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Snowflake SnowPro Advanced: Data Analyst Certification Exam Sample Questions (Q12-Q17):

NEW QUESTION # 12
Data clustering is an example of which type of data analysis technique?

A. Exploratory analysis
B. Predictive analysis
C. Prescriptive analysis
D. Descriptive analysis

Answer: B

NEW QUESTION # 13
A marketing team wants to understand the impact of their campaigns on website traffic and conversions. You have the following tables in Snowflake: sCAMPAlGN PERFORMANCE: 'CAMPAIGN ONT), (DATE), 'CLICKS' (INT), 'IMPRESSIONS' (INT), 'COST (NUMBER) 'DATE' (DATE), 'PAGE_VIEWS' ONT), (INT) 'CONVERSIONS' 'DATE (DATE), ONT), (NUMBER) Which SQL query and visualization technique would be most suitable for identifying the correlation between campaign spend and website conversions over time, allowing the team to quickly identify campaigns with a high return on investment (ROI)?

A. An excel Pivot table from exported data from all these tables which uses the data points required.
B. A scatter plot visualizing the relationship between 'COST' from 'CAMPAIGN PERFORMANCE and 'CONVERSION COUNT from 'CONVERSIONS', aggregated by 'DATE and calculated ROI, generated from a query using window functions to compute cumulative sums and moving averages.
C. Aline chart displaying 'COST from 'CAMPAIGN PERFORMANCE, from 'WEBSITE TRAFFIC, and 'CONVERSION COUNT from 'CONVERSIONS' over time ( ' DATE), joined on the 'DATE column, with a calculated ROI metric displayed as a separate line on the same chart. The query uses a common table expression (CTE) to first calculate daily ROI.
D. A simple bar chart showing total clicks per campaign ID, generated from a query that joins 'CAMPAIGN PERFORMANCE with 'WEBSITE _ TRAFFIC' on the DATE column.
E. Three separate pie charts, one showing the percentage of clicks per campaign, one showing the percentage of impressions per campaign, and one showing the percentage of conversions per campaign.

Answer: C

Explanation:
Option D is the most effective. A line chart plotting cost, unique visitors, and conversion count over time allows for visual identification of trends and correlations. Displaying ROI on the same chart provides a direct measure of campaign effectiveness. The CTE helps organize the ROI calculation. Option B, while useful, doesn't explicitly show the temporal relationship. Options A and C offer limited insights into ROI. Exporting and using Excel (E) is not scalable or efficient for dynamic analysis.

NEW QUESTION # 14
When performing forecasting, which statistical method is commonly used based on historical data?

A. Data normalization
B. Inferential statistics
C. Regression analysis
D. Simple data aggregation

Answer: C

Explanation:
Regression analysis is frequently used for forecasting based on historical data, predicting future trends.

NEW QUESTION # 15
You are troubleshooting a slow-running query that performs a complex transformation on a large dataset using a series of CTEs. You've identified one particular CTE, , as contributing significantly to the overall execution time. Examination of the query profile reveals high spillover to local storage during the execution of this CTE. Which of the following actions could potentially reduce spillover and improve the performance of the CTE? Select all that apply.

A. Rewrite the CTE to use smaller intermediate tables.
B. Reduce the 'MAX MEMORY USAGE IN parameter at the session level.
C. Partition the underlying tables used in the CTE.
D. Increase the warehouse size.
E. Create a materialized view from the 'calculate metrics CTE.

Answer: A,D

Explanation:
Increasing the warehouse size (A) provides more memory, which directly reduces spillover. Rewriting the CTE to use smaller intermediate tables (C) reduces the memory footprint of the operation. Partitioning the tables (B) is not directly supported in Snowflake. Creating a materialized view from the CTE (D) can improve performance if the CTE's results are frequently reused, but it does not necessarily address the spillover issue directly. Reducing the 'MAX (E) would worsen spillover. Using temporary tables (E) will not necessarily impact spilling if the memory limits are still exceeded within the query runtime.

NEW QUESTION # 16
When performing forecasting, which factors are essential for accurate predictions? (Select all that apply)

A. Incorporating statistical methods for prediction accuracy
B. Relying solely on historical data without considering external influences
C. Using basic arithmetic functions exclusively for forecasting
D. Examining trends and anomalies in historical data

Answer: A,D

Explanation:
Incorporating statistical methods and considering trends/anomalies are crucial for accurate predictions in forecasting.

NEW QUESTION # 17
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