News & Events

James Davis James Davis

0 Course Enrolled • 0 Course Completed

Biography

Data-Engineer-Associate Valid Exam Notes & Data-Engineer-Associate Verified Answers

These Data-Engineer-Associate practice exams enable you to monitor your progress and make adjustments. These Data-Engineer-Associate practice tests are very useful for pinpointing areas that require more effort. You can lower your anxiety level and boost your confidence by taking our Data-Engineer-Associate Practice Tests. Only Windows computers support the desktop practice exam software. The web-based AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate) practice test is functional on all operating systems.

Our company guarantees this pass rate from various aspects such as content and service on our Data-Engineer-Associate exam questions. We have hired the most authoritative professionals to compile the content Of the Data-Engineer-Associate study materials. And we offer 24/7 service online to help you on all kinds of the problems about the Data-Engineer-Associate learning guide. Of course, we also consider the needs of users, ourData-Engineer-Associate exam questions hope to help every user realize their dreams.

>> Data-Engineer-Associate Valid Exam Notes <<

Data-Engineer-Associate Verified Answers | Data-Engineer-Associate 100% Correct Answers

Success in acquiring the Data-Engineer-Associate is seen to be crucial for your career growth. But preparing for the AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate) exam in today's busy routine might be difficult. This is where actual Amazon Data-Engineer-Associate Exam Questions offered by ExamDumpsVCE come into play. For those candidates, who want to clear the Data-Engineer-Associate certification exam in a short time, we offer updated and real exam questions.

Amazon AWS Certified Data Engineer - Associate (DEA-C01) Sample Questions (Q168-Q173):

NEW QUESTION # 168
A company has a data lake in Amazon 53. 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 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.
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 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.

Answer: B

Explanation:
Problem Analysis:
The company uses AWS Glue for ETL pipelines and must enforce data quality checks during pipeline execution.
The goal is to implement quality checks with minimal implementation effort.
Key Considerations:
AWS Glue provides an Evaluate Data Quality transform that allows for defining quality checks directly in the pipeline.
DQDL (Data Quality Definition Language) simplifies the process by allowing declarative rule definitions.
Solution Analysis:
Option A: SQL Transform
SQL queries can implement rules but require manual effort for each rule and do not integrate natively with Glue.
Option B: Evaluate Data Quality Transform + DQDL
AWS Glue's built-in Evaluate Data Quality transform is designed for this use case.
Allows defining thresholds and rules in DQDL with minimal coding effort.
Option C: Custom Transform with PyDeequ
PyDeequ is a powerful library but adds unnecessary complexity compared to Glue's native features.
Option D: Custom Transform with Great Expectations
Similar to PyDeequ, Great Expectations adds operational complexity and external dependencies.
Final Recommendation:
Use the Evaluate Data Quality transform with DQDL to implement data quality rules in AWS Glue pipelines.
Reference:
AWS Glue Data Quality
DQDL Syntax and Examples
AWS Glue Studio Documentation

NEW QUESTION # 169
A company uses an Amazon Redshift cluster as a data warehouse that is shared across two departments. To comply with a security policy, each department must have unique access permissions.
Department A must have access to tables and views for Department A. Department B must have access to tables and views for Department B.
The company often runs SQL queries that use objects from both departments in one query.
Which solution will meet these requirements with the LEAST operational overhead?

A. Group tables and views for each department into dedicated schemas. Manage permissions at the schema level.
B. Update the names of the tables and views to follow a naming convention that contains the department names. Manage permissions based on the new naming convention.
C. Create an IAM user group for each department. Use identity-based IAM policies to grant table and view permissions based on the IAM user group.
D. Group tables and views for each department into dedicated databases. Manage permissions at the database level.

Answer: A

NEW QUESTION # 170
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. Register the S3 bucket as a data lake location in AWS Lake Formation. Use the Lake Formation row-level security features to enforce the company's access policies.
B. Move the data to AWS Regions that are close to the countries where the customers are. Provide access to each analyst based on the country that the analyst serves.
C. Load the data into Amazon Redshift. Create a view for each country. Create separate 1AM roles for each country to provide access to data from each country. Assign the appropriate roles to the analysts.
D. Create a separate table for each country's customer data. Provide access to each analyst based on the country that the analyst serves.

Answer: A

Explanation:
AWS Lake Formation is a service that allows you to easily set up, secure, and manage data lakes. One of the features of Lake Formation is row-level security, which enables you to control access to specific rows or columns of data based on the identity or role of the user. This feature is useful for scenarios where you need to restrict access to sensitive or regulated data, such as customer data from different countries. By registering the S3 bucket as a data lake location in Lake Formation, you can use the Lake Formation console or APIs to define and apply row-level security policies to the data in the bucket. You can also use Lake Formation blueprints to automate the ingestion and transformation of data from various sources into the data lake. This solution requires the least operational effort compared to the other options, as it does not involve creating or moving data, or managing multiple tables, views, or roles. Reference:
AWS Lake Formation
Row-Level Security
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 4: Data Lakes and Data Warehouses, Section 4.2: AWS Lake Formation

NEW QUESTION # 171
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?

