Das neueste Data-Engineer-Associate, nützliche und praktische Data-Engineer-Associate pass4sure Trainingsmaterial

Übrigens, Sie können die vollständige Version der ZertFragen Data-Engineer-Associate Prüfungsfragen aus dem Cloud-Speicher herunterladen: https://drive.google.com/open?id=1qTuM8zG8TPuCyGFGlMfYtoi7dHfIHmTX

Die simulierten Prüfungen zu machen können Ihre Selbstbewusstsein erstarken. Mit der Simulations-Software Testing Engine von unserer Amazon Data-Engineer-Associate können Sie die realistische Atmosphäre dieser Prüfung erfahren. Diese Erfahrungen sind sehr wichtig für Sie bei der späteren echten Amazon Data-Engineer-Associate Prüfung. Neben Amazon Data-Engineer-Associate haben wir auch viele andere IT-Prüfungsunterlagen geforscht. Diese Prüfungshilfe können Sie auf unserer Webseite finden. Wenn Sie irgend bezügliche Fragen haben, können Sie einfach mit unserem 24/7 online Kundendienst Personal kommunizieren.

Amazon Data-Engineer-Associate Exam Syllabus Topics:

SectionWeightObjectives
Data Store Management26%- Optimize storage performance and cost
- Design and implement data storage solutions
  • 1. Data lakes, data warehouses, databases
  • 2. S3, Redshift, DynamoDB, RDS, Lake Formation
- Manage data lifecycle and storage tiers
Data Ingestion and Transformation34%- Ingest data from various sources
  • 1. Use services like Kinesis, DMS, Glue, S3
  • 2. Batch and streaming data ingestion
- Transform and enrich data
  • 1. Use Spark, EMR, Step Functions
  • 2. Apply data processing logic
  • 3. Orchestrate data pipelines
- Implement data quality and validation
Data Security and Governance18%- Encrypt data at rest and in transit
- Implement access control and authentication
  • 1. IAM, Lake Formation, resource policies
- Enforce compliance and data governance
  • 1. Data lineage, audit logging, regulatory requirements
- Protect sensitive data
Data Operations and Support22%- Automate operational tasks
- Monitor and troubleshoot data pipelines
  • 1. CloudWatch, X-Ray, logging and metrics
- Ensure reliability and scalability
- Backup, restore, and disaster recovery

>> Data-Engineer-Associate Deutsch Prüfung <<

Wir machen Data-Engineer-Associate leichter zu bestehen!

Unsere Garantie, Die Prüfungsfragen und Antworten zu Amazon Data-Engineer-Associate （AWS Certified Data Engineer - Associate (DEA-C01)） von ZertFragen ist eine Garantie für eine erfolgreiche Prüfung! Bisher fiel noch keiner unserer Kandidaten durch! Falls aber jemand durch die Zertifizierungsprüfung fallen sollte, zahlen wir die 100% Material-Gebühr zurück. Wir übernehmen die volle Geld-zurück-Garantie auf Ihre Zertifizierungsprüfungen! Unsere Fragen und Antoworten sind alle aus dem Fragenpool, alle sind echt und original.

Amazon AWS Certified Data Engineer - Associate (DEA-C01) Data-Engineer-Associate Prüfungsfragen mit Lösungen (Q192-Q197):

192. Frage
A company is uploading log files from on-premises servers to an Amazon S3 bucket. The company needs to validate that the logs from the on-premises servers are the same as the logs that are stored in the S3 bucket.
Which solution will meet this requirement?

Antwort: B

Begründung:
Amazon S3 natively supports checksum validation during uploads when objects are uploaded by using the AWS SDK. The SDK can automatically calculate a checksum, such as CRC32, on the client side and send it with the upload request. Amazon S3 validates the checksum upon receipt and stores it with the object, ensuring that the data uploaded is exactly the same as the source data.
Storing the checksum in the S3 object metadata provides a lightweight and cost-effective way to verify data integrity without requiring additional compute, storage, or post-processing steps. This approach validates the logs at upload time, which is the most efficient and reliable method.
Using AWS Lambda to calculate SHA-256 checksums would require additional compute, orchestration, and storage, increasing cost and operational complexity. Amazon S3 Object Lock enforces immutability and retention but does not validate data integrity between source and destination. Governance or compliance mode Object Lock cannot detect whether uploaded data matches the original logs.
Therefore, using the AWS SDK checksum validation during upload is the simplest, most efficient, and AWS- recommended approach for ensuring log integrity.


