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Snowflake DEA-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 3	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 4	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 5	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.

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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q312-Q317):

NEW QUESTION # 312
Which column provides information when the stream became stale or may become stale if not con-sumed?

A. STALE_STREAM_PERIOD
B. STALE_PERIOD_AFTER
C. STREAM_STALE_PERIOD
D. STALE_AFTER

Answer: D

Explanation:
Explanation
execute SHOW STREAMS command.
Column Name: STALE_AFTER
Timestamp when the stream became stale or may become stale if not consumed. The value is calcu-lated by adding the retention period for the source table (i.e. the larger of the DA-TA_RETENTION_TIME_IN_DAYS or MAX_DATA_EXTENSION_TIME_IN_DAYS parame-ter setting) to the last time the stream was read.

NEW QUESTION # 313
A company stores customer data tables that include customer addresses in an AWS Lake Formation data lake. To comply with new regulations, the company must ensure that users cannot access data for customers who are in Canada.
The company needs a solution that will prevent user access to rows for customers who are in Canada.
Which solution will meet this requirement with the LEAST operational effort?

A. Create an IAM role that restricts user access to an address where the country is Canada.
B. Apply a tag to all rows where Canada is the country. Prevent user access where the tag is equal to "Canada".
C. Set a row-level filter to prevent user access to a row where the country is Canada.
D. Set a column-level filter to prevent user access to a row where the country is Canada.

Answer: C

NEW QUESTION # 314
For enabling non-ACCOUNTADMIN Roles to Perform Data Sharing Tasks, which two glob-al/account privileges snowflake provide?

A. CREATE SHARE
B. REFERENCE USAGE
C. OPERATE
D. IMPORT SHARE

Answer: A,D

Explanation:
Explanation
CREATE SHARE
In a provider account, this privilege enables creating and managing shares (for sharing data with consumer accounts).
IMPORT SHARE
In a consumer account, this privilege enables viewing the inbound shares shared with the account. Also enables creating databases from inbound shares; requires the global CREATE DATABASE privilege.
By default, these privileges are granted only to the ACCOUNTADMIN role, ensuring that only ac-count administrators can perform these tasks. However, the privileges can be granted to other roles, enabling the tasks to be delegated to other users in the account.

NEW QUESTION # 315
An airline company is collecting metrics about flight activities for analytics. The company is conducting a proof of concept (POC) test to show how analytics can provide insights that the company can use to increase on-time departures.
The POC test uses objects in Amazon S3 that contain the metrics in .csv format. The POC test uses Amazon Athena to query the data. The data is partitioned in the S3 bucket by date.
As the amount of data increases, the company wants to optimize the storage solution to improve query performance.
Which combination of solutions will meet these requirements? (Choose two.)

A. Add a randomized string to the beginning of the keys in Amazon S3 to get more throughput across partitions.
B. Preprocess the .csv data to JSON format by fetching only the document keys that the query requires.
C. Use an S3 bucket that is in the same account that uses Athena to query the data.
D. Preprocess the .csv data to Apache Parquet format by fetching only the data blocks that are needed for predicates.
E. Use an S3 bucket that is in the same AWS Region where the company runs Athena queries.

Answer: D,E

Explanation:
https://docs.aws.amazon.com/athena/latest/ug/performance-tuning.html

NEW QUESTION # 316
A company runs multiple applications on AWS. The company configured each application to output logs. The company wants to query and visualize the application logs in near real time.
Which solution will meet these requirements?

A. Configure the applications to output logs to Amazon CloudWatch Logs log groups. Create an Amazon S3 bucket. Create an AWS Lambda function that runs on a schedule to export the required log groups to the S3 bucket. Use Amazon Athena to query the log data in the S3 bucket.
B. Configure the applications to output logs to Amazon CloudWatch Logs log groups. Use CloudWatch log anomaly detection to query and visualize the log data.
C. Create an Amazon OpenSearch Service domain. Configure the applications to output logs to Amazon CloudWatch Logs log groups. Create an OpenSearch Service subscription filter for each log group to stream the data to OpenSearch. Create the required queries and dashboards in OpenSearch Service to analyze and visualize the data.
D. Update the application code to send the log data to Amazon QuickSight by using Super-fast, Parallel, In-memory Calculation Engine (SPICE).Create the required analyses and dashboards in QuickSight.

Answer: C

Explanation:
By streaming your CloudWatch Logs log groups directly into an Amazon OpenSearch Service domain via subscription filters, you get near-real-time indexing and can build Kibana dashboards for querying and visualization with virtually no batching delays. This fully managed pipeline minimizes custom glue code and meets your requirements with low operational overhead.

NEW QUESTION # 317
......

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