Eric Lewis Eric Lewis's Profile Page

Eric Lewis Eric Lewis

0 Course Enrolled • 0 Course Completed

Biography

DEA-C02試験攻略、DEA-C02試験復習

2025年ShikenPASSの最新DEA-C02 PDFダンプおよびDEA-C02試験エンジンの無料共有：https://drive.google.com/open?id=1E4OP90g6QuA5HvOhwKEOeYcYhWvqa5O-

複雑な知識が簡素化され、学習内容が習得しやすいDEA-C02テストトレントのセットを提供します。これにより、貴重な時間を制限しながら、より重要な知識を獲得できます。当社のDEA-C02ガイドトレントには、計時機能とシミュレーションテスト機能が装備されています。タイムキーパーを設定して、速度を調整し、効率を改善するために注意を払うのに役立ちます。当社の専門家チームは、DEA-C02認定トレーニングでDEA-C02試験を準備するのに20〜30時間しかかからない非常に効率的なトレーニングプロセスを設計しました。

あなたはDEA-C02試験に不安を持っていますか？DEA-C02参考資料をご覧下さい。私たちのDEA-C02参考資料は十年以上にわたり、専門家が何度も練習して、作られました。あなたに高品質で、全面的なDEA-C02参考資料を提供することは私たちの責任です。私たちより、DEA-C02試験を知る人はいません。

>> DEA-C02試験攻略 <<

無料ダウンロードDEA-C02試験攻略: SnowPro Advanced: Data Engineer (DEA-C02)合格

DEA-C02試験問題を購入すると、DEA-C02学習ツールの24時間オンラインサービスが提供されます。ご不明な点がございましたら、電子メールをお送りください。私たちはあなたにフィードバックを迅速に提供し、問題の解決を心からお手伝いします。 Googleのスペシャリストは、DEA-C02学習ツールに更新があるかどうかを毎日確認しています。更新システムがある場合は、自動的に送信されます。したがって、DEA-C02テストトレントが最新の知識を持ち、変化のペースに追いつくことを保証できます。

Snowflake SnowPro Advanced: Data Engineer (DEA-C02) 認定 DEA-C02 試験問題 (Q327-Q332):

質問 # 327
Consider a scenario where you have a Snowflake external table 'ext_logs' pointing to log files in an S3 bucket. The log files are continuously being updated, and new files are added frequently. You want to ensure that your external table always reflects the latest data available in S3. Which of the following actions and configurations are required or recommended to keep the external table synchronized with the underlying data source? (Select all that apply)

A. Implement a stored procedure that periodically executes a query on the external table to force a metadata refresh.
B. Enable auto-refresh on the external table using the 'AUTO_REFRESH = TRUE parameter during creation.
C. Periodically execute the 'ALTER EXTERNAL TABLE ext_logs REFRESH' command to update the metadata about the files in S3.
D. Create a Snowpipe that continuously loads data from the S3 bucket into a Snowflake table instead of using an external table.
E. Configure an event notification service (e.g., AWS SQS) to trigger an external table refresh whenever new files are added to S3.

正解：B、C、E

解説：
Enabling 'AUTO_REFRESH = TRUE (A) automatically refreshes the metadata. Executing 'ALTER EXTERNAL TABLE . REFRESH' (B) manually updates the metadata. Configuring event notifications (C) allows near real-time updates when new files are added. Snowpipe loads data into a Snowflake table, not an external table (D). A stored procedure executing queries doesn't guarantee metadata refresh (E).

質問 # 328
Which of the following statements are TRUE regarding Snowflake's Fail-safe mechanism and its relation to Time Travel? (Select all that apply)

A. Fail-safe provides a historical data retention period of 7 days, similar to the default Time Travel setting.
B. The Fail-safe period starts immediately after the Time Travel retention period ends.
C. Users can query data directly from Fail-safe using SQL commands if Time Travel is insufficient.
D. Fail-safe is automatically enabled for all Snowflake accounts and requires no configuration.
E. Fail-safe is exclusively used by Snowflake to recover data in the event of a catastrophic system failure, and users have no direct access.

正解：B、D、E

解説：
Fail-safe is automatically enabled and managed by Snowflake (B). It kicks in after Time Travel (C) and is not directly accessible to users (E). Users cannot query data from Fail-safe using SQL commands. Fail-safes duration depends on the Snowflake Edition but not for the same days as time travel.

質問 # 329
You are working with a Snowpark DataFrame named 'customer data' that contains sensitive Personally Identifiable Information (PII). The DataFrame has columns such as 'customer id', 'name', 'email' , and 'phone number'. Your task is to create a new DataFrame that only contains 'customer id' and a hash of the 'email' address for anonymization purposes, while also filtering out any customers whose 'customer id' starts with 'TEMP'. Which of the following approaches adheres to best practices for data security and efficiency in Snowpark, using secure hashing algorithms provided by Snowflake?

A. Option B
B. Option C
C. Option E
D. Option A
E. Option D

正解：E

解説：
Option D is the most appropriate. 'sha2 with a bit length of 256 or higher (like 256 in this example) is a strong cryptographic hash function suitable for anonymizing sensitive data. The 'where' function is used with the negation of the 'startswith' function (through column reference 'col()'), so it appropriately filters out customer IDs starting with 'TEMP. Using 'select' projects only the necessary columns, minimizing the risk of exposing other PII data. Option A utilizes the 'filter' and provides the correct filter. Option C attempts to utilize However, cache_result() is not suitable for this task. Option B, however, is suboptimal because MD5 is considered cryptographically broken and should not be used for security-sensitive applications. Options A and E are technically correct in filtering out customer IDs. They are not as clear as Option D. The code will accomplish the objective of the question but not clearly show which customer IDs will be retained.

