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The customizable Snowflake DEA-C01 practice tests create a scenario of a real-based Snowflake which is helpful for students so they don’t feel much pressure when they are giving the final examination. The students can give unlimited DEA-C01 practice tests and make themselves better day by day to achieve their desired destination. The candidates can even access their previously given Snowflake DEA-C01 Practice Test from the history which allows them to be careful while giving the test next time and prepare for Snowflake DEA-C01 certification in a better way.

Snowflake DEA-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	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 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	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.
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	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.

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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q383-Q388):

NEW QUESTION # 383
Which are the two ways to access elements in a JSON object?

A. Use SemiColon notation to traverse a path in a JSON object:
<col-umn>:<level1_element>;<level2_element>;<level3_element>.
B. Use dot notation to traverse a path in a JSON object:
<col-umn>:<level1_element>.<level2_element>.<level3_element>.
C. use bracket notation to traverse the path in an object:
<col-umn>['<level1_element>']['<level2_element>'].
D. use Curly bracket notation to traverse the path in an object:
<col-umn>{'<level1_element>'}{'<level2_element>'}.

Answer: B,C

NEW QUESTION # 384
Find out the odd one out:

A. 1. Bulk Data Load: Load history Stored in the metadata of the target table for 365 days.
2. SnowPipe: Load history Stored in the metadata of the pipe for 64 days.
B. 1. Bulk Data Load: Requires a user-specified warehouse to execute COPY statements.
2. SnowPipe: Uses Snowflake-supplied compute resources.
C. 1. Bulk Data Load: Billed for the amount of time each virtual warehouse is active.
2. SnowPipe: Billed according to the compute resources used in the Snowpipe ware-house while loading the files.
D. 1. Bulk Data Load: Loads are always performed in a single transaction.
2. SnowPipe: Loads are combined or split into a single or multiple transactions based on the number and size of the rows in each data file.

Answer: A

Explanation:
Explanation
Bulk data load
Load History Stored in the metadata of the target table for 64 days. Available upon completion of the COPY statement as the statement output.
Snowpipe
Load History Stored in the metadata of the pipe for 14 days. Must be requested from Snowflake via a REST endpoint, SQL table function, or ACCOUNT_USAGE view.
Rest are correct statements.

NEW QUESTION # 385
A large e-commerce company manages a single S3 bucket containing product images, customer data, and marketing materials. Different departments within the company require access to specific data sets, but granting access to the entire bucket for each department poses a security risk.
What AWS service can be implemented to provide granular access control and simplify permission management for various departments while using a single S3 bucket?

A. Bucket ACLs
B. S3 Access Pointsright
C. IAM User Groups with bucket policies
D. S3 Object Ownership

Answer: B

Explanation:
S3 Access Points offer a more efficient and secure solution. You can create multiple access points for the single S3 bucket, each with a unique namespace. These access points can then be assigned specific IAM policies that grant granular access control for different departments.
Reference:
https://aws.amazon.com/s3/features/access-points/

NEW QUESTION # 386
A company stores employee data in Amazon Resdshift. A table names Employee uses columns named Region ID, Department ID, and Role ID as a compound sort key.
Which queries will MOST increase the speed of query by using a compound sort key of the table?
(Choose two.)

A. Select *from Employee where Role ID=50;
B. Select *from Employee where Region ID='North America' and Role ID=50;
C. Select *from Employee where Region ID='North America' and Department ID=20;
D. Select *from Employee where Department ID=20 and Region ID='North America';
E. Select *from Employee where Region ID='North America';

Answer: B,C

Explanation:
To maximize the speed of queries by using the compound sort key (Region ID, Department ID, and Role ID) in the Employee table in Amazon Redshift, the queries should align with the order of the columns in the sort key.

NEW QUESTION # 387
A finance company uses Amazon Redshift as a data warehouse. The company stores the data in a shared Amazon S3 bucket. The company uses Amazon Redshift Spectrum to access the data that is stored in the S3 bucket. The data comes from certified third-party data providers. Each third-party data provider has unique connection details.
To comply with regulations, the company must ensure that none of the data is accessible from outside the company's AWS environment.
Which combination of steps should the company take to meet these requirements? (Choose two.)

A. Create an AWS CloudHSM hardware security module (HSM) for each data provider. Encrypt each data provider's data by using the corresponding HSM for each data provider.
B. Turn on enhanced VPC routing for the Amazon Redshift cluster. Set up an AWS Direct Connect connection and configure a connection between each data provider and the finance company's VPC.
C. Use federated queries to access the data from each data provider. Do not upload the data to the S3 bucket. Perform the federated queries through a gateway VPC endpoint.
D. Define table constraints for the primary keys and the foreign keys.
E. Replace the existing Redshift cluster with a new Redshift cluster that is in a private subnet. Use an interface VPC endpoint to connect to the Redshift cluster. Use a NAT gateway to give Redshift access to the S3 bucket.

Answer: B,E

NEW QUESTION # 388
......

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