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FreePdfDump Snowflake DAA-C01 Dumps PDF Format

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The SnowPro Advanced: Data Analyst Certification Exam (DAA-C01) study material of FreePdfDump is available in three different and easy-to-access formats. The first one is printable and portable SnowPro Advanced: Data Analyst Certification Exam (DAA-C01) PDF format. With the PDF version, you can access the collection of actual SnowPro Advanced: Data Analyst Certification Exam (DAA-C01) questions with your smart devices like smartphones, tablets, and laptops.

Snowflake SnowPro Advanced: Data Analyst Certification Exam Sample Questions (Q66-Q71):

NEW QUESTION # 66
When performing a diagnostic analysis, what action aids in identifying demographics and relationships? (Select all that apply)

A. Focusing solely on isolated data points
B. Ignoring data relationships for focused analysis
C. Collecting related data
D. Analyzing statistical trends

Answer: C,D

Explanation:
Analyzing statistical trends and collecting related data are crucial in identifying demographics and relationships in diagnostic analysis.

NEW QUESTION # 67
You are working with a table named 'PRODUCT DESCRIPTIONS that contains product descriptions in a 'description' (VARCHAR) column. You need to implement a solution to identify potentially sensitive information within these descriptions, specifically looking for mentions of credit card numbers or social security numbers (SSNs). You want to flag any description that contains either of these patterns. Which of the following Snowflake SQL snippets, leveraging scalar string functions and regular expressions, provides the most efficient and accurate way to achieve this? (Assume that valid credit card numbers are 16 digits and valid SSNs are in the format 'XXX-XX-XXXX'). Select all correct options.

A. Option D
B. Option B
C. Option E
D. Option C
E. Option A

Answer: D,E

Explanation:
Options A and C are both correct. Option A uses 'REGEXP_LIKE with two separate regular expressions to search for a 16-digit number (credit card) and a 'XXX-XX-XXXX' pattern (SSN). Option C uses a single 'REGEXP LIKE' function with an alternation to combine both patterns into one regular expression , which is generally more efficient. Option B relies on 'CONTAINS' which performs a simple substring search, not regular expression matching; this will not accurately identify the patterns. Option D uses 'STARTS WITH' which will only identify descriptions that begin with the specified keywords, missing most cases. Option E uses 'LIKE operator for the mentioned words in the sentence that can be 'Credit Card' or 'Social Security Number', but this isn't a search for Credit card numbers or SSNs.

NEW QUESTION # 68
A data analyst is tasked with creating a view in Snowflake that aggregates sales data by region. The underlying sales table is updated frequently. The analyst wants to optimize query performance and minimize the impact of these updates. Which of the following approaches would be the MOST suitable for creating the view?

A. Create a materialized view using CREATE MATERIALIZED VIEW statement.
B. Create a temporary table, populate it with the aggregated data, and query from the temporary table.
C. Create a recursive view to handle potential hierarchical region data.
D. Create a standard view using CREATE VIEW statement.
E. Create a secure view using CREATE SECURE VIEW statement.

Answer: A

Explanation:
A materialized view (Option B) is the most suitable because it pre-computes and stores the aggregated data. This improves query performance, especially for frequently accessed aggregated data. Since it's automatically refreshed when the underlying sales table is updated, it minimizes the impact of updates on query performance. Standard views are computed on the fly, negating performance benefits. Temporary tables require manual updates. Secure views focus on data security, not performance. Recursive views are for hierarchical data, not aggregation.

NEW QUESTION # 69
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?

A. Use 'QUALIFY Clause with 'CORR function to determine the coefficient values, and then apply statistical significance tests manually by calculating p-values.
B. Use a combination of 'WHERE clause to filter out rows where either 'ITEM COUNT or 'ORDER VALUE is NULL, and then apply the 'CORR function to the filtered data.
C. Use the 'CORR function directly on the 'ITEM_COUNT and 'ORDER_VALUE columns. No special handling is needed for NULL values as 'CORR automatically ignores them.
D. First, replace NULL values in both 'ITEM COUNT and 'ORDER _ VALUE with 0 using 'COALESCE, then apply the 'CORR function.
E. Use 'AVG' and 'STDDEV_POP functions to calculate the mean and standard deviation for both and Then, manually compute the correlation coefficient using these statistics.

Answer: B

Explanation:
The 'CORR function in Snowflake can calculate the Pearson correlation coefficient. However, NULL values can affect the result. Option E correctly handles this by explicitly filtering out rows containing NULL values in either column using a 'WHERE' clause, ensuring that the 'CORR function is applied only to complete pairs of data. Replacing NULL with zero can skew the distribution. Manual computation using AVG and STDDEV POP are more error prone and time taking.

NEW QUESTION # 70
How do secure views enhance data analysis practices?

A. Secure views prevent the creation of materialized views.
B. Secure views provide enhanced data security while enabling selective data access.
C. They improve query performance but don't impact data security.
D. Secure views limit access to data, hindering analysis.

Answer: B

Explanation:
Secure views offer enhanced data security by allowing selective data access, benefiting analysis while maintaining security.

NEW QUESTION # 71
......

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