capacity issues. ZooKeeper storage is unrelated to broker log storage, changing broker instance size does not directly increase EBS storage, and topic configuration does not use a Target Volume-in-GiB parameter.
Question 134
A company uses AWS Glue Data Catalog to index data that is uploaded to an Amazon S3 bucket every day. The company uses a daily batch processes in an extract, transform, and load (ETL) pipeline to upload data from external sources into the S3 bucket.
The company runs a daily report on the S3 data. Some days, the company runs the report before all the daily data has been uploaded to the S3 bucket. A data engineer must be able to send a message that identifies any incomplete data to an existing Amazon Simple Notification Service (Amazon SNS) topic.
Which solution will meet this requirement with the LEAST operational overhead?
A. Create data quality checks for the source datasets that the daily reports use. Create a new AWS managed Apache Airflow cluster. Run the data quality checks by using Airflow tasks that run data quality queries on the columns data type and the presence of null values. Configure Airflow Directed Acyclic Graphs (DAGs) to send an email notification that informs the data engineer about the incomplete datasets to the SNS topic.
B. Create data quality checks on the source datasets that the daily reports use. Create a new Amazon EMR cluster. Use Apache Spark SQL to create Apache Spark jobs in the EMR cluster that run data quality queries on the columns data type and the presence of null values. Orchestrate the ETL pipeline by using an AWS Step Functions workflow. Configure the workflow to send an email notification that informs the data engineer about the incomplete datasets to the SNS topic.
C. Create data quality checks on the source datasets that the daily reports use. Create data quality actions by using AWS Glue workflows to confirm the completeness and consistency of the datasets. Configure the data quality actions to create an event in Amazon EventBridge if a dataset is incomplete. Configure EventBridge to send the event that informs the data engineer about the incomplete datasets to the Amazon SNS topic.
D. Create AWS Lambda functions that run data quality queries on the columns data type and the presence of null values. Orchestrate the ETL pipeline by using an AWS Step Functions workflow that runs the Lambda functions. Configure the Step Functions workflow to send an email notification that informs the data engineer about the incomplete datasets to the SNS topic.
Show Answer
Correct Answer: C
Explanation: AWS Glue Data Quality integrates directly with the AWS Glue Data Catalog and Glue workflows to evaluate dataset quality, including completeness and consistency. It can emit events to Amazon EventBridge when data quality evaluations fail, and EventBridge can route those events to an existing Amazon SNS topic with minimal operational overhead. The other options require managing additional infrastructure such as MWAA, EMR, Lambda, or Step Functions.
Question 135
A data engineer needs to onboard a new data producer into AWS. The data producer needs to migrate data products to AWS.
The data producer maintains many data pipelines that support a business application. Each pipeline must have service accounts and their corresponding credentials. The data engineer must establish a secure connection from the data producer's on-premises data center to AWS. The data engineer must not use the public internet to transfer data from an on-premises data center to AWS.
Which solution will meet these requirements?
A. Instruct the new data producer to create Amazon Machine Images (AMIs) on Amazon Elastic Container Service (Amazon ECS) to store the code base of the application. Create security groups in a public subnet that allow connections only to the on-premises data center.
B. Create an AWS Direct Connect connection to the on-premises data center. Store the service account credentials in AWS Secrets manager.
C. Create a security group in a public subnet. Configure the security group to allow only connections from the CIDR blocks that correspond to the data producer. Create Amazon S3 buckets than contain presigned URLS that have one-day expiration dates.
D. Create an AWS Direct Connect connection to the on-premises data center. Store the application keys in AWS Secrets Manager. Create Amazon S3 buckets that contain presigned URLS that have one-day expiration dates.
Show Answer
Correct Answer: B
Explanation: AWS Direct Connect provides a private network connection from the on-premises data center to AWS without using the public internet. AWS Secrets Manager is the appropriate service to securely store and manage service account credentials. The other options either rely on public internet mechanisms (such as presigned URLs), misuse AWS services, or do not address the credential management requirement.
Question 136
A retail company is expanding its operations globally. The company needs to use Amazon QuickSight to accurately calculate currency exchange rates for financial reports. The company has an existing dashboard that includes a visual that is based on an analysis of a dataset that contains global currency values and exchange rates.
A data engineer needs to ensure that exchange rates are calculated with a precision of four decimal places. The calculations must be precomputed. The data engineer must materialize results in QuickSight super-fast, parallel, in-memory calculation engine (SPICE).
Which solution will meet these requirements?
A. Define and create the calculated field in the dataset.
B. Define and create the calculated field in the analysis.
C. Define and create the calculated field in the visual.
D. Define and create the calculated field in the dashboard.
Show Answer
Correct Answer: A
Explanation: Calculated fields created at the dataset level are computed during dataset ingestion/refresh and stored in SPICE, allowing precomputed, materialized results. Calculated fields created in an analysis are evaluated at query time, and visuals or dashboards do not define SPICE-materialized calculated fields. Dataset-level calculations also allow controlling numeric precision such as four decimal places before analysis.
Question 137
An ecommerce company operates a complex order fulfilment process that spans several operational systems hosted in AWS. Each of the operational systems has a Java Database
Connectivity (JDBC)-compliant relational database where the latest processing state is captured.
The company needs to give an operations team the ability to track orders on an hourly basis across the entire fulfillment process.
Which solution will meet these requirements with the LEAST development overhead?
A. Use AWS Glue to build ingestion pipelines from the operational systems into Amazon Redshift Build dashboards in Amazon QuickSight that track the orders.
B. Use AWS Glue to build ingestion pipelines from the operational systems into Amazon DynamoDBuild dashboards in Amazon QuickSight that track the orders.
