Free AWS DEA-C01 Practice Questions & Answers 2026 Part3

A company uses Amazon RDS to store transactional data. The company runs an RDS DB instance in a private subnet. A developer wrote an AWS Lambda function with default settings to insert, update, or delete data in the DB instance.The developer needs to give the Lambda function the ability to connect to the DB instance privately without using the public internet.Which combination of steps will meet this requirement with the LEAST operational overhead? (Choose two.)

A data engineer needs to create an AWS Lambda function that converts the format of data from .csv to Apache Parquet. The Lambda function must run only if a user uploads a .csv file to an Amazon S3 bucket.Which solution will meet these requirements with the LEAST operational overhead?

A web application generates clickstream events that must be ingested continuously for downstream processing. Which Alibaba Cloud service is most appropriate?

A data engineer must orchestrate a series of Amazon Athena queries that will run every day. Each query can run for more than 15 minutes.Which combination of steps will meet these requirements MOST cost-effectively? (Choose two.)

A company needs to implement a workflow to process transactions. Each transaction goes through multiple levels of validation. Each validation level depends on the preceding validation level.The workflow must either process or reject each transaction within 24 hours. The workflow must run for less than 24 hours total.Which solution will meet these requirements with the LEAST operational cost?

A company wants to implement real-time analytics capabilities. The company wants to use Amazon Kinesis Data Streams and Amazon Redshift to ingest and process streaming data at the rate of several gigabytes per second. The company wants to derive near real-time insights by using existing business intelligence (BI) and analytics tools.Which solution will meet these requirements with the LEAST operational overhead?

A company processes 500 GB of audience and advertising data daily, storing CSV files in Amazon S3 with schemas registered in AWS Glue Data Catalog. They need to convert these files to Apache Parquet format and store them in an S3 bucket. The solution requires a long-running workflow with 15 GiB memory capacity to process the data concurrently, followed by a correlation process that begins only after the first two processes complete. AWS Glue Workflows can coordinate multiple ETL jobs and triggers. They support parallel execution and sequential dependencies, which is ideal for concurrent data processing followed by correlation steps, all with minimal operational overhead. ''Use AWS Glue Workflows to orchestrate multiple ETL jobs in sequence or in parallel, supporting conditional triggers and dependency management.'' -- Ace the AWS Certified Data Engineer - Associate Certification - version 2 - apple.pdf

A company maintains an Amazon Redshift provisioned cluster that the company uses for extract, transform, and load (ETL) operations to support critical analysis tasks. A sales team within the company maintains a Redshift cluster that the sales team uses for business intelligence (BI) tasks.The sales team recently requested access to the data that is in the ETL Redshift cluster so the team can perform weekly summary analysis tasks. The sales team needs to join data from the ETL cluster with data that is in the sales team's BI cluster.The company needs a solution that will share the ETL cluster data with the sales team without interrupting the critical analysis tasks. The solution must minimize usage of the computing resources of the ETL cluster.Which solution will meet these requirements?

A company uses Amazon RDS to store transactional data. The company runs an RDS DB instance in a private subnet. A developer wrote an AWS Lambda function with default settings to insert, update, or delete data in the DB instance.The developer needs to give the Lambda function the ability to connect to the DB instance privately without using the public internet.Which combination of steps will meet this requirement with the LEAST operational overhead? (Choose two.)

A company uses Amazon S3 to store semi-structured data in a transactional data lake. Some of the data files are small, but other data files are tens of terabytes.A data engineer must perform a change data capture (CDC) operation to identify changed data from the data source. The data source sends a full snapshot as a JSON file every day and ingests the changed data into the data lake.Which solution will capture the changed data MOST cost-effectively?

A company uses an Amazon Redshift cluster that runs on RA3 nodes. The company wants to scale read and write capacity to meet demand. A data engineer needs to identify a solution that will turn on concurrency scaling.Which solution will meet this requirement?

A company wants to implement real-time analytics capabilities. The company wants to use Amazon Kinesis Data Streams and Amazon Redshift to ingest and process streaming data at the rate of several gigabytes per second. The company wants to derive near real-time insights by using existing business intelligence (BI) and analytics tools.Which solution will meet these requirements with the LEAST operational overhead?

