Practice Free DAA-C01 Exam Online Questions
When customizing data presentations in dashboards using filtering and editing techniques, what advantages do these methods offer? (Select all that apply)
- A . Simplified data representation
- B . Enhanced data accuracy
- C . Improved data relevancy
- D . Limited data exploration
B,C
Explanation:
Customizing through filtering and editing enhances data accuracy and relevancy in dashboards.
In what way can regular views be advantageous in data analysis?
- A . Regular views simplify complex data structures for ease of analysis.
- B . Regular views can only be utilized in combination with UDFs.
- C . Regular views don’t impact query performance significantly.
- D . They restrict data access, improving security but hindering analysis.
A
Explanation:
Regular views simplify complex data structures, aiding ease of analysis by providing a streamlined representation of data.
What is the primary benefit of connecting BI tools to Snowflake for dashboard creation?
- A . Simplified data access for all users
- B . Improved data security in dashboards
- C . BI tools restrict dashboard customization
- D . Seamless integration and data visualization
D
Explanation:
Connecting BI tools to Snowflake enables seamless integration and data visualization in dashboard creation.
When enriching data with Snowflake Marketplace, what role do data shares play in joining external data with existing datasets?
- A . Data shares only work with Snowflake-provided datasets.
- B . Data shares facilitate secure data exchange between parties.
- C . They restrict access to external data.
- D . They limit the types of data that can be joined.
B
Explanation:
Data shares enable secure data exchange, allowing joining external data with existing datasets.
When utilizing materialized views, what benefit do they offer in terms of query performance and data retrieval?
- A . Materialized views restrict data retrieval for improved security.
- B . Regular views simplify complex data structures for better query performance.
- C . They offer real-time updates reflecting instantaneous database changes.
- D . Materialized views provide precomputed snapshots, improving query performance.
D
Explanation:
Materialized views provide precomputed snapshots, enhancing query performance.
When customizing data presentations in dashboards using filtering and editing techniques, what advantages do these methods offer? (Select all that apply)
- A . Enhanced data accuracy
- B . Limited data exploration
- C . Improved data relevancy
- D . Simplified data representation
A,C
Explanation:
Customizing through filtering and editing enhances data accuracy and relevancy in dashboards.
Which statistical method is commonly used in forecasting based on historical data?
- A . Regression analysis
- B . Simple data aggregation
- C . Data normalization
- D . Inferential statistics
A
Explanation:
Regression analysis is frequently employed for forecasting based on historical data, predicting future trends based on past patterns.
How do materialized views differ from regular views in the context of data analysis?
- A . Regular views provide a persisted snapshot of data, unlike materialized views.
- B . Materialized views restrict data accessibility compared to regular views.
- C . Regular views offer precomputed snapshots, differentiating them from materialized views.
- D . Materialized views simplify complex data structures for ease of analysis, unlike regular views.
C
Explanation:
Materialized views offer precomputed snapshots, differentiating them from regular views.
When creating reports and dashboards, how does evaluating data based on business requirements impact the visualization process?
- A . It limits data selection, affecting overall dashboard quality.
- B . Business requirements have no impact on data selection for visualization.
- C . Evaluating data ensures relevant and useful dashboard content.
- D . Evaluating data complicates dashboard creation.
C
Explanation:
Evaluating data based on business requirements ensures the dashboard contains relevant and useful content, improving its quality.
In Snowflake, how does partition pruning contribute to optimizing query performance?
- A . Impacts query planning but not execution
- B . Limits data accessibility across warehouses
- C . Filters unnecessary partitions during query execution
- D . Increases query complexity and optimization
C
Explanation:
Partition pruning in Snowflake filters out unnecessary partitions during query execution, significantly enhancing query performance by minimizing the data scanned during the query.