AUTHORITATIVE DEA-C02 EXAMINATIONS ACTUAL QUESTIONS | DEA-C02 100% FREE POSITIVE FEEDBACK

Authoritative DEA-C02 Examinations Actual Questions | DEA-C02 100% Free Positive Feedback

Authoritative DEA-C02 Examinations Actual Questions | DEA-C02 100% Free Positive Feedback

Blog Article

Tags: DEA-C02 Examinations Actual Questions, Positive DEA-C02 Feedback, Certification DEA-C02 Book Torrent, DEA-C02 New Dumps Free, DEA-C02 New Study Questions

We know students run on low budgets so we made every possible effort to reduce the pre-purchase doubts. You can easily avail of our product at an affordable price. We are aware that the syllabus of DEA-C02 exam is extremely dynamic and changes with incoming updates, so we also offer you updates for free after purchase for 1 year. We assure you in every possible way that our Snowflake DEA-C02 Exam Preparation material is the most reliable there is.

If you still worry too much about purchasing professional DEA-C02 test guide on the internet, I can tell that it is quite normal. Useful certification DEA-C02 guide materials will help your preparing half work with double results. If you consider about our DEA-C02 exam questoins quality, you can free downlaod the demo of our DEA-C02 Exam Questions. We have thought of your needs and doubts considerately on the DEA-C02 study guide. Our certification DEA-C02 guide materials are collected and compiled by experience experts who have worked in this line more than 10 years.

>> DEA-C02 Examinations Actual Questions <<

DEA-C02 Examinations Actual Questions - 2025 Snowflake DEA-C02 First-grade Positive Feedback

ActualtestPDF's Snowflake DEA-C02 Exam Training materials allows candidates to learn in the case of mock examinations. You can control the kinds of questions and some of the problems and the time of each test. In the site of ActualtestPDF, you can prepare for the exam without stress and anxiety. At the same time, you also can avoid some common mistakes. So you will gain confidence and be able to repeat your experience in the actual test to help you to pass the exam successfully.

Snowflake SnowPro Advanced: Data Engineer (DEA-C02) Sample Questions (Q115-Q120):

NEW QUESTION # 115
You are using Snowpipe to ingest data from Azure Blob Storage into a Snowflake table. You have successfully set up the pipe and configured the event notifications. However, you notice that duplicate records are appearing in your target table. After reviewing the logs, you determine that the same file is being processed multiple times by Snowpipe. Which of the following strategies can you implement to prevent duplicate data ingestion, assuming you cannot modify the source data in Azure Blob Storage to include a unique ID or timestamp?

  • A. Implement idempotent logic within a Snowflake stored procedure that is triggered by a task after the data is loaded by Snowpipe. The stored procedure should identify and remove duplicate rows based on all other columns in the table.
  • B. Modify the Azure Event Grid subscription configuration to filter events based on file size or creation time to avoid resending events for already processed files.
  • C. Use a data masking policy with the 'MASK' function to obfuscate duplicate records based on their similarity, making them effectively invisible to downstream queries.
  • D. Create a Snowflake stream on the target table and use it to incrementally load data into a separate, deduplicated table using a merge statement with conditional logic to insert or update records based on a combination of columns.
  • E. Configure the Snowpipe definition with the 'PURGE = TRUE parameter. This will ensure that each file is only processed once.

Answer: D

Explanation:
Using a Snowflake stream (C) is the most effective and scalable solution for handling duplicate data ingestion in this scenario. Streams provide change data capture (CDC) capabilities, allowing you to track changes to the target table caused by Snowpipe. By creating a stream and then using a merge statement with a combination of columns, you can identify and handle duplicates effectively during the incremental load into a separate table. Option A, while functional, would require processing the entire table after each Snowpipe load, which is not efficient for large datasets. Option B, PURGE = TRUE, is not valid for Snowpipe. Data masking does not help prevent or remove duplicate records. While Option E sounds promising, it doesn't provide guarantee of removing duplicates.


NEW QUESTION # 116
You have a Snowflake table named 'ORDERS' with columns 'ORDER D', 'CUSTOMER D', and 'ORDER JSON' (a variant column storing order details). You need to extract specific product names from the 'ORDER JSON' column for each order and return them as a table. The 'ORDER JSON' structure is an array of objects, where each object represents a product with fields like 'product_name' and 'quantity'. Which approach is the most efficient and scalable way to achieve this, considering the possibility of millions of rows in the 'ORDERS table?

  • A. Create a Java UDF that takes ORDER JSON' as input, parses it using a JSON library, extracts the product names, and returns a comma-separated string. Use a WHILE loop within the UDF to parse the JSON array.
  • B. Create a JavaScript UDF that takes ' ORDER_JSON' as input and returns an array of product names. Use 'JSON.parse()' to parse the JSON string and iterate using array methods.
  • C. Create a Python UDTF that takes 'ORDER JSON' as input, parses it, and yields a row for each product name extracted. Use LATERAL FLATTEN within the UDTF for optimized JSON processing.
  • D. Create a SQL UDF that iterates through the JSON array using SQL commands and returns a comma-separated string of product names. Then, use SPLIT TO_TABLE to convert the string to rows.
  • E. Use a standard SQL query with LATERAL FLATTEN and JSON VALUE functions to extract product names directly without using a UDF or UDTF.