A data engineer notices slow query performance on a highly partitioned table that is in Amazon Athena. The table contains daily data for the previous 5 years, partitioned by date. The data engineer wants to improve query performance and to automate partition management. Which solution will meet these requirements?

A company is creating a new data pipeline to populate a data lake. A data analyst needs to prepare and standardize the data before a data engineering team can perform advanced data transformations. The data analyst needs a solution to process the data that does not require writing new code.Which solution will meet these requirements with the LEAST operational effort?

A company is building an analytics solution. The solution uses Amazon S3 for data lake storage and Amazon Redshift for a data warehouse. The company wants to use Amazon Redshift Spectrum to query the data that is in Amazon S3.Which actions will provide the FASTEST queries? (Choose two.)

A company is planning to use a provisioned Amazon EMR cluster that runs Apache Spark jobs to perform big data analysis. The company requires high reliability. A big data team must follow best practices for running cost-optimized and long-running workloads on Amazon EMR. The team must find a solution that will maintain the company's current level of performance.Which combination of resources will meet these requirements MOST cost-effectively? (Choose two.)

A company is migrating a legacy application to an Amazon S3 based data lake. A data engineer reviewed data that is associated with the legacy application. The data engineer found that the legacy data contained some duplicate information.The data engineer must identify and remove duplicate information from the legacy application data.Which solution will meet these requirements with the LEAST operational overhead?

A company uses Amazon RDS to store transactional data. The company runs an RDS DB instance in a private subnet. A developer wrote an AWS Lambda function with default settings to insert, update, or delete data in the DB instance.The developer needs to give the Lambda function the ability to connect to the DB instance privately without using the public internet.Which combination of steps will meet this requirement with the LEAST operational overhead? (Choose two.)

A data engineer needs to use AWS Step Functions to design an orchestration workflow. The workflow must parallel process a large collection of data files and apply a specific transformation to each file.Which Step Functions state should the data engineer use to meet these requirements?

A data engineer needs to join data from multiple sources to perform a one-time analysis job. The data is stored in Amazon DynamoDB, Amazon RDS, Amazon Redshift, and Amazon S3.Which solution will meet this requirement MOST cost-effectively?

A company uses Amazon RDS to store transactional data. The company runs an RDS DB instance in a private subnet. A developer wrote an AWS Lambda function with default settings to insert, update, or delete data in the DB instance.The developer needs to give the Lambda function the ability to connect to the DB instance privately without using the public internet.Which combination of steps will meet this requirement with the LEAST operational overhead? (Choose two.)

A company is building an analytics solution. The solution uses Amazon S3 for data lake storage and Amazon Redshift for a data warehouse. The company wants to use Amazon Redshift Spectrum to query the data that is in Amazon S3.Which actions will provide the FASTEST queries? (Choose two.)

A data engineer needs to create an AWS Lambda function that converts the format of data from .csv to Apache Parquet. The Lambda function must run only if a user uploads a .csv file to an Amazon S3 bucket.Which solution will meet these requirements with the LEAST operational overhead?

A company is designing a data lake on Amazon S3. To ensure high performance when accessing the data, which best practice should the company adopt in organizing its data in the S3 bucket?

You have been tasked with migrating an on-premises MySQL database to Amazon Aurora PostgreSQL using AWS Database Migration Service (DMS). The stakeholder emphasizes that the source database must remain fully operational during the migration process.Which of the following statements about DMS is accurate with respect to this scenario?

A data engineer needs to join data from multiple sources to perform a one-time analysis job. The data is stored in Amazon DynamoDB, Amazon RDS, Amazon Redshift, and Amazon S3.Which solution will meet this requirement MOST cost-effectively?

A company is building an analytics solution. The solution uses Amazon S3 for data lake storage and Amazon Redshift for a data warehouse. The company wants to use Amazon Redshift Spectrum to query the data that is in Amazon S3.Which actions will provide the FASTEST queries? (Choose two.)