A. Create a destination data stream in the security AWS account. Create an IAM role and a trust policy to grant CloudWatch Logs the permission to put data into the stream. Create a subscription filter in the security AWS account.
B. Create a destination data stream in the security AWS account. Create an IAM role and a trust policy to grant CloudWatch Logs the permission to put data into the stream. Create a subscription filter in the production AWS account.
C. Create a destination data stream in the production AWS account. In the security AWS account, create an IAM role that has cross-account permissions to Kinesis Data Streams in the production AWS account.
D. Create a destination data stream in the production AWS account. In the production AWS account, create an IAM role that has cross-account permissions to Kinesis Data Streams in the security AWS account.

Answer: B

Explanation:
Amazon Kinesis Data Streams is a service that enables you to collect, process, and analyze real-time streaming data. You can use Kinesis Data Streams to ingest data from various sources, such as Amazon CloudWatch Logs, and deliver it to different destinations, such as Amazon S3 or Amazon Redshift. To use Kinesis Data Streams to deliver the security logs from the production AWS account to the security AWS account, you need to create a destination data stream in the security AWS account. This data stream will receive the log data from the CloudWatch Logs service in the production AWS account. To enable this cross-account data delivery, you need to create an IAM role and a trust policy in the security AWS account. The IAM role defines the permissions that the CloudWatch Logs service needs to put data into the destination data stream. The trust policy allows the production AWS account to assume the IAM role. Finally, you need to create a subscription filter in the production AWS account. A subscription filter defines the pattern to match log events and the destination to send the matching events. In this case, the destination is the destination data stream in the security AWS account. This solution meets the requirements of using Kinesis Data Streams to deliver the security logs to the security AWS account. The other options are either not possible or not optimal. You cannot create a destination data stream in the production AWS account, as this would not deliver the data to the security AWS account. You cannot create a subscription filter in the security AWS account, as this would not capture the log events from the production AWS account. Reference:
Using Amazon Kinesis Data Streams with Amazon CloudWatch Logs
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 3: Data Ingestion and Transformation, Section 3.3: Amazon Kinesis Data Streams

NEW QUESTION # 172
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?

A. Change the primary key to be the data column that is most often used in a WHERE clause of the SQL SELECT statement.
B. Change the sort key to be the data column that is most often used in a WHERE clause of the SQL SELECT statement.
C. Change the distribution key to the table column that has the largest dimension.
D. Upgrade the reserved node from ra3.4xlarqe to ra3.16xlarqe.

Answer: C

Explanation:
Changing the distribution key to the table column that has the largest dimension will help to balance the load more evenly across all five compute nodes. The distribution key determines how the rows of a table are distributed among the slices of the cluster. If the distribution key is not chosen wisely, it can cause data skew, meaning some slices will have more data than others, resulting in uneven CPU load and query performance.
By choosing the table column that has the largest dimension, meaning the column that has the most distinct values, as the distribution key, the data engineer can ensure that the rows are distributed more uniformly across the slices, reducing data skew and improving query performance.
The other options are not solutions that will meet the requirements. Option A, changing the sort key to be the data column that is most often used in a WHERE clause of the SQL SELECT statement, will not affect the data distribution or the CPU load. The sort key determines the order in which the rows of a table are stored on disk, which can improve the performance of range-restricted queries, but not the load balancing. Option C, upgrading the reserved node from ra3.4xlarge to ra3.16xlarge, will not maintain the current number of compute nodes, as it will increase the cost and the capacity of the cluster. Option D, changing the primary key to be the data column that is most often used in a WHERE clause of the SQL SELECT statement, will not affect the data distribution or the CPU load either. The primary key is a constraint that enforces the uniqueness of the rows in a table, but it does not influence the data layout or the query optimization. References:
Choosing a data distribution style
Choosing a data sort key
Working with primary keys

NEW QUESTION # 173
......

The process of getting a certificate isn’t an easy process for many of the candidates. We will provide you with the company in your whole process of preparation in the Data-Engineer-Associate learning materials. You will find that you are not the only yourself, you also have us, our service stuff will offer you the most considerate service, and in the process of practicing the Data-Engineer-Associate Training Materials, if you have any questions please contact us, we will be very glad to help you.

Data-Engineer-Associate Verified Answers: https://www.examdumpsvce.com/Data-Engineer-Associate-valid-exam-dumps.html

Amazon Data-Engineer-Associate Valid Exam Notes It's better to hand-lit own light than look up to someone else's glory, Amazon Data-Engineer-Associate Valid Exam Notes All successful stories have some painstaking effort and perspiration included, Data-Engineer-Associate Interactive Exam engines, Our Data-Engineer-Associate study questions have simplified the complicated notions and add the instances, the stimulation and the diagrams to explain any hard-to-explain contents, With Data-Engineer-Associate exam torrent, you neither need to keep yourself locked up in the library for a long time nor give up a rare vacation to review.

Task Environment Analysis, How many times has this happened to you, It's Data-Engineer-Associate better to hand-lit own light than look up to someone else's glory, All successful stories have some painstaking effort and perspiration included.

Data-Engineer-Associate Test Quiz & Data-Engineer-Associate Actual Test & Data-Engineer-Associate Test Torrent

Data-Engineer-Associate Interactive Exam engines, Our Data-Engineer-Associate study questions have simplified the complicated notions and add the instances, the stimulation and the diagrams to explain any hard-to-explain contents.

With Data-Engineer-Associate exam torrent, you neither need to keep yourself locked up in the library for a long time nor give up a rare vacation to review.