AWS Certified Data Engineer – Associate DEA-C01 Dumps (V10.02) Are Available Online: Come Here and Check the Amazon DEA-C01 Free Dumps (Part 1, Q1-Q40)

1. A manufacturing company collects sensor data from its factory floor to monitor and enhance operational efficiency. The company uses Amazon Kinesis Data Streams to publish the data that the sensors collect to a data stream. Then Amazon Kinesis Data Firehose writes the data to an Amazon S3 bucket.

The company needs to display a real-time view of operational efficiency on a large screen in the manufacturing facility.

Which solution will meet these requirements with the LOWEST latency?

2. A company has five offices in different AWS Regions. Each office has its own human resources (HR) department that uses a unique IAM role. The company stores employee records in a data lake that is based on Amazon S3 storage.

A data engineering team needs to limit access to the records. Each HR department should be able to access records for only employees who are within the HR department's Region.

Which combination of steps should the data engineering team take to meet this requirement with the LEAST operational overhead? (Choose two.)

3. 1.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?

4. 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?

5. A security company stores IoT data that is in JSON format in an Amazon S3 bucket. The data structure can change when the company upgrades the IoT devices. The company wants to create a data catalog that includes the IoT data. The company's analytics department will use the data catalog to index the data.

Which solution will meet these requirements MOST cost-effectively?

6. 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?

7. A company receives .csv files that contain physical address data. The data is in columns that have the following names: Door_No, Street_Name, City, and Zip_Code.

The company wants to create a single column to store these values in the following format:

Which solution will meet this requirement with the LEAST coding effort?

8. 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?

9. A company is developing an application that runs on Amazon EC2 instances. Currently, the data that the application generates is temporary. However, the company needs to persist the data, even if the EC2 instances are terminated.

A data engineer must launch new EC2 instances from an Amazon Machine Image (AMI) and configure the instances to preserve the data.

Which solution will meet this requirement?

10. 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.)

11. A company needs to build a data lake in AWS. The company must provide row-level data access and column-level data access to specific teams. The teams will access the data by using Amazon Athena, Amazon Redshift Spectrum, and Apache Hive from Amazon EMR.

Which solution will meet these requirements with the LEAST operational overhead?

12. A company uses Amazon Redshift for its data warehouse. The company must automate refresh schedules for Amazon Redshift materialized views.

Which solution will meet this requirement with the LEAST effort?

13. 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?

14. 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?

15. A data engineer must build an extract, transform, and load (ETL) pipeline to process and load data from 10 source systems into 10 tables that are in an Amazon Redshift database. All the source systems generate .csv, JSON, or Apache Parquet files every 15 minutes. The source systems all deliver files into one Amazon S3 bucket. The file sizes range from 10 MB to 20 GB. The ETL pipeline must function correctly despite changes to the data schema.

Which data pipeline solutions will meet these requirements? (Choose two.)

16. A company stores details about transactions in an Amazon S3 bucket. The company wants to log all writes to the S3 bucket into another S3 bucket that is in the same AWS Region.

Which solution will meet this requirement with the LEAST operational effort?

17. A company needs to partition the Amazon S3 storage that the company uses for a data lake.

The partitioning will use a path of the S3 object keys in the following format: s3://bucket/prefix/year=2023/month=01/day=01.

A data engineer must ensure that the AWS Glue Data Catalog synchronizes with the S3 storage when the company adds new partitions to the bucket.

Which solution will meet these requirements with the LEAST latency?

18. A data engineer must manage the ingestion of real-time streaming data into AWS. The data engineer wants to perform real-time analytics on the incoming streaming data by using time-based aggregations over a window of up to 30 minutes. The data engineer needs a solution that is highly fault tolerant.

Which solution will meet these requirements with the LEAST operational overhead?

19. 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?

20. 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?

21. 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?

22. A data engineering team is using an Amazon Redshift data warehouse for operational reporting. The team wants to prevent performance issues that might result from long- running queries. A data engineer must choose a system table in Amazon Redshift to record anomalies when a query optimizer identifies conditions that might indicate performance issues.

Which table views should the data engineer use to meet this requirement?

23. A manufacturing company wants to collect data from sensors. A data engineer needs to implement a solution that ingests sensor data in near real time.

The solution must store the data to a persistent data store. The solution must store the data in nested JSON format. The company must have the ability to query from the data store with a latency of less than 10 milliseconds.

Which solution will meet these requirements with the LEAST operational overhead?

24. A company uses Amazon Athena to run SQL queries for extract, transform, and load (ETL) tasks by using Create Table As Select (CTAS). The company must use Apache Spark instead of SQL to generate analytics.

Which solution will give the company the ability to use Spark to access Athena?

25. A company uses an Amazon Redshift provisioned cluster as its database. The Redshift cluster has five reserved ra3.4xlarge nodes and uses key distribution.

A data engineer notices that one of the nodes frequently has a CPU load over 90%. SQL Queries that run on the node are queued. The other four nodes usually have a CPU load under 15% during daily operations.

The data engineer wants to maintain the current number of compute nodes. The data engineer also wants to balance the load more evenly across all five compute nodes.

Which solution will meet these requirements?

26. 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.)

27. 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.)

28. A company has a production AWS account that runs company workloads. The company's security team created a security AWS account to store and analyze security logs from the production AWS account. The security logs in the production AWS account are stored in Amazon CloudWatch Logs. The company needs to use Amazon Kinesis Data Streams to deliver the security logs to the security AWS account.

Which solution will meet these requirements?

29. 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?

30. A company is planning to upgrade its Amazon Elastic Block Store (Amazon EBS) General Purpose SSD storage from gp2 to gp3. The company wants to prevent any interruptions in its Amazon EC2 instances that will cause data loss during the migration to the upgraded storage.

Which solution will meet these requirements with the LEAST operational overhead?

31. A company receives call logs as Amazon S3 objects that contain sensitive customer information. The company must protect the S3 objects by using encryption. The company must also use encryption keys that only specific employees can access.

Which solution will meet these requirements with the LEAST effort?

32. An airline company is collecting metrics about flight activities for analytics. The company is conducting a proof of concept (POC) test to show how analytics can provide insights that the company can use to increase on-time departures.

The POC test uses objects in Amazon S3 that contain the metrics in .csv format. The POC test uses Amazon Athena to query the data. The data is partitioned in the S3 bucket by date.

As the amount of data increases, the company wants to optimize the storage solution to improve query performance.

Which combination of solutions will meet these requirements? (Choose two.)

33. 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?

34. 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?

35. 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?

36. 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.)

37. A company stores data in a data lake that is in Amazon S3. Some data that the company stores in the data lake contains personally identifiable information (PII). Multiple user groups need to access the raw data. The company must ensure that user groups can access only the PII that they require.

Which solution will meet these requirements with the LEAST effort?

38. 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?

39. A company is migrating on-premises workloads to AWS. The company wants to reduce overall operational overhead. The company also wants to explore serverless options.

The company's current workloads use Apache Pig, Apache Oozie, Apache Spark, Apache Hbase, and Apache Flink. The on-premises workloads process petabytes of data in seconds. The company must maintain similar or better performance after the migration to AWS.

Which extract, transform, and load (ETL) service will meet these requirements?

40. A media company uses software as a service (SaaS) applications to gather data by using third-party tools. The company needs to store the data in an Amazon S3 bucket. The company will use Amazon Redshift to perform analytics based on the data.

Which AWS service or feature will meet these requirements with the LEAST operational overhead?