A company uses Amazon RDS to store transactional data. The company runs an RDS DB instance in a private subnet. A developer wrote an AWS Lambda function with default settings to insert, update, or delete data in the DB instance.The developer needs to give the Lambda function the ability to connect to the DB instance privately without using the public internet.Which combination of steps will meet this requirement with the LEAST operational overhead? (Choose two.)

A data engineer needs to schedule a workflow that runs a set of AWS Glue jobs every day. The data engineer does not require the Glue jobs to run or finish at a specific time.Which solution will run the Glue jobs in the MOST cost-effective way?

A financial company wants to implement a data mesh. The data mesh must support centralized data governance, data analysis, and data access control. The company has decided to use AWS Glue for data catalogs and extract, transform, and load (ETL) operations.Which combination of AWS services will implement a data mesh? (Choose two.)

A data engineer needs to join data from multiple sources to perform a one-time analysis job. The data is stored in Amazon DynamoDB, Amazon RDS, Amazon Redshift, and Amazon S3.Which solution will meet this requirement MOST cost-effectively?

A company is building an analytics solution. The solution uses Amazon S3 for data lake storage and Amazon Redshift for a data warehouse. The company wants to use Amazon Redshift Spectrum to query the data that is in Amazon S3.Which actions will provide the FASTEST queries? (Choose two.)

For evolving schema and high compatibility, which data format should be chosen for downstream analytics?

A company is migrating a legacy application to an Amazon S3 based data lake. A data engineer reviewed data that is associated with the legacy application. The data engineer found that the legacy data contained some duplicate information.The data engineer must identify and remove duplicate information from the legacy application data.Which solution will meet these requirements with the LEAST operational overhead?

A company is migrating a legacy application to an Amazon S3 based data lake. A data engineer reviewed data that is associated with the legacy application. The data engineer found that the legacy data contained some duplicate information.The data engineer must identify and remove duplicate information from the legacy application data.Which solution will meet these requirements with the LEAST operational overhead?

A company is building an analytics solution. The solution uses Amazon S3 for data lake storage and Amazon Redshift for a data warehouse. The company wants to use Amazon Redshift Spectrum to query the data that is in Amazon S3.Which actions will provide the FASTEST queries? (Choose two.)

A company uses Amazon RDS to store transactional data. The company runs an RDS DB instance in a private subnet. A developer wrote an AWS Lambda function with default settings to insert, update, or delete data in the DB instance.The developer needs to give the Lambda function the ability to connect to the DB instance privately without using the public internet.Which combination of steps will meet this requirement with the LEAST operational overhead? (Choose two.)

A company wants to implement real-time analytics capabilities. The company wants to use Amazon Kinesis Data Streams and Amazon Redshift to ingest and process streaming data at the rate of several gigabytes per second. The company wants to derive near real-time insights by using existing business intelligence (BI) and analytics tools.Which solution will meet these requirements with the LEAST operational overhead?

A data engineer is using an AWS Glue ETL job to remove outdated customer records from a table that contains customer account information. The data engineer is using the following SQL command: MERGE INTO accounts t USING monthly_accounts_update s ON t.customer = s.customer WHEN MATCHED THEN DELETE What will happen when the data engineer runs the SQL command? In AWS Glue's SQL implementation (Spark SQL-compatible), the MERGE INTO statement supports conditional actions. The clause WHEN MATCHED THEN DELETE deletes matching records from the target table (accounts) where the join condition is true. ''A MERGE INTO statement can perform updates, inserts, or deletes based on the match condition between source and target tables.'' -- Ace the AWS Certified Data Engineer - Associate Certification - version 2 - apple.pdf

A data engineer needs to create an AWS Lambda function that converts the format of data from .csv to Apache Parquet. The Lambda function must run only if a user uploads a .csv file to an Amazon S3 bucket.Which solution will meet these requirements with the LEAST operational overhead?

A data engineer needs to create an AWS Lambda function that converts the format of data from .csv to Apache Parquet. The Lambda function must run only if a user uploads a .csv file to an Amazon S3 bucket.Which solution will meet these requirements with the LEAST operational overhead?

A company is migrating a legacy application to an Amazon S3 based data lake. A data engineer reviewed data that is associated with the legacy application. The data engineer found that the legacy data contained some duplicate information.The data engineer must identify and remove duplicate information from the legacy application data.Which solution will meet these requirements with the LEAST operational overhead?

