Snowflake ARA-C01技術試験、ARA-C01練習問題集

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テストの準備に多くの時間を費やし、それでも何度も失敗するのは馬鹿げていますか？一部の受験者は、Snowflake ARA-C01試験ダンプ問題で簡単に試験に合格しますか？試験に合格し、認定を取得することが目標である場合、ARA-C01試験ダンプは、目標を簡単に達成するのに役立ちます。選択してみませんか？ ARA-C01試験ダンプ問題を含むテストの前にわずか数十のお金と20〜35時間の有効な準備で、確実に試験をクリアできます。では、なぜあなたは無駄な努力をするのに多くの時間を無駄にしているのですか？

Snowflake ARA-C01試験は、Snowflakeのクラウドデータプラットフォームとその様々なコンポーネントに深い理解を持つことが求められる厳しいテストです。試験は、スケーラブルで高性能かつコスト効果の高いソリューションを設計・実装する能力を試します。

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Snowflake SnowPro Advanced Architect Certification 認定 ARA-C01 試験問題 (Q60-Q65):

質問 # 60
When using the copy into <table> command with the CSV file format, how does the match_by_column_name parameter behave?

A. The command will return an error.
B. The command will return a warning stating that the file has unmatched columns.
C. It expects a header to be present in the CSV file, which is matched to a case-sensitive table column name.
D. The parameter will be ignored.

正解：C

質問 # 61
A healthcare company is deploying a Snowflake account that may include Personal Health Information (PHI).
The company must ensure compliance with all relevant privacy standards.
Which best practice recommendations will meet data protection and compliance requirements? (Choose three.)

A. Use the External Tokenization feature to obfuscate sensitive data.
B. Avoid sharing data with partner organizations.
C. Rewrite SQL queries to eliminate projections of PHI data based on current_role().
D. Use, at minimum, the Business Critical edition of Snowflake.
E. Use the Internal Tokenization feature to obfuscate sensitive data.
F. Create Dynamic Data Masking policies and apply them to columns that contain PHI.

正解：A、D、F

解説：
* A healthcare company that handles PHI data must ensure compliance with relevant privacy standards, such as HIPAA, HITRUST, and GDPR. Snowflake provides several features and best practices to help customers meet their data protection and compliance requirements1.
* One best practice recommendation is to use, at minimum, the Business Critical edition of Snowflake. This edition provides the highest level of data protection and security, including end-to-end encryption with customer-managed keys, enhanced object-level security, and HIPAA and HITRUST compliance2. Therefore, option A is correct.
* Another best practice recommendation is to create Dynamic Data Masking policies and apply them to columns that contain PHI. Dynamic Data Masking is a feature that allows masking or redacting sensitive data based on the current user's role. This way, only authorized users can view the unmasked data, while others will see masked values, such as NULL, asterisks, or random characters3. Therefore, option B is correct.
* A third best practice recommendation is to use the External Tokenization feature to obfuscate sensitive data. External Tokenization is a feature that allows replacing sensitive data with tokens that are
* generated and stored by an external service, such as Protegrity. This way, the original data is never stored or processed by Snowflake, and only authorized users can access the tokenized data through the external service4. Therefore, option D is correct.
* Option C is incorrect, because the Internal Tokenization feature is not available in Snowflake. Snowflake does not provide any native tokenization functionality, but only supports integration with external tokenization services4.
* Option E is incorrect, because rewriting SQL queries to eliminate projections of PHI data based on current_role() is not a best practice. This approach is error-prone, inefficient, and hard to maintain. A better alternative is to use Dynamic Data Masking policies, which can automatically mask data based on the user's role without modifying the queries3.
* Option F is incorrect, because avoiding sharing data with partner organizations is not a best practice.
Snowflake enables secure and governed data sharing with internal and external consumers, such as business units, customers, or partners. Data sharing does not involve copying or moving data, but only granting access privileges to the shared objects. Data sharing can also leverage Dynamic Data Masking and External Tokenization features to protect sensitive data5.
References: : Snowflake's Security & Compliance Reports : Snowflake Editions : Dynamic Data Masking : External Tokenization : Secure Data Sharing

質問 # 62
A company has a Snowflake account named ACCOUNTA in AWS us-east-1 region. The company stores its marketing data in a Snowflake database named MARKET_DB. One of the company's business partners has an account named PARTNERB in Azure East US 2 region. For marketing purposes the company has agreed to share the database MARKET_DB with the partner account.
Which of the following steps MUST be performed for the account PARTNERB to consume data from the MARKET_DB database?

