Snowflake DEA-C01 Exam Online & VCE DEA-C01 Exam Simulator

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Snowflake DEA-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	Security: The Security topic of the DEA-C01 test covers the principles of Snowflake security, including the management of system roles and data governance. It measures the ability to secure data and ensure compliance with policies, crucial for maintaining secure data environments for Snowflake Data Engineers and Software Engineers.
Topic 2	Data Movement: Snowflake Data Engineers and Software Engineers are assessed on their proficiency to load, ingest, and troubleshoot data in Snowflake. It evaluates skills in building continuous data pipelines, configuring connectors, and designing data sharing solutions.
Topic 3	Performance Optimization: This topic assesses the ability to optimize and troubleshoot underperforming queries in Snowflake. Candidates must demonstrate knowledge in configuring optimal solutions, utilizing caching, and monitoring data pipelines. It focuses on ensuring engineers can enhance performance based on specific scenarios, crucial for Snowflake Data Engineers and Software Engineers.
Topic 4	Data Transformation: The SnowPro Advanced: Data Engineer exam evaluates skills in using User-Defined Functions (UDFs), external functions, and stored procedures. It assesses the ability to handle semi-structured data and utilize Snowpark for transformations. This section ensures Snowflake engineers can effectively transform data within Snowflake environments, critical for data manipulation tasks.
Topic 5	Storage and Data Protection: The topic tests the implementation of data recovery features and the understanding of Snowflake's Time Travel and micro-partitions. Engineers are evaluated on their ability to create new environments through cloning and ensure data protection, highlighting essential skills for maintaining Snowflake data integrity and accessibility.

>> Snowflake DEA-C01 Exam Online <<

Free PDF Snowflake DEA-C01 Exam Online Are Leading Materials & Practical DEA-C01: SnowPro Advanced: Data Engineer Certification Exam

Our Snowflake practice examinations provide a wonderful opportunity to pinpoint and overcome mistakes. By overcoming your mistakes before appearing in the real Snowflake DEA-C01 test, you can avoid making mistakes in the actual DEA-C01 Exam. These DEA-C01 self-assessment exams show your results, helping you to improve your performance while tracking your progress.

Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q28-Q33):

NEW QUESTION # 28
Which are the Cloud Platforms that Support Calling an External Function?

A. AWS only
B. AWS & AZURE
C. GCP
D. AWS,GCP,AZURE

Answer: D

NEW QUESTION # 29
Pivoting in SQL is mainly used to transform data from:

A. Multiple rows into multiple columns
B. One row to one column
C. Only one column to one row
D. Multiple columns into multiple rows

Answer: A

NEW QUESTION # 30
Mohan, Data engineer works with ALTUSO Company, wants to programmatically check the status of the query. He needs query id to identify each query executed by Snowflake & using Snowflake Connector for Python to execute a query, how he will be able to meet this requirements. Select the best options you will suggest?

A. He can access the query ID through the sfqid attribute in the Cursor object.
1.cur = con.cursor()
2.cur.execute("SELECT * FROM snowtable")
3.print(cur.sfqid)
B. When he used the Snowflake Connector for Python to execute a query, he can access the query ID through the pyqueryid attribute in the Cursor object.
C. He needs to query history views to get the queryID as best practices.
D. Using python connector, snowflake does not support queryID retrieval for both syn-chronous & asynchronous query.

Answer: A

Explanation:
Explanation
Retrieving the Snowflake Query ID
A query ID identifies each query executed by Snowflake. When you use the Snowflake Connector for Python to execute a query, you can access the query ID through the sfqid attribute in the Cursor object:
1.# Retrieving a Snowflake Query ID
2.cur = con.cursor()
3.cur.execute("SELECT * FROM testtable")
4.print(cur.sfqid)

NEW QUESTION # 31
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. Use Amazon Athena Federated Query to join the data from all data sources.
B. Use Redshift Spectrum to query data from DynamoDB, Amazon RDS, and Amazon S3 directly from Redshift.
C. Use an Amazon EMR provisioned cluster to read from all sources. Use Apache Spark to join the data and perform the analysis.
D. Copy the data from DynamoDB, Amazon RDS, and Amazon Redshift into Amazon S3. Run Amazon Athena queries directly on the S3 files.

Answer: A

Explanation:
You can query these sources by using Federated Queries, which is a native feature of Athena.
The other options may increase costs and operational overhead, as they use more than one service to achieve the same result.
https://docs.aws.amazon.com/athena/latest/ug/connectors-available.html

NEW QUESTION # 32
External Function is a type of UDF & can be Scaler or Tabular?

A. TRUE
B. FALSE

Answer: B

Explanation:
Explanation
External functions must be scalar functions. A scalar external function returns a single value for each input row.

NEW QUESTION # 33
......

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SNOWFLAKE DEA-C01 EXAM ONLINE & VCE DEA-C01 EXAM SIMULATOR

Snowflake DEA-C01 Exam Online & VCE DEA-C01 Exam Simulator