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Snowflake SnowPro Advanced: Data Analyst Certification Exam Sample Questions (Q164-Q169):

NEW QUESTION # 164
When planning for data volume collection, what is an important consideration to ensure scalability and performance?

A. The expected growth rate of data
B. The physical location of data
C. The types of data visualization tools used
D. The data processing capabilities

Answer: A

NEW QUESTION # 165
A large retail company is migrating its transaction data to Snowflake and wants to build a consumption layer for BI reporting. They have historical data with frequent updates and require both point-in-time analysis and trend analysis. Which modeling technique(s) would be MOST suitable for this scenario, considering performance, storage efficiency, and the need for both historical tracking and current state views?

A. A wide, denormalized table created using CREATE TABLE AS SELECT (CTAS) statement, refreshed nightly.
B. Data Vault modeling, with point-in-time tables built on top of the Data Vault for Bl reporting.
C. Snowflake Schema with Slowly Changing Dimension Type 2 (SCD2) for relevant dimensions.
D. Star Schema with Slowly Changing Dimension Type 1 (SCDI) for all dimensions.
E. Star Schema with Slowly Changing Dimension Type 0 (SCDO) for critical dimensions.

Answer: B,C

Explanation:
Data Vault provides the historical tracking and auditability needed, while point-in-time tables on top optimize for BI queries. Snowflake schema with SCD2 also allows historical tracking within a dimensional model. SCDI alone will not preserve history, and SCDO locks in attributes indefinitely. A wide denormalized table is not suitable for historical analysis or frequent updates and can lead to redundancy. Therefore options B and C are suitable for BI reporting.

NEW QUESTION # 166
You are performing an UPDATE operation on a large table 'CUSTOMER ORDERS with millions of rows. The update logic involves complex calculations based on data from another table 'PRODUCT PRICES. To minimize the impact on concurrent queries and ensure data consistency, which of the following strategies should you implement?

A. Create a new version of table with updated data and switch to new version.
B. Break the UPDATE operation into smaller batches using a WHERE clause with a limiting condition based on a primary key or date range and commit changes after each batch.
C. Use a MERGE statement to update the 'CUSTOMER ORDERS' table based on the data from the 'PRODUCT PRICES' table.
D. Create a temporary table with the updated values, drop the original table, and rename the temporary table to the original table name.
E. Execute the UPDATE statement directly without any special considerations, relying on Snowflake's default concurrency control.

Answer: B,C

Explanation:
Breaking the UPDATE into smaller batches minimizes lock contention and reduces the duration of the update transaction, thereby reducing the impact on concurrent queries. A MERGE statement is an efficient way to perform updates based on data from another table, optimizing the process compared to a simple UPDATE statement. Option A is not recommended for large tables due to potential lock contention. Option C is disruptive and might cause issues if concurrent queries are running against the table. Option E is not a standard approach.

NEW QUESTION # 167
How do logging and monitoring solutions contribute to data processing solutions? (Select all that apply)

A. Automate data processing effectively
B. Respond to processing failures promptly
C. Ensure real-time data processing
D. Provide insights into processing status

Answer: B,D

Explanation:
Logging and monitoring solutions help respond to processing failures promptly and provide insights into processing status.

NEW QUESTION # 168
How do diverse chart types (e.g., bar charts, scatter plots, heat grids) contribute to effective data presentation and visualization in reports and dashboards?

A. Diverse chart types restrict data exploration in reports and dashboards.
B. Charts don't impact data visualization in reports or dashboards.
C. Different chart types offer varied data representation for better analysis.
D. They limit data representation options for simplicity.

Answer: C

Explanation:
Different chart types offer varied data representation, aiding better analysis in reports and dashboards.

NEW QUESTION # 169
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