1. Home
  2. Snowflake
  3. Snowflake SnowPro Certification
  4. DEA-C01 Exam Info

Snowflake DEA-C01 Exam Questions - Navigate Your Path to Success

The Snowflake SnowPro Advanced: Data Engineer Certification Exam (DEA-C01) exam is a good choice and if the candidate manages to pass Snowflake SnowPro Advanced: Data Engineer Certification Exam, he/she will earn Snowflake SnowPro Certification, Snowflake SnowPro Advanced Certifications. Below are some essential facts for Snowflake DEA-C01 exam candidates:

  • TrendyCerts offers 65 Questions that are based on actual Snowflake DEA-C01 syllabus.
  • Our Snowflake DEA-C01 Exam Practice Questions were last updated on: Mar 05, 2025

Sample Questions for Snowflake DEA-C01 Exam Preparation

Question 1

A company built a sales reporting system with Python, connecting to Snowflake using the Python Connector. Based on the user's selections, the system generates the SQL queries needed to fetch the data for the report First it gets the customers that meet the given query parameters (on average 1000 customer records for each report run) and then it loops the customer records sequentially Inside that loop it runs the generated SQL clause for the current customer to get the detailed data for that customer number from the sales data table

When the Data Engineer tested the individual SQL clauses they were fast enough (1 second to get the customers 0 5 second to get the sales data for one customer) but the total runtime of the report is too long

How can this situation be improved?

Correct : D

This option is the best way to improve the situation, as using a loop construct to run SQL queries for each customer is very inefficient and slow. Instead, the report should be rewritten to use a single SQL query that joins the customer and sales data tables and applies the query parameters as filters. This way, the report can leverage Snowflake's parallel processing and optimization capabilities and reduce the network overhead and latency.


Options Selected by Other Users:
Question 2

A Data Engineer is evaluating the performance of a query in a development environment.

DEA-C01 Exam Question 2 Exhibit 1

Based on the Query Profile what are some performance tuning options the Engineer can use? (Select TWO)

Correct : A, C

The performance tuning options that the Engineer can use based on the Query Profile are:

Add a LIMIT to the ORDER BY If possible: This option will improve performance by reducing the amount of data that needs to be sorted and returned by the query. The ORDER BY clause requires sorting all rows in the input before returning them, which can be expensive and time-consuming. By adding a LIMIT clause, the query can return only a subset of rows that satisfy the order criteria, which can reduce sorting time and network transfer time.

Create indexes to ensure sorted access to data: This option will improve performance by reducing the amount of data that needs to be scanned and filtered by the query. The query contains several predicates on different columns, such as o_orderdate, o_orderpriority, l_shipmode, etc. By creating indexes on these columns, the query can leverage sorted access to data and prune unnecessary micro-partitions or rows that do not match the predicates. This can reduce IO time and processing time.

The other options are not optimal because:

Use a multi-cluster virtual warehouse with the scaling policy set to standard: This option will not improve performance, as the query is already using a multi-cluster virtual warehouse with the scaling policy set to standard. The Query Profile shows that the query is using a 2XL warehouse with 4 clusters and a standard scaling policy, which means that the warehouse can automatically scale up or down based on the load. Changing the warehouse size or the number of clusters will not affect the performance of this query, as it is already using the optimal resources.

Increase the max cluster count: This option will not improve performance, as the query is not limited by the max cluster count. The max cluster count is a parameter that specifies the maximum number of clusters that a multi-cluster virtual warehouse can scale up to. The Query Profile shows that the query is using a 2XL warehouse with 4 clusters and a standard scaling policy, which means that the warehouse can automatically scale up or down based on the load. The default max cluster count for a 2XL warehouse is 10, which means that the warehouse can scale up to 10 clusters if needed. However, the query does not need more than 4 clusters, as it is not CPU-bound or memory-bound. Increasing the max cluster count will not affect the performance of this query, as it will not use more clusters than necessary.


Options Selected by Other Users:
Snowflake DEA-C01