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NEW QUESTION # 87
When optimizing query performance in Snowflake, what benefits does result caching provide?
Answer: B
Explanation:
Result caching accelerates query execution by storing intermediate results, reducing processing time for repetitive or commonly accessed queries.
NEW QUESTION # 88
You have a table 'PRODUCTS' with a 'PRICE' column stored as VARCHAR. Some values in this column are valid numerical strings (e.g., '12.99'), while others contain invalid characters (e.g., '12.99USD', 'N/A'). You need to calculate the average price of all valid products. Which of the following approaches ensures that you only consider valid numeric values and handles potential errors effectively? Select all that apply.
Answer: A,D
Explanation:
Option B is correct because it uses a regular expression to explicitly check if the PRICE column contains only valid numeric characters (digits and an optional decimal point) before attempting to cast it to a DECIMAL. 'REGEXP LIKE' ensures that non-numeric values are filtered out, preventing errors during casting, and then 'CAST is used since it is validated by the regular expression check. Option D is also correct because it uses 'CASE statement with 'IS DECIMAL' function that is a user defined function (UDF) for checking if a string can be converted to decimal, and if True, it casts the PRICE to DECIMAL; otherwise, it assigns NULL. The AVG function automatically ignores NULL values, ensuring that only valid numeric values are considered. Option A won't work as DECIMAL' function is not standard, so you will need to create user defined function. 'TO_NUMBER and 'TO_DECIMAL' throws error if it cannot parse which is not ideal. Option E, throws error if column PRICE cannot be converted, where as 'TRY TO DECIMAL' will not throw the error and return NULL.
NEW QUESTION # 89
What critical role do user-defined functions (UDFs) play in data analysis using SQL?
Answer: C
Explanation:
UDFs allow customization and extension of SQL functionalities beyond standard operations.
NEW QUESTION # 90
You have developed a Snowsight dashboard for your marketing team that contains sensitive customer data'. You need to share this dashboard with a specific group of users, but ensure that they can only view the data and cannot modify the dashboard itself or the underlying queries. Which of the following steps should you take to securely share the dashboard?
Answer: D
Explanation:
Sharing with 'Can view' (B) ensures the users cannot modify the dashboard itself. Granting 'SELECT on the underlying tables/views and USAGE' on the database/schema allows them to see the data when the dashboard executes queries on their behalf. 'Can edit' (A) would allow them to modify the dashboard, which is not desired. 'MONITOR (C) is for monitoring warehouse usage, not data access. Exporting as PDF (D) is a workaround, but it loses interactivity and isn't a direct sharing method. E isn't correct because permissions on the data sources must be granted separately.
NEW QUESTION # 91
You have a table 'CUSTOMER DATA with sensitive information like 'SSN' and 'CREDIT CARD NUMBER. You need to provide access to analysts for reporting purposes but must mask the sensitive columns. You decide to use a combination of Secure Views and data masking policies. Consider the following code snippets:
An analyst with the 'ANALYST ROLE executes the following query: SELECT FROM ANALYST CUSTOMER VIEW LIMIT 10; What will be the value of the 'SSN' column in the result set for the analyst?
Answer: B
Explanation:
The masking policy 'mask_ssn' is applied to the 'SSN' column in the 'CUSTOMER DATA' table. Because the analyst executing the query has the 'ANALYST_ROLE, the masking policy will transform the 'SSN' value to - before the result set is returned. Secure Views can access masked columns and display them according to the policy definition. The secure view ensures that the analyst can only access the data through the view, further enhancing security.
NEW QUESTION # 92
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