A data engineer maintains custom Python scripts that perform a data formatting process that many AWS Lambda functions use. When the data engineer needs to modify the Python scripts, the data engineer must manually update all the Lambda functions.The data engineer requires a less manual way to update the Lambda functions.Which solution will meet this requirement?

What is a characteristic of the use of binding variables in JavaScript stored procedures in Snowflake?

Mark a Data Engineer, looking to implement streams on local views & want to use change tracking metadata for one of its Data Loading use case. Please select the incorrect understanding points of Mark with respect to usage of Streams on Views?

A data engineer needs to deploy a complex pipeline. The stages of the pipeline must be able to run a script. The data engineer must use only fully managed and serverless services in the pipeline. Which solution will meet these requirements?

A company wants to implement real-time analytics capabilities. The company wants to use Amazon Kinesis Data Streams and Amazon Redshift to ingest and process streaming data at the rate of several gigabytes per second. The company wants to derive near real-time insights by using existing business intelligence (BI) and analytics tools.Which solution will meet these requirements with the LEAST operational overhead?

A company uses Amazon Athena for one-time queries against data that is in Amazon S3. The company has several use cases. The company must implement permission controls to separate query processes and access to query history among users, teams, and applications that are in the same AWS account.Which solution will meet these requirements?

A company loads transaction data for each day into Amazon Redshift tables at the end of each day. The company wants to have the ability to track which tables have been loaded and which tables still need to be loaded.A data engineer wants to store the load statuses of Redshift tables in an Amazon DynamoDB table. The data engineer creates an AWS Lambda function to publish the details of the load statuses to DynamoDB.How should the data engineer invoke the Lambda function to write load statuses to the DynamoDB table?

A company created an extract, transform, and load (ETL) data pipeline in AWS Glue. A data engineer must crawl a table that is in Microsoft SQL Server. The data engineer needs to extract, transform, and load the output of the crawl to an Amazon S3 bucket. The data engineer also must orchestrate the data pipeline.Which AWS service or feature will meet these requirements MOST cost-effectively?

To advance the offset of a stream to the current table version without consuming the change data in a DML operation, which of the following operations can be done by Data Engineer? [Select 2]

A data engineer is building a new data pipeline that stores metadata in an Amazon DynamoDB table. The data engineer must ensure that all items that are older than a specified age are removed from the DynamoDB table daily.Which solution will meet this requirement with the LEAST configuration effort?

A company uses an Amazon QuickSight dashboard to monitor usage of one of the company's applications. The company uses AWS Glue jobs to process data for the dashboard. The company stores the data in a single Amazon S3 bucket. The company adds new data every day.A data engineer discovers that dashboard queries are becoming slower over time. The data engineer determines that the root cause of the slowing queries is long-running AWS Glue jobs.Which actions should the data engineer take to improve the performance of the AWS Glue jobs? (Choose two.)

A company is migrating a legacy application to an Amazon S3 based data lake. A data engineer reviewed data that is associated with the legacy application. The data engineer found that the legacy data contained some duplicate information.The data engineer must identify and remove duplicate information from the legacy application data.Which solution will meet these requirements with the LEAST operational overhead?

A company is building an analytics solution. The solution uses Amazon S3 for data lake storage and Amazon Redshift for a data warehouse. The company wants to use Amazon Redshift Spectrum to query the data that is in Amazon S3.Which actions will provide the FASTEST queries? (Choose two.)

A company has a data warehouse in Amazon Redshift. To comply with security regulations, the company needs to log and store all user activities and connection activities for the data warehouse. Which solution will meet these requirements? Problem Analysis: The company must log all user activities and connection activities in Amazon Redshift for security compliance. Key Considerations: Redshift supports audit logging, which can be configured to write logs to an S3 bucket. S3 provides durable, scalable, and cost-effective storage for logs. Solution Analysis: Option A: S3 for Logging Standard approach for storing Redshift logs. Easy to set up and manage with minimal cost. Option B: Amazon EFS EFS is unnecessary for this use case and less cost-efficient than S3. Option C: Aurora MySQL Using a database to store logs increases complexity and cost. Option D: EBS Volume EBS is not a scalable option for log storage compared to S3. Final Recommendation: Enable Redshift audit logging and specify an S3 bucket as the destination. : Amazon Redshift Audit Logging Storing Logs in Amazon S3

A data engineer needs to use AWS Step Functions to design an orchestration workflow. The workflow must parallel process a large collection of data files and apply a specific transformation to each file.Which Step Functions state should the data engineer use to meet these requirements?