C. Use AWS Database Migration Service (AWS DMS) to capture changed records in the operational systems. Publish the changes to an Amazon DynamoDB table in a different AWS region from the source database. Build Grafana dashboards that track the orders.
D. Use AWS Database Migration Service (AWS DMS) to capture changed records in the operational systems. Publish the changes to an Amazon DynamoDB table in a different AWS region from the source database. Build Amazon QuickSight dashboards that track the orders.
Show Answer
Correct Answer: A
Explanation: AWS Glue can connect directly to multiple JDBC-compliant relational databases and load the data into Amazon Redshift, which is purpose-built for analytics across relational datasets. Amazon QuickSight integrates natively with Redshift for dashboards. The DynamoDB options introduce unnecessary data modeling complexity for analytical reporting, and the DMS options target DynamoDB rather than an analytical data store, making them a poorer fit for cross-system reporting.
Question 138
A company has a gaming application that stores data in Amazon DynamoDB tables. A data engineer needs to ingest the game data into an Amazon OpenSearch Service cluster. Data updates must occur in near real time.
Which solution will meet these requirements?
A. Use AWS Step Functions to periodically export data from the Amazon DynamoDB tables to an Amazon S3 bucket. Use an AWS Lambda function to load the data into Amazon OpenSearch Service.
B. Configure an AWS Glue job to have a source of Amazon DynamoDB and a destination of Amazon OpenSearch Service to transfer data in near real time.
C. Use Amazon DynamoDB Streams to capture table changes. Use an AWS Lambda function to process and update the data in Amazon OpenSearch Service.
D. Use a custom OpenSearch plugin to sync data from the Amazon DynamoDB tables.
Show Answer
Correct Answer: C
Explanation: Amazon DynamoDB Streams provides near real-time change data capture for item-level inserts, updates, and deletes. An AWS Lambda function can be triggered by the stream to transform and index the changed records into Amazon OpenSearch Service, providing near real-time synchronization. The other options are either batch-oriented (Step Functions with exports, AWS Glue jobs) or rely on a custom plugin that is not the standard managed integration.
Question 139
A company has an application that uses a microservice architecture. The company hosts the application on an Amazon Elastic Kubernetes Services (Amazon EKS) cluster.
The company wants to set up a robust monitoring system for the application. The company needs to analyze the logs from the EKS cluster and the application. The company needs to correlate the cluster's logs with the application's traces to identify points of failure in the whole application request flow.
Which combination of steps will meet these requirements with the LEAST development effort? (Choose two.)
A. Use FluentBit to collect logs. Use OpenTelemetry to collect traces.
B. Use Amazon CloudWatch to collect logs. Use Amazon Kinesis to collect traces.
C. Use Amazon CloudWatch to collect logs. Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to collect traces.
D. Use Amazon OpenSearch to correlate the logs and traces.
E. Use AWS Glue to correlate the logs and traces.
Show Answer
Correct Answer: A, D
Explanation: Fluent Bit is the standard lightweight log collector for Amazon EKS and OpenTelemetry is the recommended open standard for collecting distributed traces with minimal instrumentation effort. Amazon OpenSearch Service supports observability features that correlate logs and traces, enabling end-to-end request flow analysis across microservices. Kinesis, MSK, and AWS Glue are not trace collection/correlation services for this use case.
Question 140
A company has a data lake in Amazon S3. The company uses AWS Glue to catalog data and AWS Glue Studio to implement data extract, transform, and load (ETL) pipelines.
The company needs to ensure that data quality issues are checked every time the pipelines run. A data engineer must enhance the existing pipelines to evaluate data quality rules based on predefined thresholds.
Which solution will meet these requirements with the LEAST implementation effort?
A. Add a new transform that is defined by a SQL query to each Glue ETL job. Use the SQL query to implement a ruleset that includes the data quality rules that need to be evaluated.
B. Add a new Evaluate Data Quality transform to each Glue ETL job. Use Data Quality Definition Language (DQDL) to implement a ruleset that includes the data quality rules that need to be evaluated.
C. Add a new custom transform to each Glue ETL job. Use the PyDeequ library to implement a ruleset that includes the data quality rules that need to be evaluated.
D. Add a new custom transform to each Glue ETL job. Use the Great Expectations library to implement a ruleset that includes the data quality rules that need to be evaluated.
Show Answer
Correct Answer: B
Explanation: AWS Glue has a built-in Evaluate Data Quality transform that integrates directly into AWS Glue Studio ETL jobs. It uses Data Quality Definition Language (DQDL) to define and evaluate data quality rules against predefined thresholds on every pipeline run, requiring the least implementation effort compared to writing SQL rules or integrating external libraries such as PyDeequ or Great Expectations.
Question 141
A company stores customer records in Amazon S3. The company must not delete or modify the customer record data for 7 years after each record is created. The root user also must not have the ability to delete or modify the data.
A data engineer wants to use S3 Object Lock to secure the data.
Which solution will meet these requirements?
A. Enable governance mode on the S3 bucket. Use a default retention period of 7 years.
B. Enable compliance mode on the S3 bucket. Use a default retention period of 7 years.
C. Place a legal hold on individual objects in the S3 bucket. Set the retention period to 7 years.
D. Set the retention period for individual objects in the S3 bucket to 7 years.
Show Answer
Correct Answer: B
Explanation: S3 Object Lock compliance mode prevents object versions from being overwritten or deleted by any user, including the AWS account root user, until the retention period expires. A default retention period of 7 years ensures newly created objects are automatically protected for the required duration.
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