A. Create a new account (called AZABC123) in Azure East US 2 region. From account ACCOUNTA create a share of database MARKET_DB, create a new database out of this share locally in AWS us-east-1 region, and replicate this new database to AZABC123 account. Then set up data sharing to the PARTNERB account.
B. Create a share of database MARKET_DB, and create a new database out of this share locally in AWS us-east-1 region. Then replicate this database to the partner's account PARTNERB.
C. From account ACCOUNTA create a share of database MARKET_DB, and create a new database out of this share locally in AWS us-east-1 region. Then make this database the provider and share it with the PARTNERB account.
D. Create a new account (called AZABC123) in Azure East US 2 region. From account ACCOUNTA replicate the database MARKET_DB to AZABC123 and from this account set up the data sharing to the PARTNERB account.

正解：D

質問 # 63
What is the MOST efficient way to design an environment where data retention is not considered critical, and customization needs are to be kept to a minimum?

A. Use a temporary table.
B. Use a transient database.
C. Use a transient table.
D. Use a transient schema.

正解：B

質問 # 64
An Architect has been asked to clone schema STAGING as it looked one week ago, Tuesday June 1st at 8:00 AM, to recover some objects.
The STAGING schema has 50 days of retention.
The Architect runs the following statement:
CREATE SCHEMA STAGING_CLONE CLONE STAGING at (timestamp => '2021-06-01 08:00:00'); The Architect receives the following error: Time travel data is not available for schema STAGING. The requested time is either beyond the allowed time travel period or before the object creation time.
The Architect then checks the schema history and sees the following:
CREATED_ON|NAME|DROPPED_ON
2021-06-02 23:00:00 | STAGING | NULL
2021-05-01 10:00:00 | STAGING | 2021-06-02 23:00:00
How can cloning the STAGING schema be achieved?

A. Rename the STAGING schema and perform an UNDROP to retrieve the previous STAGING schema version, then run the CLONE statement.
B. Undrop the STAGING schema and then rerun the CLONE statement.
C. Modify the statement: CREATE SCHEMA STAGING_CLONE CLONE STAGING at (timestamp => '2021-05-01 10:00:00');
D. Cloning cannot be accomplished because the STAGING schema version was not active during the proposed Time Travel time period.

正解：A

解説：
The error message indicates that the schema STAGING does not have time travel data available for the requested timestamp, because the current version of the schema was created on 2021-06-02 23:00:00, which is after the timestamp of 2021-06-01 08:00:00. Therefore, the CLONE statement cannot access the historical data of the schema at that point in time.
Option A is incorrect, because undropping the STAGING schema will not restore the previous version of the schema that was active on 2021-06-01 08:00:00. Instead, it will create a new version of the schema with the same name and no data or objects.
Option B is incorrect, because modifying the timestamp to 2021-05-01 10:00:00 will not clone the schema as it looked one week ago, but as it looked when it was first created. This may not reflect the desired state of the schema and its objects.
Option C is correct, because renaming the STAGING schema and performing an UNDROP to retrieve the previous STAGING schema version will restore the schema that was dropped on 2021-06-02 23:00:00. This schema has time travel data available for the requested timestamp of 2021-06-01 08:00:00, and can be cloned using the CLONE statement.
Option D is incorrect, because cloning can be accomplished by using the UNDROP command to access the previous version of the schema that was active during the proposed time travel period.

質問 # 65
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