質問 # 330
A data engineer is facing performance issues with a complex analytical query in Snowflake. The query joins several large tables and uses multiple window functions. The query profile indicates that a significant amount of time is spent in the 'Remote Spill' stage. This means the data from one of the query stages is spilling to the remote disk. What are the possible root causes for 'Remote Spill' and what steps can be taken to mitigate this issue? Select two options.

A. The query is using a non-optimal join strategy. Review the query profile and consider using join hints to force a different join order or algorithm.
B. The virtual warehouse is not appropriately sized for the volume of data and complexity of the query. Increasing the virtual warehouse size might provide sufficient memory to avoid spilling.
C. The window functions are operating on large partitions of data, exceeding the available memory on the compute nodes. Try to reduce the partition size by pre- aggregating the data or using filtering before applying the window functions.
D. The data being queried is stored in a non-Snowflake database, making it difficult to optimize the join.
E. The 'Remote Spill' indicates network latency issues between compute nodes. There is nothing the data engineer can do to fix this; it is an infrastructure issue.

正解：B、C

解説：
Options A and D are the correct root causes and solutions for remote spill. Remote spill indicates that a query stage is exceeding the available memory on the compute node, and the overflow data is written to remote storage (usually S3 for Snowflake). Option A addresses this by increasing the warehouse size. Option D addresses the root cause by suggesting a reduction in the amount of data being processed by the window functions. Option B could help but does not directly address the spill. Option C is unlikely as Snowflake manages the network internally, and while network issues could exist, it's not the first thing to troubleshoot. Option E is unlikely since Snowflake only queries data within Snowflake itself, unless its connecting to external tables.

質問 # 331
You are designing a data protection strategy for a Snowflake environment that processes sensitive payment card industry (PCI) data'. You decide to use a combination of column-level security and external tokenization. Which of the following statements are TRUE regarding the advantages of using both techniques together? (Select TWO)

A. The use of both techniques increases query performance drastically.
B. Masking policies and external tokenization provide independent layers of security. If one is compromised, the other still provides protection.
C. Column-level security can be used to restrict access to the tokenization UDF itself, ensuring that only authorized users can perform tokenization or detokenization operations.
D. Tokenization ensures compliance with PCl DSS standards, while masking policies are primarily useful for internal access control and obfuscation for development environments. Using both doesn't increase security.
E. Combining masking policies and external tokenization allows for complete elimination of PCl data from the Snowflake environment, even during processing.

正解：B、C

解説：
Combining masking policies and external tokenization provides defense in depth. Masking policies control who can see sensitive data (or a masked version), while tokenization replaces the actual data with a non-sensitive representation. This means that even if a user bypasses the masking policy (e.g., through a vulnerability), they still won't see the actual PCl data. Also, you can use column-level security to control access to the tokenization and detokenization functions. Option A is incorrect, sensitive data exists until tokenized. Option C is incorrect as using both techniques strengthens security. Option E is Incorrect, as both the techniques impact query performance

質問 # 332
......

あらゆる種類の問題に取り組まれる可能性があります。時には、何かを下に置いて他の問題に対処する必要があります。後者はより緊急であり、すぐに実行する必要があります。 DEA-C02トレーニングガイドの助けを借りて、あなたの夢がもう遅れることはありません。なぜなら、私たちはクライアントがよりゆっくりと勉強するのを支援するインテリジェントなアプリケーションと高効率のメリットを持っているからです。 DEA-C02の実際の試験で20〜30時間準備する場合、DEA-C02試験はあなたの前で簡単になります。

DEA-C02試験復習: https://www.shikenpass.com/DEA-C02-shiken.html

受験者たちは使用してからDEA-C02試験に高いポイントを得られます、我々の問題集を通して、あなたはDEA-C02試験で高い成績を取れると信じています、DEA-C02試験にすばやく合格できるようにする必要があるため、信頼できる製品を選択する必要があります、Snowflake DEA-C02試験攻略 3. 1年間のカスタマーサービスを提供します、DEA-C02試験問題は毎日更新されます、DEA-C02試験問題には他にも多くの利点があります、また、一生懸命勉強して、資格試験に合格し、DEA-C02証明書を取得することは、もはや夢ではありません、Snowflake DEA-C02試験攻略それで、我々は異なる製品を提供し、顧客の要求を満たします。

近づいたら投げるからね、結局のところ、コロケーション施設はどれほど印象的でしょうか、受験者たちは使用してからDEA-C02試験に高いポイントを得られます、我々の問題集を通して、あなたはDEA-C02試験で高い成績を取れると信じています。

最高-ユニークなDEA-C02試験攻略試験-試験の準備方法DEA-C02試験復習

DEA-C02試験にすばやく合格できるようにする必要があるため、信頼できる製品を選択する必要があります、3. 1年間のカスタマーサービスを提供します、DEA-C02試験問題は毎日更新されます。

P.S.ShikenPASSがGoogle Driveで共有している無料の2025 Snowflake DEA-C02ダンプ：https://drive.google.com/open?id=1E4OP90g6QuA5HvOhwKEOeYcYhWvqa5O-

Eric Lewis Eric Lewis

Biography

2024 Online Education