Answer: C

Explanation:
Python UDTFs with LATERAL FLATTEN are the most efficient and scalable for JSON parsing in Snowflake due to their ability to leverage Snowflake's vectorized execution engine. Using LATERAL FLATTEN inside the UDTF avoids unnecessary data movement and allows for optimized JSON processing. SQL UDFs, Java UDFs, JavaScript UDFs and SQL with JSON_VALUE are generally less performant for complex JSON parsing at scale compared to Python UDTFs leveraging the Snowflake engine.


NEW QUESTION # 117
You have a table named 'sales_data' with columns 'region', 'product_category', and 'revenue'. You want to create an aggregation policy to prevent users without the 'FINANCE ADMIN' role from seeing revenue values aggregated across all regions. Instead, these users should only see revenue aggregated at the region level. The policy should return NULL for the 'revenue' column when aggregated across all regions by non-admin users. Which of the following SQL snippets correctly implements this aggregation policy?

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

Answer: C

Explanation:
Option B correctly uses the GROUPING() function to identify when the aggregation is being performed across all regions (GROUPING(region) = 1). It then returns NULL for non-FINANCE_ADMIN users in this scenario. Options A is incorrect because grouping(region) = 0 means region-level aggregation. Options C does not consider regions in the policy, so non-admin users will always see null revenue. Option D's syntax is incorrect. must be combined with GROUPING as in E to work correctly. Option E can also work but the CASE statement is clearer and easier to understand.


NEW QUESTION # 118
You are troubleshooting a slowly performing query in Snowflake that aggregates data from a large ORDERS table (10 billion rows) partitioned by ORDER DATE. The query execution plan shows significant 'Remote Spill to Disk'. Which of the following actions would be MOST effective in reducing the spill and improving query performance? Assume all statistics are up-to-date and the data is properly clustered by ORDER_DATE.

  • A. Increase the value of the parameter. This allows the warehouse to scale up further if needed.
  • B. Reduce the number of columns selected in the query, only selecting those that are essential for the aggregation.
  • C. Optimize the query to leverage data pruning based on ORDER DATE by ensuring the query filters on a specific or limited range of ORDER DATE values.
  • D. Increase the virtual warehouse size. This will provide more memory for the query to execute.
  • E. Rewrite the query to use window functions instead of aggregate functions.

Answer: C

Explanation:
Remote Spill to Disk indicates that Snowflake is running out of memory to process the query. Increasing the virtual warehouse size (A) can help, but focusing on data pruning (E) is often more effective. By filtering on ORDER_DATE, you drastically reduce the amount of data that needs to be processed, minimizing memory usage and the need to spill to disk. Options B, C, and D are less likely to directly address the spill issue. doesn't exist. Window functions don't inherently resolve spills. Reducing selected columns can help slightly but is usually less impactful than data pruning.


NEW QUESTION # 119
Which of the following statements are true regarding data masking policies in Snowflake? (Select all that apply)

  • A. Different masking policies cannot be applied to different columns within the same table.
  • B. Data masking policies can be applied to both tables and views.
  • C. Data masking policies are supported on external tables.
  • D. The 'CURRENT_ROLE()' function can be used within a masking policy to implement role-based data masking.
  • E. Once a masking policy is applied to a column, the original data is permanently altered.

Answer: B,C,D

Explanation:
A and D are correct. Masking policies can be applied to tables and views, and the function is essential for implementing role-based masking. B is incorrect because masking policies apply dynamically at query time and don't alter the underlying data. C is incorrect; different policies can be applied to different columns. E is correct, Data masking policies are also supported on external tables.


NEW QUESTION # 120
......

We aim to provide the best service for our customers, and we demand our after sale service staffs to the highest ethical standard, and our DEA-C02 study guide and compiling processes will be of the highest quality. We play an active role in making every country and community in which we selling our DEA-C02 practice test a better place to live and work. Therefore, our responsible after sale service staffs are available in twenty four hours a day, seven days a week. That is to say, if you have any problem after DEA-C02 Exam Materials purchasing, you can contact our after sale service staffs anywhere at any time.

Positive DEA-C02 Feedback: https://www.actualtestpdf.com/Snowflake/DEA-C02-practice-exam-dumps.html

We are sure, all the aspiring potential professionals are intended to attempt DEA-C02 exam dumps to update their credentials, We know your needs, and we will help you gain confidence to pass the Snowflake DEA-C02 exam, Snowflake DEA-C02 Dumps Book - The talent is everywhere in modern society, Snowflake DEA-C02 Examinations Actual Questions In this competitive society, being good at something is able to take up a large advantage, especially in the IT industry.

Dodging and burning, adding textures, transforming Positive DEA-C02 Feedback a location, and using the power of gray" for composites, The Ball: Basic Movement, We are sure, all the aspiring potential professionals are intended to attempt DEA-C02 Exam Dumps to update their credentials.

100% Pass 2025 Snowflake Useful DEA-C02: SnowPro Advanced: Data Engineer (DEA-C02) Examinations Actual Questions

We know your needs, and we will help you gain confidence to pass the Snowflake DEA-C02 exam, Snowflake DEA-C02 Dumps Book - The talent is everywhere in modern society.

In this competitive society, being good at something DEA-C02 is able to take up a large advantage, especially in the IT industry, Use the Snowflake DEA-C02 exam practice software for practicing the actual questions of DEA-C02 exam in the real exam environment.

Report this page