A company is planning to use a provisioned Amazon EMR cluster that runs Apache Spark jobs to perform big data analysis. The company requires high reliability. A big data team must follow best practices for running cost-optimized and long-running workloads on Amazon EMR. The team must find a solution that will maintain the company's current level of performance.Which combination of resources will meet these requirements MOST cost-effectively? (Choose two.)

A data engineer needs to use AWS Step Functions to design an orchestration workflow. The workflow must parallel process a large collection of data files and apply a specific transformation to each file.Which Step Functions state should the data engineer use to meet these requirements?

A company uses an on-premises Microsoft SQL Server database to store financial transaction data. The company migrates the transaction data from the on-premises database to AWS at the end of each month. The company has noticed that the cost to migrate data from the on-premises database to an Amazon RDS for SQL Server database has increased recently.The company requires a cost-effective solution to migrate the data to AWS. The solution must cause minimal downtown for the applications that access the database.Which AWS service should the company use to meet these requirements?

A company uses an Amazon QuickSight dashboard to monitor usage of one of the company's applications. The company uses AWS Glue jobs to process data for the dashboard. The company stores the data in a single Amazon S3 bucket. The company adds new data every day.A data engineer discovers that dashboard queries are becoming slower over time. The data engineer determines that the root cause of the slowing queries is long-running AWS Glue jobs.Which actions should the data engineer take to improve the performance of the AWS Glue jobs? (Choose two.)

A data engineer is configuring an AWS Glue job to read data from an Amazon S3 bucket. The data engineer has set up the necessary AWS Glue connection details and an associated IAM role. However, when the data engineer attempts to run the AWS Glue job, the data engineer receives an error message that indicates that there are problems with the Amazon S3 VPC gateway endpoint.The data engineer must resolve the error and connect the AWS Glue job to the S3 bucket.Which solution will meet this requirement?

A company is building an analytics solution. The solution uses Amazon S3 for data lake storage and Amazon Redshift for a data warehouse. The company wants to use Amazon Redshift Spectrum to query the data that is in Amazon S3.Which actions will provide the FASTEST queries? (Choose two.)

A company is planning to use a provisioned Amazon EMR cluster that runs Apache Spark jobs to perform big data analysis. The company requires high reliability. A big data team must follow best practices for running cost-optimized and long-running workloads on Amazon EMR. The team must find a solution that will maintain the company's current level of performance.Which combination of resources will meet these requirements MOST cost-effectively? (Choose two.)

A data engineer needs to use AWS Step Functions to design an orchestration workflow. The workflow must parallel process a large collection of data files and apply a specific transformation to each file.Which Step Functions state should the data engineer use to meet these requirements?

A company wants to implement real-time analytics capabilities. The company wants to use Amazon Kinesis Data Streams and Amazon Redshift to ingest and process streaming data at the rate of several gigabytes per second. The company wants to derive near real-time insights by using existing business intelligence (BI) and analytics tools.Which solution will meet these requirements with the LEAST operational overhead?

A company is planning to use a provisioned Amazon EMR cluster that runs Apache Spark jobs to perform big data analysis. The company requires high reliability. A big data team must follow best practices for running cost-optimized and long-running workloads on Amazon EMR. The team must find a solution that will maintain the company's current level of performance.Which combination of resources will meet these requirements MOST cost-effectively? (Choose two.)

A company maintains an Amazon Redshift provisioned cluster that the company uses for extract, transform, and load (ETL) operations to support critical analysis tasks. A sales team within the company maintains a Redshift cluster that the sales team uses for business intelligence (BI) tasks.The sales team recently requested access to the data that is in the ETL Redshift cluster so the team can perform weekly summary analysis tasks. The sales team needs to join data from the ETL cluster with data that is in the sales team's BI cluster.The company needs a solution that will share the ETL cluster data with the sales team without interrupting the critical analysis tasks. The solution must minimize usage of the computing resources of the ETL cluster.Which solution will meet these requirements?

