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Snowflake SnowPro Advanced: Data Analyst Certification Exam Sample Questions (Q103-Q108):

NEW QUESTION # 103
You are examining sales data for an e-commerce company in Snowflake. You notice a recurring dip in sales every Wednesday. The 'SALES' table contains columns: 'order_id', 'order date' , 'product_id', 'quantity', 'price'. Which of the following SQL queries and analytical techniques would be the MOST effective for diagnosing the reasons behind this weekly sales dip, assuming no external promotional activity always happens on Wednesdays?

A. Review recent code deployments related to the e-commerce platform and identify if any changes were implemented on Tuesdays or Wednesdays that could be impacting sales.
B. Run a query to calculate the average daily sales for each day of the week and visualize the results to confirm the dip on Wednesdays. Use "DAYOFWEEK' function for this.
C. Investigate shipping times by day of the week to determine if longer shipping times on orders placed earlier in the week are affecting Wednesday sales. Join ' SALES table with 'SHIPPING' table and calculate difference between 'order_date' and 'ship_date' .
D. Check if there are any scheduled maintenance windows or system outages occurring on Wednesdays that might be affecting order processing. Use 'INFORMATION SCHEMA.LOAD HISTORY' to look for any loads failing on wednesdays
E. Analyze sales patterns by 'product_id' and day of the week to see if specific product categories are driving the overall dip on Wednesdays. Use 'PIVOT' operator for cross-tabulation.

Answer: A,B,C,E

Explanation:
Options A, B, C, and E are the most relevant. Option A helps confirm the dip. Option B identifies product-specific patterns. Option C investigates a potential shipping-related cause. Option E explores potential software changes, while Option D focuses on a possible but less relevant cause of system maintenance.

NEW QUESTION # 104
What is the primary benefit of connecting BI tools to Snowflake for dashboard creation?

A. BI tools restrict dashboard customization
B. Improved data security in dashboards
C. Simplified data access for all users
D. Seamless integration and data visualization

Answer: D

Explanation:
Connecting BI tools to Snowflake enables seamless integration and data visualization in dashboard creation.

NEW QUESTION # 105
You are performing an UPDATE operation on a large table 'CUSTOMER ORDERS with millions of rows. The update logic involves complex calculations based on data from another table 'PRODUCT PRICES. To minimize the impact on concurrent queries and ensure data consistency, which of the following strategies should you implement?

A. Create a new version of table with updated data and switch to new version.
B. Use a MERGE statement to update the 'CUSTOMER ORDERS' table based on the data from the 'PRODUCT PRICES' table.
C. Execute the UPDATE statement directly without any special considerations, relying on Snowflake's default concurrency control.
D. Create a temporary table with the updated values, drop the original table, and rename the temporary table to the original table name.
E. Break the UPDATE operation into smaller batches using a WHERE clause with a limiting condition based on a primary key or date range and commit changes after each batch.

Answer: B,E

Explanation:
Breaking the UPDATE into smaller batches minimizes lock contention and reduces the duration of the update transaction, thereby reducing the impact on concurrent queries. A MERGE statement is an efficient way to perform updates based on data from another table, optimizing the process compared to a simple UPDATE statement. Option A is not recommended for large tables due to potential lock contention. Option C is disruptive and might cause issues if concurrent queries are running against the table. Option E is not a standard approach.

NEW QUESTION # 106
How do table functions differ from other Snowflake functions?

A. Table functions return tables as results.
B. Table functions modify existing table structures.
C. They only operate on entire tables.
D. They perform mathematical computations exclusively.

Answer: A

Explanation:
Table functions return tables as results, distinguishing them from other Snowflake functions.

NEW QUESTION # 107
In what way can regular views be advantageous in data analysis?

A. They restrict data access, improving security but hindering analysis.
B. Regular views can only be utilized in combination with UDFs.
C. Regular views simplify complex data structures for ease of analysis.
D. Regular views don't impact query performance significantly.

Answer: C

Explanation:
Regular views simplify complex data structures, aiding ease of analysis by providing a streamlined representation of data.

NEW QUESTION # 108
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