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IT업계 종사자라면 누구나 Snowflake 인증DEA-C02시험을 패스하고 싶어하리라고 믿습니다. 많은 분들이 이렇게 좋은 인증시험은 아주 어렵다고 생각합니다. 네 맞습니다. 패스할 확율은 아주 낮습니다. 노력하지 않고야 당연히 불가능한 일이 아니겠습니까? Snowflake 인증DEA-C02 시험은 기초 지식 그리고 능숙한 전업지식이 필요 합니다. Fast2test는 여러분들한테Snowflake 인증DEA-C02시험을 쉽게 빨리 패스할 수 있도록 도와주는 사이트입니다. Fast2test의Snowflake 인증DEA-C02시험관련 자료로 여러분은 짧은 시간내에 간단하게 시험을 패스할수 있습니다. 시간도 절약하고 돈도 적게 들이는 이런 제안은 여러분들한테 딱 좋은 해결책이라고 봅니다.
Snowflake인증 DEA-C02시험준비중이신 분들은Snowflake인증 DEA-C02시험통과가 많이 어렵다는것을 알고 있을것입니다. 학교공부하랴,회사다니랴 자격증공부까지 하려면 너무 많은 정력과 시간이 필요할것입니다. 그렇다고 자격증공부를 포기하면 자신의 위치를 찾기가 힘들것입니다. Fast2test 덤프는 IT인증시험을 대비하여 제작된것이므로 시험적중율이 높아 다른 시험대비공부자료보다 많이 유용하기에 IT자격증을 취득하는데 좋은 동반자가 되어드릴수 있습니다. Fast2test 덤프를 사용해보신 분들의 시험성적을 통계한 결과 시험통과율이 거의 100%에 가깝다는 놀라운 결과를 얻었습니다.
IT자격증을 많이 취득하여 IT업계에서 자신만의 단단한 자리를 보장하는것이 여러분들의 로망이 아닐가 싶습니다. Fast2test의 완벽한 Snowflake인증 DEA-C02덤프는 IT전문가들이 자신만의 노하우와 경험으로 실제Snowflake인증 DEA-C02시험문제에 대비하여 연구제작한 완벽한 작품으로서 100%시험통과율을 보장합니다.
질문 # 141
A Data Engineer needs to implement dynamic data masking for a PII column named in a table 'CUSTOMERS. The masking policy should apply only to users with the role 'ANALYST. If the user is not an 'ANALYST, the full 'EMAIL' address should be displayed. Which of the following is the MOST efficient and secure way to achieve this using Snowflake's masking policies?
정답：A
설명：
Using is the most efficient and recommended approach for checking a user's active role within a masking policy. It avoids unnecessary parsing or string comparisons. It directly checks if the role is active in the current session, providing a clear and performant check. The other options either rely on string comparisons, which can be less reliable, or are overly complex and inefficient ways to determine role membership.
질문 # 142
You have a requirement to continuously load data from a cloud storage location into a Snowflake table. The source data is in Avro format and is being appended to the cloud storage location frequently. You want to automate this process using Snowpipe. You've already created the Snowpipe and the associated stage and file format. However, you notice that some files are being skipped during the ingestion process, and data is missing in your Snowflake table. What is the MOST likely reason for this issue, assuming all necessary permissions and configurations (stage, file format, pipe definition) are correctly set up?
정답：E
설명：
Option D is the most likely reason. Snowpipe relies on cloud storage event notifications (e.g., SQS for AWS S3, Event Grid for Azure Blob Storage, Pub/Sub for Google Cloud Storage) to trigger data ingestion. If these notifications are not properly configured, Snowpipe will not be notified of new files being added to the storage location, resulting in skipped files. Option A is possible, but less likely if the pipe was just created and initial data loading is failing. Option B is incorrect; Snowpipe detects files based on event notifications, not by continuously scanning the storage location. Option C could be an issue, but the question states the file format is defined. Option E is incorrect; Snowpipe does support Avro format.
질문 # 143
A large e-commerce company is experiencing performance issues with its daily sales report queries. These queries aggregate data from a fact table 'SALES FACT (100 billion rows) and several dimension tables, including 'CUSTOMER DIM', 'PRODUCT DIM', and 'DATE DIM'. The queries are run every morning and are essential for business decision-making. The team has identified that the 'SALES FACT table's primary key is 'SALE ID, but the queries frequently filter and join on 'CUSTOMER and 'PRODUCT ID. You want to use query acceleration service for these reports without changing query logic. Which combination of actions will MOST effectively leverage query acceleration service, assuming sufficient credits?
정답：C
설명：
Enabling search optimization on and in the 'SALES FACT table is the most effective approach for query acceleration in this scenario. This allows Snowflake to efficiently find the rows needed for the reports without scanning the entire table. Automatic Clustering improves data organization, but it doesn't directly accelerate individual queries in the same way. Materialized views are also useful, but require additional storage and maintenance. Simply increasing the warehouse size and enabling query acceleration without addressing the data organization or indexing might not be as cost-effective. Clustering dimension tables won't affect the performance on the large fact table.