193. Frage
A data engineer is processing a large amount of log data from web servers. The data is stored in an Amazon S3 bucket. The data engineer uses AWS services to process the data every day. The data engineer needs to extract specific fields from the raw log data and load the data into a data warehouse for analysis.

Antwort: D


194. Frage
A data engineer needs to create a new empty table in Amazon Athena that has the same schema as an existing table named old-table.
Which SQL statement should the data engineer use to meet this requirement?

Antwort: C

Begründung:
* Problem Analysis:
* The goal is to create a new empty table in Athena with the same schema as an existing table (old_table).
* The solution must avoid copying any data.
* Key Considerations:
* CREATE TABLE AS (CTAS) is commonly used in Athena for creating new tables based on an existing table.
* Adding the WITH NO DATA clause ensures only the schema is copied, without transferring any data.
* Solution Analysis:
* Option A: Copies both schema and data. Does not meet the requirement for an empty table.
* Option B: Inserts data into an existing table, which does not create a new table.
* Option C: Creates an empty table but does not copy the schema.
* Option D: Creates a new table with the same schema and ensures it is empty by using WITH NO DATA.
* Final Recommendation:
* Use D. CREATE TABLE new_table AS (SELECT * FROM old_table) WITH NO DATA to create an empty table with the same schema.
:
Athena CTAS Queries
CREATE TABLE Statement in Athena


195. Frage
A company stores historical customer data in an Amazon Redshift table. A column named Email contains null entries and values that are not email addresses. The quality of the Email column is critical for multiple downstream processes. A data engineer must create an AWS Glue Data Quality rule that fails when the percentage of valid email addresses in the Email column is less than 90%.
Which component of an AWS Glue Data Quality rule will meet these requirements?

Antwort: B

Begründung:
Option C is correct because the requirement is to verify that at least 90% of values in the Email column are valid email addresses. In AWS Glue Data Quality, rules are written in DQDL, and ColumnValues is the rule component used to validate whether column values satisfy a condition or pattern. AWS Glue Data Quality documentation explains that DQDL is the language used to define rules, and it specifically notes that ColumnValues rules can evaluate column content and that NULL values do not pass during comparisons.
That is important here because the problem explicitly says the column contains null entries and invalid email values. A threshold of > 0.9 means the rule passes only when more than 90% of rows satisfy the email- validation condition.
Option A is incorrect because Uniqueness checks the percentage of values that are unique, not whether values are valid email addresses. AWS documents Uniqueness as measuring how many values occur exactly once, which is unrelated to email-format validity. Option D has the same issue because UniqueValueRatio addresses uniqueness characteristics, not format validation. Option B uses the right rule family but the wrong threshold because > 0.1 would require only 10% valid values. Therefore, ColumnValues with a threshold greater than 0.9 is the correct choice.


196. Frage
A data engineer needs to create a new empty table in Amazon Athena that has the same schema as an existing table named old-table.
Which SQL statement should the data engineer use to meet this requirement?

Antwort: D

Begründung:
Problem Analysis:
The goal is to create a new empty table in Athena with the same schema as an existing table (old_table).
The solution must avoid copying any data.
Key Considerations:
CREATE TABLE AS (CTAS) is commonly used in Athena for creating new tables based on an existing table.
Adding the WITH NO DATA clause ensures only the schema is copied, without transferring any data.
Solution Analysis:
Option A: Copies both schema and data. Does not meet the requirement for an empty table.
Option B: Inserts data into an existing table, which does not create a new table.
Option C: Creates an empty table but does not copy the schema.
Option D: Creates a new table with the same schema and ensures it is empty by using WITH NO DATA.
Final Recommendation:
Use D. CREATE TABLE new_table AS (SELECT * FROM old_table) WITH NO DATA to create an empty table with the same schema.
Athena CTAS Queries
CREATE TABLE Statement in Athena


197. Frage
......

ZertFragen ist nicht nur zuverlässig, sondern bietet auch erstklassigen Service. Wenn Sie die Prüfung nach dem Kauf der Data-Engineer-Associate -Produkte nicht bestehen, versprechen wir Ihnen 100% eine volle Rückerstattung. ZertFragen steht Ihnen auch einen einjährigen kostenlosen Update-Service zur Verfügung.

Data-Engineer-Associate Deutsche Prüfungsfragen: https://www.zertfragen.com/Data-Engineer-Associate_prufung.html

BONUS!!! Laden Sie die vollständige Version der ZertFragen Data-Engineer-Associate Prüfungsfragen kostenlos herunter: https://drive.google.com/open?id=1qTuM8zG8TPuCyGFGlMfYtoi7dHfIHmTX