A company uses an Amazon QuickSight dashboard to monitor usage of one of the company's applications. The company uses AWS Glue jobs to process data for the dashboard. The company stores the data in a single Amazon S3 bucket. The company adds new data every day.A data engineer discovers that dashboard queries are becoming slower over time. The data engineer determines that the root cause of the slowing queries is long-running AWS Glue jobs.Which actions should the data engineer take to improve the performance of the AWS Glue jobs? (Choose two.)

A company uses Amazon RDS to store transactional data. The company runs an RDS DB instance in a private subnet. A developer wrote an AWS Lambda function with default settings to insert, update, or delete data in the DB instance.The developer needs to give the Lambda function the ability to connect to the DB instance privately without using the public internet.Which combination of steps will meet this requirement with the LEAST operational overhead? (Choose two.)

A data engineer needs to join data from multiple sources to perform a one-time analysis job. The data is stored in Amazon DynamoDB, Amazon RDS, Amazon Redshift, and Amazon S3.Which solution will meet this requirement MOST cost-effectively?

A data engineer needs to join data from multiple sources to perform a one-time analysis job. The data is stored in Amazon DynamoDB, Amazon RDS, Amazon Redshift, and Amazon S3.Which solution will meet this requirement MOST cost-effectively?

A company is planning to use a provisioned Amazon EMR cluster that runs Apache Spark jobs to perform big data analysis. The company requires high reliability. A big data team must follow best practices for running cost-optimized and long-running workloads on Amazon EMR. The team must find a solution that will maintain the company's current level of performance.Which combination of resources will meet these requirements MOST cost-effectively? (Choose two.)

A company stores daily records of the financial performance of investment portfolios in .csv format in an Amazon S3 bucket. A data engineer uses AWS Glue crawlers to crawl the S3 data.The data engineer must make the S3 data accessible daily in the AWS Glue Data Catalog.Which solution will meet these requirements?

A data engineer must ingest a source of structured data that is in .csv format into an Amazon S3 data lake. The .csv files contain 15 columns. Data analysts need to run Amazon Athena queries on one or two columns of the dataset. The data analysts rarely query the entire file. Which solution will meet these requirements MOST cost-effectively? Amazon Athena is a serverless interactive query service that allows you to analyze data in Amazon S3 using standard SQL. Athena supports various data formats, such as CSV, JSON, ORC, Avro, and Parquet. However, not all data formats are equally efficient for querying. Some data formats, such as CSV and JSON, are row-oriented, meaning that they store data as a sequence of records, each with the same fields. Row-oriented formats are suitable for loading and exporting data, but they are not optimal for analytical queries that often access only a subset of columns. Row-oriented formats also do not support compression or encoding techniques that can reduce the data size and improve the query performance. On the other hand, some data formats, such as ORC and Parquet, are column-oriented, meaning that they store data as a collection of columns, each with a specific data type. Column-oriented formats are ideal for analytical queries that often filter, aggregate, or join data by columns. Column-oriented formats also support compression and encoding techniques that can reduce the data size and improve the query performance. For example, Parquet supports dictionary encoding, which replaces repeated values with numeric codes, and run-length encoding, which replaces consecutive identical values with a single value and a count. Parquet also supports various compression algorithms, such as Snappy, GZIP, and ZSTD, that can further reduce the data size and improve the query performance. Therefore, creating an AWS Glue extract, transform, and load (ETL) job to read from the .csv structured data source and writing the data into the data lake in Apache Parquet format will meet the requirements most cost-effectively. AWS Glue is a fully managed service that provides a serverless data integration platform for data preparation, data cataloging, and data loading. AWS Glue ETL jobs allow you to transform and load data from various sources into various targets, using either a graphical interface (AWS Glue Studio) or a code-based interface (AWS Glue console or AWS Glue API). By using AWS Glue ETL jobs, you can easily convert the data from CSV to Parquet format, without having to write or manage any code. Parquet is a column-oriented format that allows Athena to scan only the relevant columns and skip the rest, reducing the amount of data read from S3. This solution will also reduce the cost of Athena queries, as Athena charges based on the amount of data scanned from S3. The other options are not as cost-effective as creating an AWS Glue ETL job to write the data into the data lake in Parquet format. Using an AWS Glue PySpark job to ingest the source data into the data lake in .csv format will not improve the query performance or reduce the query cost, as .csv is a row-oriented format that does not support columnar access or compression. Creating an AWS Glue ETL job to ingest the data into the data lake in JSON format will not improve the query performance or reduce the query cost, as JSON is also a row-oriented format that does not support columnar access or compression. Using an AWS Glue PySpark job to ingest the source data into the data lake in Apache Avro format will improve the query performance, as Avro is a column-oriented format that supports compression and encoding, but it will require more operational effort, as you will need to write and maintain PySpark code to convert the data from CSV to Avro format.Reference: Amazon Athena Choosing the Right Data Format AWS Glue [AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide], Chapter 5: Data Analysis and Visualization, Section 5.1: Amazon Athena

