Practice Free DAA-C01 Exam Online Questions
What role does operationalizing data play in maintaining reports and dashboards for business requirements?
- A . It restricts data updates, affecting dashboard accuracy.
- B . It limits the usability of reports by narrowing down access.
- C . Operationalizing data complicates dashboard management.
- D . Operationalizing data ensures consistent and efficient usage.
D
Explanation:
Operationalizing data ensures consistent and efficient usage of reports and dashboards.
How does understanding and analyzing the Query Profile contribute to query optimization in Snowflake?
- A . Facilitates query planning and execution analysis
- B . Validates query result consistency
- C . Provides real-time data updates
- D . Limits query access for specific user roles
A
Explanation:
Analyzing the Query Profile aids in understanding query planning and execution, offering insights into optimizing query performance in Snowflake by identifying execution steps and bottlenecks.
In Snowflake, what factors determine the effectiveness of using materialized views for query optimization?
- A . Limitations in accessing historical data
- B . Compatibility with specific BI tools only
- C . Query result caching capabilities
- D . Frequency of data updates and refresh requirements
C,D
Explanation:
Materialized views’ effectiveness depends on factors like data update frequency and query result caching, impacting query optimization based on the nature of data updates and caching capabilities.
When performing forecasting, which statistical method is commonly used based on historical data?
- A . Regression analysis
- B . Data normalization
- C . Inferential statistics
- D . Simple data aggregation
A
Explanation:
Regression analysis is frequently used for forecasting based on historical data, predicting future trends.
How do stored procedures contribute to data analysis efficiency in SQL compared to UDFs?
- A . They enable the execution of repetitive tasks, enhancing efficiency.
- B . Stored procedures allow limited data accessibility for improved security.
- C . UDFs enhance query performance more effectively than stored procedures.
- D . Stored procedures hinder customization in data operations.
A
Explanation:
Stored procedures enhance efficiency by enabling the execution of repetitive tasks.
Which action is crucial in performing diagnostic analysis to identify reasons/causes of anomalies in historical data?
- A . Collecting unrelated data and ignoring statistical trends
- B . Ignoring demographic variations in the data
- C . Collecting related data and demographics
- D . Analyzing data from isolated points in time
C
Explanation:
Collecting related data and demographics is crucial in identifying reasons/causes of anomalies in historical data.
How does incorporating visualizations in reports and dashboards aid in presenting data for business use analyses?
- A . Visualizations enhance data comprehension for effective analysis.
- B . It limits data presentation to textual formats only.
- C . Visualizations complicate data representation, hindering analysis.
- D . Presenting data visually doesn’t impact business use analyses.
A
Explanation:
Visualizations enhance data comprehension, aiding effective analysis in business use scenarios.
How do exploratory ad-hoc analyses differ from routine analysis?
- A . They involve querying known patterns without exploring further.
- B . Ad-hoc analyses deviate from established routines, exploring patterns and anomalies in data.
- C . Ad-hoc analyses focus on anomalies and established trends.
- D . Ad-hoc analyses rely heavily on predefined queries.
B
Explanation:
Ad-hoc analyses deviate from established routines, exploring patterns and anomalies in data beyond predefined queries.
What actions are involved in data discovery to identify necessary elements from available datasets in Snowflake? (Select all that apply)
- A . Running SQL queries on tables
- B . Evaluating necessary transformations
- C . Performing data mining techniques
- D . Identifying missing data fields
A,B
Explanation:
Data discovery in Snowflake involves querying tables and evaluating required transformations for dataset refinement.
In Snowsight, why is the utilization of different chart types crucial for effective data analysis and interpretation?
- A . Snowsight doesn’t support multiple chart types.
- B . It limits users’ ability to visualize data accurately.
- C . Multiple chart types in Snowsight hinder data interpretation.
- D . Different chart types offer diverse data representation.
D
Explanation:
Different chart types offer varied data representation, aiding analysis and interpretation in Snowsight.