SnowPro Advanced Real Exam Questions and Answers FREE DAA-C01 Updated on Apr 11, 2026 [Q28-Q42]

QUESTION 28
You are tasked with identifying potential data sources for a new marketing analytics dashboard. The dashboard needs to provide insights into customer behavior across various touchpoints. Which of the following would be the MOST appropriate data sources to consider?

QUESTION 29
You’re working with a large dataset containing website user activity, including ‘session_id’, ‘user_id’, ‘timestamp’, and ‘page_view’. You suspect bot activity is skewing your engagement metrics. Bots tend to have very short session durations and high page view counts within those sessions. Which of the following Snowflake SQL queries, used in combination, would be MOST effective in identifying and flagging potential bot sessions, considering performance on a large dataset? Assume you have access to Snowflake’s statistical functions.

QUESTION 30
You have a table ‘CUSTOMER DATA’ with a column ‘phone_number” (VARCHAR) that contains phone numbers in various formats (e.g., ‘123-456-7890’, ‘1234567890’, ‘+11234567890’). You need to standardize the phone numbers to a format of ‘1234567890’ (no hyphens or country code). Which Snowflake SQL statement, using scalar string functions, will achieve this standardization while gracefully handling potentially invalid phone numbers (e.g., too short or containing letters) by returning NULL for invalid entries?

QUESTION 31
A marketing company is analyzing customer purchase data stored in Snowflake to understand which customer demographics are most likely to purchase a newly launched product. The ‘CUSTOMERS table has columns: ‘customer_id’, ‘age’ , ‘gender’ , ‘location’ , and ‘household income’. The ‘PURCHASES’ table has columns: ‘customer_id’, ‘purchase_date’, and ‘product id’. Which SQL query would most effectively identify the top three age groups with the highest purchase rate for the new product (product_id = ‘NEW PRODUCT’)?

QUESTION 32
A table named ‘website_visits’ tracks user activity with columns ‘user_id’, ‘visit_timestamp’ , and ‘page_view’. You need to determine the time difference (in minutes) between each user’s consecutive page views. Assuming ‘visit_timestamp’ is of data type TIMESTAMP NTZ, which Snowflake SQL query will accurately calculate this?

QUESTION 33
You need to create a dashboard for a logistics company to track delivery performance. The dashboard should display the following information: (1) Total number of deliveries per day, (2) Percentage of deliveries completed on time, (3) Average delivery time per city, (4) Number of deliveries exceeding the SLA (Service Level Agreement) by more than 1 hour. Which of the following chart combinations would be MOST effective to display this information in a clear and concise manner?

QUESTION 34
What is the primary benefit of connecting BI tools to Snowflake for dashboard creation?

QUESTION 35
You are analyzing customer churn for a subscription-based service. You have a table ‘SUBSCRIPTIONS’ with columns: ‘CUSTOMER_ID, ‘START_DATE’, ‘END_DATE’, ‘SUBSCRIPTION TYPE, and ‘REVENUE’. You want to classify customers who are likely to churn based on their past subscription behavior. Which Snowflake SQL code snippet is MOST efficient for calculating the number of months each customer was subscribed and identifying those who subscribed for less than 3 months as potential churn candidates?

QUESTION 36
You have a Snowflake table ‘order details’ with columns ‘order id’, ‘customer id’, ‘order date’, and ‘order amount’. You need to calculate the 3-month moving average of ‘order_amount’ for each customer, but only for those customers who have placed at least 5 orders. Which of the following SQL statements will correctly achieve this? (Assume the current date is ‘2024-01-01 ‘)

QUESTION 37
What steps are typically involved in troubleshooting query performance issues in Snowflake?
(Select all that apply)

QUESTION 38
You are tasked with migrating data from an existing relational database to Snowflake. The database contains a ‘Customers’ table (CustomerlD, Name, City, State) and an ‘OrderS table (OrderlD, CustomerlD, OrderDate, TotalAmount). A critical requirement is to maintain data integrity and quickly identify any orphaned records after the initial load. Which approach provides the MOST efficient and robust method to identify orphaned ‘Orders’ (orders where the CustomerlD does not exist in the ‘Customers’ table) in Snowflake, considering large data volumes and performance?

QUESTION 39
Your organization stores clickstream data in Parquet files in an external stage ‘s3://your-bucket/clickstreamP. The data includes nested JSON structures representing user activity. You need to create a Snowflake table to query this data efficiently, extracting specific fields from the nested JSON. The challenge is to optimize query performance by leveraging Parquet’s columnar storage and schema evolution capabilities. Which of the following approaches offers the BEST combination of performance and flexibility for querying the data in Snowflake, considering potential schema changes in the Parquet files over time?

QUESTION 40
What role does leveraging native data types play in Snowflake while working with different datasets?

QUESTION 41
A data analyst is tasked with optimizing a query that aggregates data from a table ‘ORDERS’ containing order details, including columns like ‘ORDER ID’, ‘CUSTOMER ID, ‘ORDER DATE, ‘PRODUCT ID’, and ‘QUANTITY. The query calculates the total quantity of products ordered per customer and month. The current query is as follows: SELECT CUSTOMER ID, DATE TRUNC(‘MONTH’, ORDER DATE) AS ORDER MONTH, SUM(QUANTITY) AS TOTAL QUANTITY FROM ORDERS GROUP BY CUSTOMER_ID, ORDER_MONTH ORDER BY CljSTOMER_lD, ORDER_MONTH; Deopite the ‘ORDERS’ table being relatively small (10 million rows), the query performance is slow. The analyst suspects a poorly chosen warehouse size. Which of the following actions, combined with monitoring query execution, would be MOST beneficial to determine the optimal warehouse size and improve query performance?

QUESTION 42
How do table functions differ from other Snowflake functions?