A data engineer needs to schedule a workflow that runs a set of AWS Glue jobs every day. The data engineer does not require the Glue jobs to run or finish at a specific time.Which solution will run the Glue jobs in the MOST cost-effective way?

A company uses an Amazon QuickSight dashboard to monitor usage of one of the company's applications. The company uses AWS Glue jobs to process data for the dashboard. The company stores the data in a single Amazon S3 bucket. The company adds new data every day.A data engineer discovers that dashboard queries are becoming slower over time. The data engineer determines that the root cause of the slowing queries is long-running AWS Glue jobs.Which actions should the data engineer take to improve the performance of the AWS Glue jobs? (Choose two.)

A company uses an Amazon QuickSight dashboard to monitor usage of one of the company's applications. The company uses AWS Glue jobs to process data for the dashboard. The company stores the data in a single Amazon S3 bucket. The company adds new data every day.A data engineer discovers that dashboard queries are becoming slower over time. The data engineer determines that the root cause of the slowing queries is long-running AWS Glue jobs.Which actions should the data engineer take to improve the performance of the AWS Glue jobs? (Choose two.)

A company is migrating a legacy application to an Amazon S3 based data lake. A data engineer reviewed data that is associated with the legacy application. The data engineer found that the legacy data contained some duplicate information.The data engineer must identify and remove duplicate information from the legacy application data.Which solution will meet these requirements with the LEAST operational overhead?

A company is migrating a legacy application to an Amazon S3 based data lake. A data engineer reviewed data that is associated with the legacy application. The data engineer found that the legacy data contained some duplicate information.The data engineer must identify and remove duplicate information from the legacy application data.Which solution will meet these requirements with the LEAST operational overhead?

A data engineer must use AWS services to ingest a dataset into an Amazon S3 data lake. The data engineer profiles the dataset and discovers that the dataset contains personally identifiable information (PII). The data engineer must implement a solution to profile the dataset and obfuscate the PII.Which solution will meet this requirement with the LEAST operational effort?

A financial services company stores financial data in Amazon Redshift. A data engineer wants to run real-time queries on the financial data to support a web-based trading application. The data engineer wants to run the queries from within the trading application.Which solution will meet these requirements with the LEAST operational overhead?

A company is planning to use a provisioned Amazon EMR cluster that runs Apache Spark jobs to perform big data analysis. The company requires high reliability. A big data team must follow best practices for running cost-optimized and long-running workloads on Amazon EMR. The team must find a solution that will maintain the company's current level of performance.Which combination of resources will meet these requirements MOST cost-effectively? (Choose two.)

A company wants to implement real-time analytics capabilities. The company wants to use Amazon Kinesis Data Streams and Amazon Redshift to ingest and process streaming data at the rate of several gigabytes per second. The company wants to derive near real-time insights by using existing business intelligence (BI) and analytics tools.Which solution will meet these requirements with the LEAST operational overhead?

