Practice Free DAA-C01 Exam Online Questions
In diagnostic analysis, what importance do demographics and relationships hold in identifying anomalies? (Select all that apply)
- A . Considering relationships among data variables
- B . Identifying demographic variations linked to anomalies
- C . Ignoring data relationships for focused analysis
- D . Analyzing only recent demographic data for anomalies
A,B
Explanation:
Identifying demographic variations and considering relationships are crucial in identifying anomalies during diagnostic analysis.
When managing Snowsight dashboards, what role do subscriptions and updates play in meeting business requirements?
- A . Subscriptions and updates ensure timely information delivery.
- B . They enhance dashboard usability without impacting data updates.
- C . Subscriptions and updates don’t impact dashboard management.
- D . Managing subscriptions and updates complicates dashboard usage.
A
Explanation:
Subscriptions and updates ensure timely information delivery, meeting business requirements.
How do partitioning strategies impact query performance and data storage efficiency in Snowflake?
- A . Partitioning improves query planning only
- B . Enhances query performance and reduces storage requirements
- C . Limits data access for specific user roles
- D . Reduces query performance and increases storage requirements
B
Explanation:
Effective partitioning strategies enhance query performance by optimizing data retrieval and storage efficiency in Snowflake.
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.
C
Explanation:
Stored Procedures aid in data analysis by enabling custom and repeated data operations, enhancing efficiency.
When evaluating and selecting data for building dashboards, what factors should be considered for ensuring data relevance and usefulness? (Select all that apply)
- A . Ignoring data complexities for simplicity in visualization
- B . Evaluating data based on business requirements
- C . Including all available data for comprehensive visualization
- D . Filtering data based on irrelevant attributes
B,D
Explanation:
To ensure relevant and useful dashboards, data must be evaluated based on business requirements and filtered for irrelevant attributes.
Which aspects are crucial for making predictions based on data for forecasting purposes? (Select all that apply)
- A . Using only basic arithmetic functions for forecasting
- B . Considering trends and anomalies in historical data
- C . Incorporating statistical methods for accurate predictions
- D . Relying solely on historical data without considering external factors
B,C
Explanation:
Incorporating statistical methods and considering trends/anomalies are crucial for accurate predictions in
forecasting.
When cleaning data, what role does using clones play in specific use-cases?
- A . Clones help preserve original data for audit purposes only
- B . Clones slow down the data cleaning process significantly
- C . Clones aid in isolating and resolving data anomalies
- D . Clones are unnecessary for data cleaning tasks
C
Explanation:
Clones are beneficial in isolating and resolving data anomalies without impacting the original dataset, facilitating safe data cleaning practices.
How does leveraging clones aid in handling specific use-cases and maintaining data integrity in Snowflake?
- A . Clones restrict data access for specific user roles
- B . Clones enforce data consistency across multiple warehouses
- C . Clones allow isolated testing and analysis without impacting original data
- D . Clones facilitate real-time data updates
C
Explanation:
Clones in Snowflake enable isolated testing and analysis without affecting original data, supporting specific use-cases while maintaining data integrity by providing a separate environment for manipulation.
How do statistics and built-in functions contribute to forecasting based on data?
- A . These functions enable the creation of custom forecasting models, offering flexibility.
- B . They solely aid in data aggregation for forecasting purposes.
- C . They limit forecasting to predefined models without flexibility.
- D . Statistics and functions hinder the forecasting process by complicating data visualization.
A
Explanation:
Statistics and built-in functions facilitate the creation of custom forecasting models, providing flexibility.
When designing a data collection system, what factors should be considered when assessing how often data needs to be collected? (Select all that apply)
- A . Volume of data
- B . Business requirements
- C . Data collection tool limitations
- D . Data source availability
A,B
Explanation:
Assessing data collection frequency involves considering business requirements and the volume of data necessary for analysis.