When maintaining reports and dashboards, why is it essential to build automated and repeatable tasks?

• A.Automated tasks increase dashboard management complexity.
• B.Repeatable tasks hinder data updates in dashboards.
• C.They ensure inconsistency in reports and dashboards.
• D.Automated tasks reduce manual efforts, ensuring consistency.

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You are analyzing website traffic data in Snowflake to identify potential bot activity. You have a table 'WEB EVENTS' with columns 'event_timestamp' (TIMESTAMP NTZ), 'user_id' (VARCHAR), and 'ip_address' (VARCHAR). Which combination of SQL techniques and Snowflake features would be MOST effective in detecting and flagging suspicious bot-like behavior, considering high query performance and scalability?

• A.Use a UDF (User-Defined Function) written in Python to perform complex behavioral analysis on user event sequences, checking for patterns like rapid page transitions or form submissions within unrealistic timeframes. Apply this UDF to the 'WEB EVENTS' table.
• B.Calculate event frequency per user and IP address using window functions (e.g., 'COUNT() OVER (PARTITION BY user_id, ip_address ORDER BY Then, identify users/lPs with abnormally high event rates within short time intervals using appropriate threshold criteria.
• C.Join the table with a publicly available list of known bot IP addresses. Flag any events originating from those IP addresses as potential bot activity. Supplement this with simple frequency counts of events per user.
• D.Create a scheduled task that periodically runs a query to analyze the ratio of human-generated events to server-generated events. If the ratio drops below a certain threshold, flag the time period as suspicious.
• E.Implement a stored procedure that iterates through each unique IP address in the table, calculating the average time between events for each 12 Flag IP addresses where the average time between events is significantly below a pre-defined threshold.

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Consider a Snowflake table 'LOG ENTRIES' with a VARIANT column 'LOG DATA' containing log messages with potentially varying structures. Some logs contain error details under the key 'error', while others do not. If 'error' exists, it contains a nested object with 'code' and 'message'. You want to extract the error 'message' when it exists, otherwise return 'No Error'. Which query accomplishes this with optimal performance?

• A.
• B.
• C.
• D.
• E.

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Why are Stored Procedures valuable in data analysis using SQL?

• A.They are exclusively used for one-time data operations.
• B.They restrict the execution of repetitive tasks, limiting efficiency.
• C.Stored Procedures enable custom and repeated data operations, enhancing efficiency.
• D.Stored Procedures solely facilitate data visualization.

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You are tasked with optimizing a dashboard displaying sales performance across different regions. The dashboard queries a large table called 'SALES DATA, which is partitioned by 'SALE DATE. The dashboard loads very slowly. The data analyst team notices that queries for the dashboard often filter on a specific region and a date range. Which of the following steps can you take to improve the dashboard's performance? (Select TWO)

• A.Create a materialized view that pre-aggregates the data by region and date. The materialized view should be incrementally updated.
• B.Create a table clone of 'SALES_DATX and point the dashboard to the clone instead.
• C.Create a search optimization policy on the 'SALES DATA' table for the 'REGION' column.
• D.Recluster the SALES DATA' table on 'REGION' and 'SALE DATE.
• E.Increase the size of the warehouse used to query the 'SALES DATA' table.

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