P.S. Free & New Data-Engineer-Associate dumps are available on Google Drive shared by VCEEngine: https://drive.google.com/open?id=1zT9iZcujDIzFeu-XrBfpkK8FtJtCYl4j
The Amazon - AWS Certified Data Engineer - Associate (DEA-C01) Data-Engineer-Associate PDF file we have introduced is ideal for quick exam preparation. If you are working in a company, studying, or busy with your daily activities, our Amazon Data-Engineer-Associate dumps PDF format is the best option for you. Since this format works on laptops, tablets, and smartphones, you can open it and read Amazon Data-Engineer-Associate Questions without place and time restrictions.
| Section | Weight | Objectives |
|---|---|---|
| Data Security and Governance | 18% | - Apply governance and compliance best practices - Implement data security controls |
| Data Operations and Support | 22% | - Monitor and maintain data pipelines - Troubleshoot data workflow issues |
| Data Store Management | 26% | - Select appropriate data storage solutions - Optimize storage performance and cost |
| Data Ingestion and Transformation | 34% | - Ingest and transform data using AWS services - Build and manage data pipelines |
>> Test Amazon Data-Engineer-Associate Quiz <<
Passing the exam rests squarely on the knowledge of exam questions and exam skills. Our Data-Engineer-Associate training quiz has bountiful content that can fulfill your aims at the same time. We know high efficient Data-Engineer-Associate practice materials play crucial roles in your review. Our experts also collect with the newest contents and have been researching where the exam trend is heading and what it really want to examine you. By analyzing the syllabus and new trend, our Data-Engineer-Associate Practice Engine is totally in line with this exam for your reference. So grapple with this chance, our Data-Engineer-Associate practice materials will not let you down.
NEW QUESTION # 152
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?
Answer: C
Explanation:
An open source data lake format, such as Apache Parquet, Apache ORC, or Delta Lake, is a cost-effective way to perform a change data capture (CDC) operation on semi-structured data stored in Amazon S3. An open source data lake format allows you to query data directly from S3 using standard SQL, without the need to move or copy data to another service. An open source data lake format also supports schema evolution, meaning it can handle changes in the data structure over time. An open source data lake format also supports upserts, meaning it can insert new data and update existing data in the same operation, using a merge command. This way, you can efficiently capture the changes from the data source and apply them to the S3 data lake, without duplicating or losing any data.
The other options are not as cost-effective as using an open source data lake format, as they involve additional steps or costs. Option A requires you to create and maintain an AWS Lambda function, which can be complex and error-prone. AWS Lambda also has some limits on the execution time, memory, and concurrency, which can affect the performance and reliability of the CDC operation. Option B and D require you to ingest the data into a relational database service, such as Amazon RDS or Amazon Aurora, which can be expensive and unnecessary for semi-structured data. AWS Database Migration Service (AWS DMS) can write the changed data to the data lake, but it also charges you for the data replication and transfer. Additionally, AWS DMS does not support JSON as a source data type, so you would need to convert the data to a supported format before using AWS DMS. Reference:
What is a data lake?
Choosing a data format for your data lake
Using the MERGE INTO command in Delta Lake
[AWS Lambda quotas]
[AWS Database Migration Service quotas]
NEW QUESTION # 153
A company has used an Amazon Redshift table that is named Orders for 6 months. The company performs weekly updates and deletes on the table. The table has an interleaved sort key on a column that contains AWS Regions.
The company wants to reclaim disk space so that the company will not run out of storage space. The company also wants to analyze the sort key column.
Which Amazon Redshift command will meet these requirements?
Answer: B
Explanation:
Amazon Redshift is a fully managed, petabyte-scale data warehouse service that enables fast and cost-effective analysis of large volumes of data. Amazon Redshift uses columnar storage, compression, and zone maps to optimize the storage and performance of data. However, over time, as data is inserted, updated, or deleted, the physical storage of data can become fragmented, resulting in wasted disk space and degraded query performance. To address this issue, Amazon Redshift provides the VACUUM command, which reclaims disk space and resorts rows in either a specified table or all tables in the current schema1.
The VACUUM command has four options: FULL, DELETE ONLY, SORT ONLY, and REINDEX. The option that best meets the requirements of the question is VACUUM REINDEX, which re-sorts the rows in a table that has an interleaved sort key and rewritesthe table to a new location on disk. An interleaved sort key is a type of sort key that gives equal weight to each column in the sort key, and stores the rows in a way that optimizes the performance of queries that filter by multiple columns in the sort key. However, as data is added or changed, the interleaved sort order can become skewed, resulting in suboptimal query performance. The VACUUM REINDEX option restores the optimal interleaved sort order and reclaims disk space by removing deleted rows. This option also analyzes the sort key column and updates the table statistics, which are used by the query optimizer to generate the most efficient query execution plan23.