A company is migrating a legacy application to an Amazon S3 based data lake. A data engineer reviewed data that is associated with the legacy application. The data engineer found that the legacy data contained some duplicate information.The data engineer must identify and remove duplicate information from the legacy application data.Which solution will meet these requirements with the LEAST operational overhead?

A retail company has a customer data hub in an Amazon S3 bucket. Employees from many countries use the data hub to support company-wide analytics. A governance team must ensure that the company's data analysts can access data only for customers who are within the same country as the analysts.Which solution will meet these requirements with the LEAST operational effort?

A data engineer needs to securely transfer 5 TB of data from an on-premises data center to an Amazon S3 bucket. Approximately 5% of the data changes every day. Updates to the data need to be regularly proliferated to the S3 bucket. The data includes files that are in multiple formats. The data engineer needs to automate the transfer process and must schedule the process to run periodically.Which AWS service should the data engineer use to transfer the data in the MOST operationally efficient way?

A company wants to implement real-time analytics capabilities. The company wants to use Amazon Kinesis Data Streams and Amazon Redshift to ingest and process streaming data at the rate of several gigabytes per second. The company wants to derive near real-time insights by using existing business intelligence (BI) and analytics tools.Which solution will meet these requirements with the LEAST operational overhead?

A financial company wants to implement a data mesh. The data mesh must support centralized data governance, data analysis, and data access control. The company has decided to use AWS Glue for data catalogs and extract, transform, and load (ETL) operations.Which combination of AWS services will implement a data mesh? (Choose two.)

A data engineer needs to join data from multiple sources to perform a one-time analysis job. The data is stored in Amazon DynamoDB, Amazon RDS, Amazon Redshift, and Amazon S3.Which solution will meet this requirement MOST cost-effectively?

Which of the following best describes the type of data found in traditional relational databases?

A company is building an analytics solution. The solution uses Amazon S3 for data lake storage and Amazon Redshift for a data warehouse. The company wants to use Amazon Redshift Spectrum to query the data that is in Amazon S3.Which actions will provide the FASTEST queries? (Choose two.)

A data engineer needs to join data from multiple sources to perform a one-time analysis job. The data is stored in Amazon DynamoDB, Amazon RDS, Amazon Redshift, and Amazon S3.Which solution will meet this requirement MOST cost-effectively?

A financial company wants to implement a data mesh. The data mesh must support centralized data governance, data analysis, and data access control. The company has decided to use AWS Glue for data catalogs and extract, transform, and load (ETL) operations.Which combination of AWS services will implement a data mesh? (Choose two.)

A company has a frontend ReactJS website that uses Amazon API Gateway to invoke REST APIs. The APIs perform the functionality of the website. A data engineer needs to write a Python script that can be occasionally invoked through API Gateway. The code must return results to API Gateway.Which solution will meet these requirements with the LEAST operational overhead?

A data engineer needs to join data from multiple sources to perform a one-time analysis job. The data is stored in Amazon DynamoDB, Amazon RDS, Amazon Redshift, and Amazon S3.Which solution will meet this requirement MOST cost-effectively?

A company created an extract, transform, and load (ETL) data pipeline in AWS Glue. A data engineer must crawl a table that is in Microsoft SQL Server. The data engineer needs to extract, transform, and load the output of the crawl to an Amazon S3 bucket. The data engineer also must orchestrate the data pipeline.Which AWS service or feature will meet these requirements MOST cost-effectively?

A data engineer needs to use AWS Step Functions to design an orchestration workflow. The workflow must parallel process a large collection of data files and apply a specific transformation to each file.Which Step Functions state should the data engineer use to meet these requirements?

A company is planning to use a provisioned Amazon EMR cluster that runs Apache Spark jobs to perform big data analysis. The company requires high reliability. A big data team must follow best practices for running cost-optimized and long-running workloads on Amazon EMR. The team must find a solution that will maintain the company's current level of performance.Which combination of resources will meet these requirements MOST cost-effectively? (Choose two.)

A data engineer needs to join data from multiple sources to perform a one-time analysis job. The data is stored in Amazon DynamoDB, Amazon RDS, Amazon Redshift, and Amazon S3.Which solution will meet this requirement MOST cost-effectively?