Q22. A data analyst is tasked with monitoring the performance of several Snowpipe data ingestion processes. They need to set up alerts based on the number of files failing to load within a specific timeframe. Which combination of Snowflake features and logging/monitoring practices would be MOST effective in achieving this?

Q23. What types of Snowflake functions are available for data analysis and manipulation? (Select all that apply)

Q24. Given the following data:

This SELECT statement is executed:

What will be the result?

Q25. A Data Analyst has been analyzing customer data in several worksheets. Each worksheet contains a complex query that provides clean and prepared data for visualizations. The Analyst has also created a Customer Overview dashboard in Snowsight. How should the Analyst add the worksheets in the Customer Analysis database to the dashboard, using the LEAST amount of operational overhead?

Q26. You are using Snowpipe to continuously load data from an external stage (AWS S3) into a Snowflake table named ‘RAW DATA. You notice that the pipe is frequently encountering errors due to invalid data formats in the incoming files. You need to implement a robust error handling mechanism that captures the problematic records for further analysis without halting the pipe’s operation. Which of the following approaches is the MOST effective and Snowflake-recommended method to achieve this?

Q27. A Data Analyst has been asked to predict sales revenue through the end of the year. Which function will provide this information?

Q28. Consider a scenario where you are building a dashboard to monitor the performance of a marketing campaign. The data includes daily ad spend, website conversions, and cost per acquisition (CPA). The stakeholders need to quickly assess whether the campaign is meeting its target CPA. What visualization type would be MOST appropriate to display the current CPA compared to the target CPA, providing a clear and concise view of performance?

Q29. 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?

Q30. You have a table named USER ACTIVITY containing user interaction data’. The ‘TIMESTAMP NTT column stores timestamps without time zone information, while the ‘USER ID column stores IDs as VARCHAR. You need to identify users who have been active between a specific UTC time range, converting the ‘TIMESTAMP NTT column to UTC. Furthermore, you want to categorize users based on the number of activities recorded. Which of the following SQL queries best achieves this, efficiently utilizing Snowflake’s casting and data transformation capabilities?

Q31. You are tasked with loading multiple CSV files from an external stage into a Snowflake table. The files have the following naming convention: HHMlSS.csv’ (e.g., ‘data_20240101 120000.csv’). You need to load all the files that were created on or after ‘2024-01-01’ into the ‘target_table’. Which of the following approaches can be used to load those data?

Q32. You are designing a data ingestion pipeline to collect clickstream data from a high-traffic e-commerce website. You anticipate a daily data volume that fluctuates significantly, ranging from 5 TB to 20 TB. To optimize Snowflake costs and ensure efficient data loading, which combination of Snowflake features and ingestion methods would be MOST effective for identifying the accurate data volume before the data is fully loaded into a production table?

Q33. You are a data analyst at a retail company. You need to calculate the total sales for each product category, but only for categories where the average unit price is above $50 and the number of sales transactions exceeds 1000. Which Snowflake SQL query would efficiently achieve this?

Q34. You are analyzing customer order data in Snowflake and need to determine if there is a statistically significant correlation between the number of items in an order (‘ITEM COUNT) and the total order value CORDER VALUE’). You have a table named ‘ORDERS’ with columns ‘ORDER ID’, ‘ITEM COUNT’, and ‘ORDER VALUE’. Which of the following Snowflake functions or methods, used in combination, would be the MOST appropriate and statistically sound for calculating the correlation coefficient between these two variables, taking into account the need to handle potential NULL values appropriately?

Q35. A retail company uses Snowflake to store sales data’. They have a dashboard showing daily sales trends, powered by a materialized view The sales data is updated every hour. The dashboard team reports that the dashboard sometimes shows stale data’. They want to ensure the dashboard always reflects the latest sales figures without significantly impacting warehouse costs. Which of the following strategies is MOST effective?

Q36. How do secure views contribute to data analysis practices in terms of access control and data security?

Q37. You are analyzing sales data from different regions stored in a Snowflake table named ‘sales_data’. The table includes columns: ‘transaction_id’ (VARCHAR), ‘region’ (VARCHAR), ‘sale_date’ (DATE), and ‘sale_amount’ (NUMBER). You discover the following data quality issues: The ‘region’ column contains inconsistent entries such as ‘North’, ‘north’, ‘NOrth ‘, and ‘ South’. The ‘sale_amount’ column has some values that are stored as strings (e.g., ‘100.50’) instead of numbers, causing errors in aggregation. There are duplicate records identified by the same ‘transaction id’. Which set of SQL statements, executed in the given order, provides the MOST effective and efficient way to address these data quality issues in Snowflake?

Q38. A scorecard tile on a Snowsight dashboard shows a comparison between the industry average employee age (which is 34) and a company’s average employee age (which is 38). The scorecard tile looks like this:
Comparison with industry average

How should this tile be interpreted?

Q39. A telecommunications company wants to segment its customers based on their usage patterns for targeted marketing campaigns. You have access to a table named ‘CUSTOMER USAGE with the following columns: ‘CUSTOMER ONT), ‘DATA USAGE GB’ (FLOAT), ‘VOICE CALL MINUTES (INT), and (INT). Which of the following Snowflake features or techniques would be MOST appropriate for performing customer segmentation and determining distinct customer clusters?

Q40. You are building a Data Vault model in Snowflake. You have identified a Hub for Customers, a Link table relating Customers to Addresses, and several Satellite tables storing descriptive attributes of both Customers and Addresses. A new business requirement emerges: you need to efficiently query the model to find all Customers who have lived at the same Address as another Customer at any point in time. Which of the following approaches is MOST efficient and scalable for implementing this query in Snowflake, without significantly impacting the Data Vault’s core principles?

Q41. How do Stored Procedures contribute to the efficiency of data analysis using SQL?

Q42. Which actions are pertinent in identifying demographics and relationships during diagnostic analysis? (Select all that apply)