The other options are not optimal for the following reasons:
A: VACUUM FULL Orders. This option reclaims disk space by removing deleted rows and resorts the entire table. However, this option is not suitable for tables that have an interleaved sort key, as it does not restore the optimal interleaved sort order. Moreover, this option is the most resource-intensive and time-consuming, as it rewrites the entire table to a new location on disk.
B: VACUUM DELETE ONLY Orders. This option reclaims disk space by removing deleted rows, but does not resort the table. This option is not suitable for tables that have any sort key, as it does not improve the query performance by restoring the sort order. Moreover, this option does not analyze the sort key column and update the table statistics.
D: VACUUM SORT ONLY Orders. This option resorts the entire table, but does not reclaim disk space by removing deleted rows. This option is not suitable for tables that have an interleaved sort key, as it does not restore the optimal interleaved sort order. Moreover, this option does not analyze the sort key column and update the table statistics.
References:
1: Amazon Redshift VACUUM
2: Amazon Redshift Interleaved Sorting
3: Amazon Redshift ANALYZE
NEW QUESTION # 154
A data engineer is building a solution to detect sensitive information that is stored in a data lake across multiple Amazon S3 buckets. The solution must detect personally identifiable information (PII) that is in a proprietary data format.
Which solution will meet these requirements with the LEAST operational overhead?
Answer: C
Explanation:
Comprehensive and Detailed Explanation (150-250 words)
AWS Glue Detect PII transform is designed to identify sensitive data using custom pattern matching, making it well suited for detecting PII in proprietary or non-standard data formats. The transform integrates directly into AWS Glue ETL jobs and requires minimal configuration beyond defining the detection patterns.
Amazon Macie primarily relies on managed data identifiers and machine learning models optimized for common data formats such as JSON, CSV, and text. While Macie supports custom identifiers, it is less efficient for deeply proprietary formats and introduces additional service configuration.
Using AWS Lambda with custom regular expressions or Amazon Athena with SQL-based pattern matching would require building, operating, and maintaining custom logic across multiple buckets, increasing operational overhead and complexity.
AWS Glue provides a serverless, scalable, and centralized approach for PII detection as part of an existing data processing pipeline, making it the most operationally efficient solution for this requirement.
Therefore, Option A is the best answer.
NEW QUESTION # 155
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?
Answer: A
Explanation:
Amazon EC2 instances can use two types of storage volumes: instance store volumes and Amazon EBS volumes. Instance store volumes are ephemeral, meaning they are only attached to the instance for the duration of its life cycle. If the instance is stopped, terminated, or fails, the data on the instance store volume is lost. Amazon EBS volumes are persistent, meaning they can be detached from the instance and attached to another instance, and the data on the volume is preserved. To meet the requirement of persisting the data even if the EC2 instances are terminated, the data engineer must use Amazon EBS volumes to store the application data. The solution is to launch new EC2 instances by using an AMI that is backed by an EC2 instance store volume, which is the default option for most AMIs. Then, the data engineer must attach an Amazon EBS volume to each instance and configure the application to write the data to the EBS volume. This way, the data will be saved on the EBS volume and can be accessed by another instance if needed. The data engineer can apply the default settings to the EC2 instances, as there is no need to modify the instance type, security group, or IAM role for this solution. The other options are either not feasible or not optimal. Launching new EC2 instances by using an AMI that is backed by an EC2 instance store volume that contains the application data (option A) or by using an AMI that is backed by a root Amazon EBS volume that contains the application data (option B) would not work, as the data on the AMI would be outdated and overwritten by the new instances. Attaching an additional EC2 instance store volume to contain the application data (option D) would not work, as the data on the instance store volume would be lost if the instance is terminated. References:
* Amazon EC2 Instance Store
* Amazon EBS Volumes
* AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 2: Data Store Management, Section 2.1: Amazon EC2
NEW QUESTION # 156
A company stores customer data in an Amazon S3 bucket. The company must permanently delete all customer data that is older than 7 years.
Answer: D
Explanation:
S3 Lifecycle policies automate data retention and deletion. By specifying an expiration rule for 7 years, objects older than that period are permanently deleted without manual intervention.
"To automatically delete aged data, configure an S3 Lifecycle rule with an expiration policy for objects older than the retention period."
- Ace the AWS Certified Data Engineer - Associate Certification - version 2 - apple.pdf
NEW QUESTION # 157
......
When choosing our Data-Engineer-Associate practice materials, we offer a whole package of both practice materials and considerate services. We provide our time-saved, high efficient Data-Engineer-Associate actual exam containing both functions into one. There is a whole profession of experts who work out the details of our Data-Engineer-Associate Study Guide. So all points of questions are wholly based on the real exam and we won the acclaim from all over the world.
Data-Engineer-Associate Latest Test Camp: https://www.vceengine.com/Data-Engineer-Associate-vce-test-engine.html
P.S. Free & New Data-Engineer-Associate dumps are available on Google Drive shared by VCEEngine: https://drive.google.com/open?id=1zT9iZcujDIzFeu-XrBfpkK8FtJtCYl4j