질문 # 144
You need to implement both a row access policy and a dynamic data masking policy on the 'EMPLOYEE table in Snowflake. The requirements are as follows: 1. Employees should only be able to see their own record in the 'EMPLOYEE table. 2. The 'SALARY' column should be masked for all employees except those with the 'HR ADMIN' role. Unmasked values are required for compliance reasons, they need to be available for 'HR ADMIN' role. Given the following table structure: CREATE TABLE EMPLOYEE ( EMPLOYEE ID INT, EMPLOYEE NAME STRING, SALARY NUMBER, EMAIL STRING ) ; Which of the following sets of steps correctly implement the row access policy and dynamic data masking policy?
정답：A
설명：
Option B implements both policies correctly. The row access policy correctly checks if the 'EMPLOYEE ID matches the 'CURRENT_USER()'. Although the use of is not correct in this situation, it is being used with 'employee_id' so can only see his own record in the 'EMPLOYEE table. The masking policy uses 'CURRENT correctly to check if the role in the session is 'HR_ADMIN'. If it is, the original salary value is returned; otherwise, it masks it to Other masking policy options will return a string representation ("MASKED") or return a hash of the value, which is not a valid 'NUMBER. Option A uses IS ROLE IN SESSION rather than CURRENT_ROLE. 'CURRENT_ROLE only returns the primary role used to initialize the session whereas will return TRUE if the role is the primary role or any of the active secondary roles in the current session.
질문 # 145
A data pipeline ingests clickstream data from various sources into a raw Snowflake table CRAW CLICKS). A transformation job then processes this data and loads it into a more structured 'CLICK EVENTS table, performing filtering, cleaning, and data enrichment. The data engineering team notices significant performance bottlenecks during this transformation process, leading to data freshness issues.
The team wants to optimize this process, considering the following:
정답：B,C,D
설명：
Implementing CDC reduces the amount of data processed. Materialized views pre-compute results, avoiding repeated transformations. Optimizing SQL queries improves the efficiency of the transformation logic. Using a larger warehouse helps, but doesn't address the fundamental issue of processing unnecessary data. Breaking the transformation job into smaller jobs may add overhead and complexity without a clear performance benefit. Partitioning is a database term and clustering is snowflake, the question relates to snowflake.
질문 # 146
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Snowflake DEA-C02인증시험패스는 아주 어렵습니다. 자기에맞는 현명한 학습자료선택은 성공을 내딛는 첫발입니다. 퍼펙트한 자료만의 시험에 성공할수 있습니다. Pass4Tes시험문제와 답이야 말로 퍼펙트한 자료이죠. 우리Snowflake DEA-C02인증시험자료는 100%보장을 드립니다. 또한 구매 후 일년무료 업데이트버전을 받을 수 있는 기회를 얻을 수 있습니다.
DEA-C02높은 통과율 공부자료: https://kr.fast2test.com/DEA-C02-premium-file.html
DEA-C02덤프는 pdf버전과 온라인버전으로 되어있는데 pdf버전은 출력가능하고 온라인버전은 휴대폰에서도 사용가능합니다, Snowflake DEA-C02시험패스 가능 덤프공부 덤프는 pdf파일과 온라인서비스로 되어있는데 pdf버전은 출력가능하고 온라인버전은 휴대폰에서도 작동가능합니다, 이는 응시자가 확실하고도 빠르게 DEA-C02 시험출제 경향을 마스터하고 SnowPro Advanced: Data Engineer (DEA-C02)시험을 패스할수 있도록 하는 또 하나의 보장입니다, Snowflake DEA-C02시험패스 가능 덤프공부 IT업계에서는 이미 많이 알려 져있습니다, 뿐만 아니라 Fast2test DEA-C02높은 통과율 공부자료에서는한국어 온라인서비스상담, 구매후 일년무료업데이트서비스, 불합격받을수 환불혹은 덤프교환 등탄탄한 구매후 서비스를 제공해드립니다.
나뿐만 아니라 천하 모든 무림인이 그렇게 생각할 거요, 그래서 미안하다고 했잖아, DEA-C02덤프는 pdf버전과 온라인버전으로 되어있는데 pdf버전은 출력가능하고 온라인버전은 휴대폰에서도 사용가능합니다, 덤DEA-C02프는 pdf파일과 온라인서비스로 되어있는데 pdf버전은 출력가능하고 온라인버전은 휴대폰에서도 작동가능합니다.
이는 응시자가 확실하고도 빠르게 DEA-C02 시험출제 경향을 마스터하고 SnowPro Advanced: Data Engineer (DEA-C02)시험을 패스할수 있도록 하는 또 하나의 보장입니다, IT업계에서는 이미 많이 알려 져있습니다, 뿐만 아니라 Fast2test에서는한국어DEA-C02시험패스온라인서비스상담, 구매후 일년무료업데이트서비스, 불합격받을수 환불혹은 덤프교환 등탄탄한 구매후 서비스를 제공해드립니다.
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